PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 EPA Document# EPA-740-S-23-001 August 2023 Office of Chemical Safety and Pollution Prevention &ERA United States Environmental Protection Agency White Paper: Quantitative Human Health Approach to be Applied in the Risk Evaluation for Asbestos Part 2 - Supplemental Evaluation including Legacy Uses and Associated Disposals of Asbestos August 2023 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 33 TABLE OF CONTENTS 34 ACKNOWLEDGEMENTS 4 35 1 INTRODUCTION 5 36 1.1 Overview 5 37 1.2 Summary of Part 1 of the Risk Evaluation 6 38 1.3 Scope and Purpose of Part 2 of the Risk Evaluation 6 39 2 STRUCTURE OF THE WHITE PAPER 9 40 3 SYSTEMATIC APPROACH TO IDENTIFY DOSE-RESPONSE INFORMATION 10 41 3.1 Step 1: Comprehensive Literature Search 11 42 3.2 Steps 2 & 3: Studies Meeting PECO Criteria at Title/Abstract and Full-Text Screening 12 43 3.3 Steps 4 & 5: Filtering of Studies for Dose-Response Consideration 12 44 3.3.1 Step 4: Standardized Mortality Ratios and Regression Analysis 12 45 3.3.2 Step 5: Exposure Measurement and Exposure Assignment in Analysis 12 46 3.3.2.1 Exposure Measurement 12 47 3.3.2.2 Exposure Assignment in Analysis 13 48 3.4 Step 6: Consideration of Cohorts for Dose-Response Analysis 13 49 4 NON-CANCER DOSE-RESPONSE FOR ASBESTOS 15 50 4.1 Systematic Approach for Identification of Epidemiologic Cohorts for Non-cancer Effects 15 51 4.2 IRIS Libby Amphibole Assessment: Non-cancer Dose-Response 17 52 4.3 Quantitative Non-cancer Approach for the Risk Evaluation for Asbestos Part 2 18 53 5 CANCER DOSE-RESPONSE FOR ASBESTOS 20 54 5.1 Identification of Epidemiologic Cohort for Cancer Dose-Response 20 55 5.2 1988 IRIS Asbestos Assessment 25 56 5.3 IRIS Libby Amphibole Assessment Cancer Dose-Response 26 57 5.4 Part 1 Risk Evaluation for Asbestos: Dose-Response 27 58 5.5 Part 2 Risk Evaluation for Asbestos: Quantitative Cancer Approach 29 59 6 SUMMARY AND NEXT STEPS 32 60 REFERENCES 33 61 APPENDICES 38 62 Appendix A ABBREVIATIONS AND ACRONYMS 38 63 Appendix B SYSTEMATIC REVIEW APPROACH 40 64 B.l Data Search and Screening 43 65 B.l.l Data Search 43 66 B.l.2 Data Screening 43 67 B,2 Identification of Studies Potentially Informative for Dose-Response Analysis 44 68 B.3 Data Quality Evaluation 49 69 B.4 Consideration of Epidemiologic Cohorts for Dose-Response Analysis 50 70 Appendix C NON-CANCER EPIDEMIOLOGIC COHORTS 51 71 C.l Cohorts Included in the IRIS Libby Amphibole Assessment 51 72 C.2 Cohorts Not Previously Considered in Non-cancer Assessments 52 Page 2 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 73 Appendix D CANCER EPIDEMIOLOGIC COHORTS 54 74 D. 1 Cohorts Included in the Risk Evaluation for Asbestos Part 1 54 75 D.2 Cohorts Included in the IRIS Libby Amphibole Asbestos Assessment 59 76 D.3 Cohorts (Mixed-Fiber) Included in the IRIS Asbestos Assessment 59 77 D.4 Cohorts Not Included in Existing EPA Assessments 61 78 Appendix E LITERATURE INVENTORY FORM 63 79 Appendix F POPULATIONS, EXPOSURES, COMPARATORS, AND OUTCOMES 80 (PECO) CRITERIA FOR PART 2 OF THE RISK EVALUATION FOR ASBESTOS 65 81 Appendix G DATA QUALITY EVALUATION CRITERIA 68 82 83 LIST OF TABLES 84 Table 4-1. Cohorts Identified for Consideration in Asbestos Part 2 Non-cancer Dose-Response 85 Analysis 15 86 Table 5-1. Cohorts Identified for Consideration in Asbestos Part 2 Cancer Dose-Response Analysis.... 21 87 Table 5-2. Comparison of EPA Inhalation Unit Risk Values for Asbestos 30 88 89 LIST OF FIGURES 90 Figure 3-1. Schematic of the Approach Used to Identify Epidemiologic Studies for Dose-Response 91 Consideration 11 92 93 LIST OF APPENDIX TABLES 94 TableApx F-l. PECO Criteria for Asbestos Part 2 (Legacy Uses and Associated Disposals) 65 95 Table Apx F-2. Major Categories of "Potentially Relevant Supplemental Material" 67 96 Table_Apx G-l. Mesothelioma Criteria 68 97 Table Apx G-2. Other Outcomes Data Quality Evaluation Criteria 83 98 99 LIST OF APPENDIX FIGURES 100 FigureApx B-l. Literature Inventory Tree - Environmental and Human Health Hazard for Asbestos 101 Part 2 41 102 Figure Apx B-2. Literature Flow Diagram Presenting the Identification, Screening, and Evaluation of 103 Literature 42 104 Page 3 of 102 ------- 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 ACKNOWLEDGEMENTS This report was developed by the United States Environmental Protection Agency (U.S. EPA), Office of Chemical Safety and Pollution Prevention (OCSPP), Office of Pollution Prevention and Toxics (OPPT). Acknowledgements The Assessment Team gratefully acknowledges the participation, input, and review comments from OPPT and OCSPP senior managers and science advisors as well as assistance from EPA contractors Battelle (Contract No. EPW16017), ERG (Contract No. 68HERD20A0002), ICF (Contract No. 68HERC19D0003), SpecPro Professional Services, LLC (Contract No. 68HERC20D0021), General Dynamics Information Technology, Inc. (Contract No. HHSN316201200013W), and SRC (Contract No. 68HERH19D0022). Special acknowledgement is given for the contributions of technical experts from EPA's Office of Research and Development (ORD), including Tom Bateson and Leonid Kopylev. Docket Supporting information can be found in the public docket (Docket ID: EPA-HQ-QPPT-2023-0309). Disclaimer Reference herein to any specific commercial products, process, or service by trade name, trademark, manufacturer, or otherwise does not constitute or imply its endorsement, recommendation, or favoring by the United States Government. Authors: Jennifer Nichols (Assessment Lead), Christelene Horton, Ryan Klein, and Leora Vegosen Contributors: Rony Arauz Melendez, Sarah Au, Jone Corrales, Ann Huang, Ross Geredien Technical Support: Mark Gibson, Hillary Hollinger, Grace Kaupas Direction, input, and approval was given by OCSPP scientific and executive leadership. Page 4 of 102 ------- 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 1 INTRODUCTION 1.1 Overview EPA's programs have evaluated various aspects of asbestos hazard and exposure over many decades. Pursuant to TSCA section 6(b)(2)(A), asbestos was designated as one of the first 10 chemical substances for the OPPT's initial risk evaluations in December 2016 (81 FR 91927). EPA's Integrated Risk Information System (IRIS) in ORD completed an Asbestos Assessment and Libby Amphibole Asbestos (LAA) Assessment in 1988 and 2014, respectively, which are used by EPA program offices such as risk assessments conducted under the Superfund program in the Office of Land and Emergency Management (OLEM). OPPT's Risk Evaluation for Asbestos Part 1: Chrysotile Asbestos (hereafter "Part 1 of the Risk Evaluation" or "Part 1") was released in December 2020 (U.S. EPA. 2020). Part 1 focused on inhalation exposures and mesothelioma and lung, laryngeal, and ovarian cancer and did not evaluate oral or dermal exposures or non-cancer effects. Part 1 also excluded consideration of all asbestos fiber types besides chrysotile and is solely focused on ongoing uses. EPA is currently developing Part 2 of the Risk Evaluation for Asbestos (hereafter "Part 2 of the Risk Evaluation" or "Part 2") that will provide a more comprehensive evaluation of the human health risks of asbestos, including all fiber types as well as cancer and non-cancer effects from all relevant routes of exposure, which EPA agreed to consider as part of an agreement that was reached for the purpose of resolving a petition for review of Part 1 of the Risk Evaluation (see AD AO, et al. v. EPA, No. 21-70160 (9th Cir. Oct. 2021)). For the human health assessment in Part 2, OPPT has continued to focus on epidemiologic evidence and evaluated cancer and non-cancer evidence and conclusions from the existing EPA assessments in addition to other studies identified from a recently conducted systematic review approach.1 The purpose of this white paper is to describe the systematic review considerations and criteria for identifying studies for dose-response analysis, to evaluate and compare existing cancer inhalation unit risks (IURs, see also Footnote 3) and the non-cancer point of departure (POD) with the results of the new systematic review, and to propose a cancer IUR and non-cancer POD for use in Part 2. In summary, OPPT has made the following findings: • OPPT conducted systematic review to identify the reasonably available information relevant for consideration in the quantitative human health approach to be applied in Part 2 of the Risk Evaluation for Asbestos. This included identification of cancer and non-cancer epidemiologic studies from oral, dermal, and inhalation routes of exposure. • OPPT has not identified any cancer or non-cancer epidemiologic studies from oral or dermal exposures that support dose-response analysis; therefore, OPPT is not proposing cancer or non- cancer values for these routes. • For inhalation exposures, OPPT has identified several inhalation epidemiologic studies (or cohorts) for non-cancer effects, including some that were considered in the IRIS LAA Assessment (U.S. EPA. 2014b). However, none of those studies warranted an updated dose- response analysis for the non-cancer POD. OPPT is proposing to use the existing POD of 2.6x 10~2 fiber/cc from the IRIS LAA Assessment to assess non-cancer risks in Part 2 with application of appropriate uncertainty factors (UFs). 1 While the white paper specifically focuses on the quantitative human health assessment and dose-response considerations. Part 2 of the Risk Evaluation for Asbestos will address studies relevant to hazard identification but not informative for dose- response assessment. Page 5 of 102 ------- 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 • OPPT did not identify any inhalation cancer cohorts beyond those considered by previous EPA assessments, including for cancers other than mesothelioma and lung cancer, which would warrant an updated dose-response assessment. • The existing IURs derived by EPA, 0.23, 0.17, and 0.16 per fiber/cc, are based on lung cancer and mesothelioma with quantitative adjustment for laryngeal and ovarian cancers in the development of the IUR of 0.16 per fiber/cc in the Part 1 Risk Evaluation. Despite each value being derived from different information and epidemiologic cohorts, and therefore having different strengths and uncertainties, the values are notably similar and round to 0.2 per fiber/cc. OPPT is proposing to use an IUR of 0.2 per fiber/cc in Part 2 of the Risk Evaluation for Asbestos. EPA is soliciting comment on these proposals and associated analyses. This document, and associated independent, expert peer review, are solely focused on the human hazard characterization and dose response to support Part 2 of the Risk Evaluation for Asbestos. OPPT will subsequently release a draft Part 2 risk evaluation, including a complete risk characterization and presentation of risk determination, which will be made available for public comment pursuant to TSCA section 6(15 U.S.C. 2605(b)(4)(H) (U.S. EPA. 2017a). OPPT will also release an accompanying Systematic Review Protocol for Asbestos at that time. 1.2 Summary of Part 1 of the Risk Evaluation For Part 1 of OPPT's Risk Evaluation for Asbestos, EPA initially adopted the definition of asbestos as defined by TSCA Title II (added to TSCA in 1986), section 202 as the "asbestiform varieties of six fiber types - chrysotile (serpentine), crocidolite (riebeckite), amosite (cummingtonite-grunerite), anthophyllite, tremolite or actinolite." However, a choice was made to focus Part 1 solely on chrysotile asbestos as this is the only asbestos fiber type that is currently imported, processed, or distributed in the United States. EPA informed the public of this decision to focus on ongoing uses of asbestos and exclude legacy uses and disposals in the Scope of the Risk Evaluation for Asbestos, released in June 2017 (U.S. EPA. 2017b). However, in late 2019, the court in Safer Chemicals, Healthy Families v. EPA, 943 F.3d 397 (9th Cir. 2019) held that EPA's Risk Evaluation Rule (82 FR 33726 [July 20, 2017]) should not have excluded "legacy uses" (i.e., uses without ongoing or prospective manufacturing, processing, or distribution for use) or "associated disposals" (i.e., future disposal of legacy uses) from the definition of conditions of use—although the court did uphold EPA's exclusion of "legacy disposals" (i.e., past disposals). Following that court ruling, EPA continued development of the risk evaluation for the ongoing uses of chrysotile asbestos and determined that the complete Risk Evaluation for Asbestos would be issued in two parts. The Risk Evaluation for Asbestos Part 1: Chrysotile Asbestos was released in December (2020). allowing the Agency to expeditiously move into risk management for the unreasonable risk identified in Part 1. 1.3 Scope and Purpose of Part 2 of the Risk Evaluation Following the finalization of Part 1 of the Risk Evaluation for Asbestos, EPA OPPT immediately began development of Part 2, starting with the issuance of a draft scope document. The Final Scope of the Risk Evaluation for Asbestos Part 2: Supplemental Evaluation Including Legacy Uses and Associated Disposals of Asbestos (87 FR 38746) (EP A-HQ-2021 -0254-0044; hereafter "Final Scope") was released in June 2021, reflecting consideration of public comments on a draft scope document. Although Part 1 of the Risk Evaluation adopted the TSCA Title II definition of asbestos, the consideration of legacy uses and associated disposals that will be evaluated in Part 2 warrant broader considerations as asbestos can be co-located geologically with commercially mined substances. In particular, LAA is known to have been present with vermiculite, extracted from an open pit mine near Libby, Montana, until the mine closed in 1990. Vermiculite was widely used in building materials which are an important focus of the Page 6 of 102 ------- 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 evaluation of legacy uses of asbestos. Thus, LAA (and its tremolite, winchite, and richterite constituents) will be considered in Part 2 of the Risk Evaluation. EPA will also determine the relevant conditions of use of asbestos-containing talc, including any "legacy use" and "associated disposal" where asbestos is implicated in Part 2 of the Risk Evaluation. Where the Agency identifies reasonably available information demonstrating asbestos-containing talc conditions of use that fall under TSCA authority, these will be evaluated in Part 2 of the Risk Evaluation for Asbestos. An additional expansion of considerations in Part 2, as described in the Final Scope, pertains to the evaluation of human health effects. Although Part 1 focused on certain cancer outcomes known to be causally related to asbestos exposure (I ARC, 2012,1977), Part 2 will consider non-cancer outcomes at the system level or higher. Historically, there has been a focus on inhalation exposures in health assessments conducted by the EPA and other organizations, but there has also been interest in the updated literature on dermal and oral exposures. These routes of exposure are being considered in Part 2, which EPA agreed to consider as part of an agreement that was reached for the purpose of resolving a petition for review of Part 1 of the Risk Evaluation (see AD AO, et al. v. EPA, No. 21-70160 (9th Cir. Oct. 2021)). A broad range of health effects are examined in the asbestos epidemiologic literature including cancer (e.g., mesothelioma, lung, ovarian, laryngeal, gastrointestinal cancers) and non-cancer (e.g., asbestosis, lung function decrements, pleural plaques/abnormalities, immune-related effects, cardiovascular effects) outcomes. This range of human health outcomes was presented in Figure 2-10 in the Final Scope, and an interactive version of this diagram is available Heat Map of Hazard Screening Results for Asbestos.2 In considering the broad range of health effects and routes of exposure, EPA will continue to focus on the epidemiologic evidence for dose-response as was done in Part 1 and supported by EPA's Science Advisory Committee on Chemicals (SACC). Prior assessments of asbestos conducted by EPA and other agencies have conducted extensive reviews of the literature including epidemiologic and toxicological studies in animals (U.S. EPA. 2020. 2014b: IARC. 2012; AT SDR. 2001; U.S. EPA. 1988. 1986; IARC. 1977). The human health hazards related to asbestos exposure are well-established and there is a robust epidemiologic evidence base. In 1977 and 2012, an International Agency for Research on Cancer (IARC) Working Group reviewed a large body of evidence that covered all fiber types in various epidemiologic studies and settings and found that there is a causal relationship between asbestos inhalation exposure and cancer (mesothelioma and lung, ovarian and laryngeal cancers) and mortality (IARC. 2012. 1977). Additionally, respiratory effects including histopathologic changes (e.g., pleural thickening [LPT], fibrosis, inflammation, etc.) and lung function decrements are consistently observed following asbestos exposure. Some studies have described cardiovascular and immune-related effects, but these effects are demonstrated to occur subsequent to observed respiratory effects (U.S. EPA. 2014b). From a qualitative point of view, the hazards for asbestos are well characterized. Thus, EPA is focusing its efforts on Part 2 on epidemiologic evidence that support quantitative dose-response relationships as needed for the risk evaluation. EPA has conducted an updated systematic review of the literature to identify and evaluate relevant information. In addition, there are three peer-reviewed, existing Agency assessments on asbestos that 2 Details on how the Heat Map of Hazard Screening Results for Asbestos and evidence tables were generated are described in Section 4.7.5 of Draft Systematic Review Protocol Supporting TSCA Risk Evaluations for Chemical Substances (U.S. EPA. 2021a). Page 7 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 264 have derived cancer inhalation unit risk (IUR)3 values and a reference concentration (RfC) for non- 265 cancer effects based on a POD: 266 1. The IRIS Asbestos Assessment (U.S. EPA. 1988) - presenting an IUR of 0.23 per fiber/cc based 267 on combined risk for lung cancer and mesothelioma; 268 2. The IRIS Libby Amphibole Asbestos (LAA) Assessment (U.S. EPA. 2014b) - presenting an 269 IUR of 0.17 per fiber/cc based on combined risk for lung cancer and mesothelioma and an RfC 270 of 9x 10~5 mg/m3 based on a POD of 2.6x 10~2 fiber/cc for LPT in the lungs; and 271 3. The Risk Evaluation for Asbestos Part 1: Chrysotile Asbestos (U.S. EPA. 2020) - presenting an 272 IUR of 0.16 per fiber/cc based on combined risk for lung cancer and mesothelioma, including a 273 quantitative adjustment for laryngeal and ovarian cancer. 3 An IUR is a value representing the upper-bound excess lifetime cancer risk estimated to result from continuous exposure to an agent per fiber/cc of exposure. The IUR can be multiplied by an estimate of lifetime exposure (in fibers/cc) to estimate the lifetime cancer risk. Page 8 of 102 ------- 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 2 STRUCTURE OF THE WHITE PAPER This white paper presents the approach taken to identify and evaluate the most relevant of the reasonably available information to inform human health dose-response considerations in Part 2 of the Risk Evaluation for Asbestos. The remainder of the document is organized into the following major sections: • Section 3 presents an overview of the systematic approach employed to identify the relevant reasonably available information and how the information was screened and categorized to efficiently identify the epidemiologic studies informative for dose-response assessment. • Section 4 presents an overview of identification of non-cancer dose-response information, a synopsis of the selection of the POD and associated evidence from the IRIS LAA Assessment (U.S. EPA. 2014bI and the proposed quantitative non-cancer approach to be applied in Part 2. • Section 5 presents an overview of the cancer dose-response information, a synopsis of the existing IURs from the IRIS Asbestos Assessment (U.S. EPA. 19881 the IRIS LAA Assessment (U.S. EPA. 2014b). the Risk Evaluation for Asbestos Part 1: Chrysotile Asbestos (U.S. EPA. 2020). and the proposed quantitative cancer approach to be applied in Part 2. • Section 6 describes the next steps in this process resulting in the release of a draft Part 2 of the Risk Evaluation for Asbestos for public comment. Additional details on the systematic review approach OPPT used and the underlying evidence for each of the IURs and POD are included in the following seven appendices and one supplemental document: • Appendix A: Abbreviations and Acronyms • Appendix B: Systematic Review Approach • Appendix C: Non-cancer Epidemiologic Cohorts • Appendix D: Cancer Epidemiologic Cohorts • Appendix E: Literature Inventory Form • Appendix F: Populations, Exposures, Comparators, and Outcomes (PECO) Criteria for Part 2 of the Risk Evaluation for Asbestos • Appendix G: Data Quality Evaluation Criteria • Supplemental File: Systematic Review of Data Quality Evaluation Information for Human Health Hazard Epidemiology (U.S. EPA. 2023) Page 9 of 102 ------- 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 3 SYSTEMATIC APPROACH TO IDENTIFY DOSE-RESPONSE INFORMATION This section presents an overview of the process used to identify, screen, and evaluate the reasonably available information in accordance with TSCA section 6. Details of the TSCA systematic review process are described in EPA's Draft Systematic Review Protocol Supporting TSCA Risk Evaluations for Chemical Substances (hereafter "2021 Draft Systematic Review Protocol") (U.S. EPA. 202la), including Appendix A, which describes updates made to that Protocol in response to recommendations from the National Academies of Sciences, Engineering, and Medicine (NASEM), SACC, and public. Subsequent comments from the April 2022 SACC Meeting on the Draft TSCA Systematic Review Protocol included a recommendation of developing chemical-specific protocols. Therefore, an asbestos- specific, supplemental protocol will be included in the forthcoming Part 2 of the Risk Evaluation that will address asbestos-specific updates for all disciplines. Appendix B in this white paper provides details on the systematic review process for epidemiologic studies for asbestos, including updates to and fit-for- purpose application of the methods described in the 2021 Draft Systematic Review Protocol. Figure 3-1 presents a schematic of the process, beginning with a comprehensive literature search (including all disciplines), followed by successive steps to screen the studies, and ultimately considers the most relevant studies for dose-response assessment. Page 10 of 102 ------- 320 321 322 323 324 325 326 327 328 329 330 331 332 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Figure 3-1. Schematic of the Approach Used to Identify Epidemiologic Studies for Dose-Response Consideration TIAB = title/abstract (screening); PCM = phase-contrast microscopy; TEM = transmission electron microscopy 3.1 Step 1: Comprehensive Literature Search For each risk evaluation conducted under TSCA, EPA conducts a comprehensive literature search for reasonably available information (Step 1 in Figure 3-1; see also Appendix B in this document and Section 4 of the 2021 Draft Systematic Review Protocol Supporting TSCA Risk Evaluations for Chemical Substances (U.S. EPA, 2021a). For asbestos, literature searches were conducted for Part 1 of the Risk Evaluation for Asbestos in 2016 and then updated in April 2021 for Part 2 (see Appendix Section C.l .24 of the 2021 Draft Systematic Review Protocol). The comprehensive literature search casts a broad net and includes references for hazard (epidemiology, human health toxicology, and environmental hazard). Page 11 of 102 ------- 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 3.2 Steps 2 & 3: Studies Meeting PECO Criteria at Title/Abstract and Full-Text Screening Following the literature search, initial screening for relevance was conducted at the title/abstract (TIAB) screening level and then subsequently conducted at the full-text level (Steps 2 and 3, respectively, in Figure 3-1). These processes are more thoroughly described in Appendix B in this white paper and the 2021 Draft Systematic Review Protocol (U.S. EPA. 2021a). TIAB and full-text screening was conducted based on criteria specified in the hazard PECO statement. Generally, for the epidemiologic literature, studies on any human population with exposure to one of the fibers included in the asbestos definition (specific to Part 2 of the Risk Evaluation, see PECO in Appendix F) and examining any outcome or route of exposure (inhalation, dermal, oral) were selected for inclusion. The full PECO statement applied for hazard is included in Appendix F. After screening for these criteria at TIAB and full-text, a total of 343 epidemiologic studies were identified as relevant (Step 3 in Figure 3-1). 3.3 Steps 4 & 5: Filtering of Studies for Dose-Response Consideration Following the PECO-based screening of the epidemiologic studies, studies were further characterized according to route of exposure, outcome assessed, analysis type and cohort. In an effort to streamline the identification of dose-response information, OPPT identified criteria to filter the literature that met PECO screening criteria. These modifications to the process described in the 2021 Draft Systematic Review Protocol (U.S. EPA. 2021a) were implemented to efficiently identify studies with dose-response data for full data quality evaluation. They included consideration of the data analysis methods used in the study, exposure measurement methods, and use of exposure assignment in analysis. These modifications and the rationale for their development and use are briefly described below and more thoroughly in Appendix B. 3.3.1 Step 4: Standardized Mortality Ratios and Regression Analysis Given the approach to dose-response analysis conducted in prior asbestos assessments, including Part 1 of the Risk Evaluation for Asbestos, identification of studies that either used standardized mortality ratios (SMRs) or conducted analyses with regression models were determined most likely to be informative for dose-response (Step 4 in Figure 3-1). An SMR is a ratio or percentage describing the increase or decrease in mortality in a given study population relative to the general population and is typically used in studies examining cancer. Regression analyses, in general, describe quantitatively the relationship between an exposure and a response and are typically used in studies examining non-cancer effects. The outputs from studies using SMRs and regression analyses can be used in assessing dose- response. Overall, there were 213 studies using either SMR or regression analyses. 3.3.2 Step 5: Exposure Measurement and Exposure Assignment in Analysis 3.3.2.1 Exposure Measurement It is well-established that the most reliable methods to detect and accurately quantify asbestos fibers are phase-contrast microscopy (PCM)4 and transmission electron microscopy (TEM) (U.S. EPA. 1985). Multiple measurements taken by PCM or TEM for a given exposure setting is preferred over a single measurement. In addition, some studies have utilized measurements of dust from midget impingers, and if a combination of methods are used such that an appropriate conversion factor is available to yield fiber concentrations from dust measurements, these data can also be informative for dose-response. 4 PCM was recommended by the National Institute for Occupational Safety and Health (NIOSH) and Occupational Safety and Health Administration (OSHA) as the preferred asbestos measurement method in 1979 as there was a recognized need for reliable measurement and evaluation of occupational exposure to asbestos to put practices into place to prevent asbestos- related disease (Leidel et al.. 1979). Page 12 of 102 ------- 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 OPPT evaluated exposure measurement methods in studies before evaluating other data quality evaluation criteria to identify those with reliable methods for dose-response (Step 5 in Figure 3-1). Notably, some epidemiologic cohorts considered in the 1988 IRIS Asbestos Assessment were not initially identified in the systematic review approach because the individual publications for these cohorts lacked sufficient detail to meet PECO criteria, including for exposure measurement; however, additional related publications were identified through citations and the information in the 1988 IRIS Asbestos Assessment (U.S. EPA. 1988) and the 1986 Airborne Asbestos Health Assessment Update (U.S. EPA. 1986) provided important information about these cohorts and analyses such that these cohorts warranted consideration in this white paper for dose-response (see Appendix D.3). Studies were considered by cohort groupings. For example, if multiple publications were available on a particular occupational cohort, they were considered as a set of information rather than as independent publications. For the 343 studies that met PECO screening criteria, a total of 156 epidemiologic cohorts were identified, and 66 of these cohorts were the subject of multiple publications. 3.3.2.2 Exposure Assignment in Analysis A variety of approaches can be used in the quantitative analysis within an epidemiologic study; however, understanding the exposure-response relationship in a given population/cohort is best informed when the analysis is conducted with consideration of three or more exposure levels or a model using a continuous exposure measure (Step 5 in Figure 3-1). For example, analyses presenting results based on only an unexposed and an exposed group is minimally informative for dose-response relative to studies presenting responses for a broader range of exposure levels. Thus, studies using appropriate exposure measurement methods and containing three or more exposure groups or a continuous measure of exposure were identified to undergo data quality evaluation. A total of 43 cohorts meeting these additional criteria of using regression or SMR and having appropriate exposure measurement and exposure assignment in analysis were identified for further consideration. These cohorts subsequently underwent data quality evaluation (Step 5 in Figure 3-1), as explained in Appendix B of this white paper and in Appendix R of the Draft Systematic Review Protocol Supporting TSCA Risk Evaluations for Chemical Substances (U.S. EPA. 2021a). Study quality evaluations were conducted using DistillerSR, and the summary of the data evaluation results are included in a Supplemental File (U.S. EPA. 2023). Briefly, the evaluation of study quality includes consideration of 22 different metrics that are rated as High, Medium, Low, or Critically Deficient based on pre-defined criteria. The assessment of each of the metrics contributes to an overall quality determination (OQD) of High, Medium, Low, or Uninformative. Cohorts with an OQD of Medium or High were further considered for dose-response assessment, of this white paper and in Appendix R of the Draft Systematic Review Protocol Supporting TSCA Risk Evaluations for Chemical Substances (U.S. EPA. 2021a). Study quality evaluations were conducted using Distiller SR, and the summary of the data evaluation results are included in a Supplemental File (U.S. EPA. 2023). Briefly, the evaluation of study quality includes consideration of 22 different metrics that are rated as High, Medium, Low, or Critically Deficient based on pre-defined criteria. The assessment of each of the metrics contributes to an overall quality determination (OQD) of High, Medium, Low, or Uninformative. Cohorts with an OQD of Medium or High were further considered for dose-response assessment. 3.4 Step 6: Consideration of Cohorts for Dose-Response Analysis Cohorts with studies receiving an OQD of Medium or High were categorized for examination of cancer and/or non-cancer outcomes. Review of the exposure and outcome data and analysis performed was done to confirm (1) the use of PCM or TEM for measurement of asbestos fibers or application of appropriate conversion factors to dust measurements, (2) the use of air measurements in the analysis, (3) Page 13 of 102 ------- 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 the analysis was conducted with health outcome data, and (4) there was adequate assessment of the outcome (e.g., sufficient follow-up time). While these four aspects were considered as part of the data quality evaluation, considering these factors in light of dose-response analysis provides a more detailed perspective. Ultimately, 32 cohorts were removed from further consideration at this point because the quantitative analyses were done with dust measurements or fiber measurements not using PCM or TEM and did not have conversion factors or because they had received a Low or Uninformative OQD rating in data quality evaluation. As noted previously, in the case of some cohorts considered in the Airborne Asbestos Health Assessment Update (U.S. EPA. 1986). additional information on conversion of dust measurements to fiber counts was available to enable use and consideration of these studies in the context of dose-response (see Appendix D.3). Finally, the extent to which cohorts may inform an exposure-response relationship was evaluated using considerations primarily aimed at the identification of high-quality exposure and outcome data to inform the estimation of an IUR and/or a POD. The list of considerations provided below was used to aid in making judgements regarding which studies or studies from a group of studies quantitatively evaluated the exposure-response relationship for asbestos to derive an estimation of its effect on the outcome in the studied population. EPA considered time since first exposure (TSFE) because it is a predictor of risk. The job exposure metric (JEM) was used because the table provides estimated exposure levels in air (fibers/cc) for workers in each job for each year. The Agency utilized these considerations, which were identified in the IRIS LAA Assessment as characteristics necessary for identifying principal studies with the greatest confidence that might inform the dose-response assessment (U.S. EPA. 2014b). A total of 19 cohorts were under consideration at this stage. Cohorts that were deemed most useful for dose- response assessment adhered to the following considerations: 1. Medium or High OQD; 2. Asbestos fibers collected on membrane filters and analyzed using PCM or TEM or a conversion factor from early measurement of total dust particles in million particles per cubic foot (mppcf) to estimate fiber/mL or the equivalent fiber/cc; 3. Used continuous measure of exposure rather than categorical exposure levels (e.g., quartiles) to provide more granular details on the exposure-response relationship; 4. Models that used individual-level exposure assignment methods; 5. Availability of data on TSFE matched to the exposure data, as this is needed to model asbestos- related outcomes in dose-response analysis (U.S. EPA. 2014b); 6. Timing of exposure relative to the outcome; 7. Sufficient length of follow-up for outcome assessment, recognizing the extended latency of asbestos-related outcomes; 8. Studies that provide information on the exposure-response relationship between asbestos exposure and outcome; and 9. Use of a JEM to accurately reconstruct workers' exposure histories to derive a cumulative exposure for each individual over the course of the relevant exposure period. While Appendix C and Appendix D provide a description of each of the non-cancer and cancer cohorts, respectively, Sections 4 and 5 focus more specifically on the key dose-response information for cancer and non-cancer, respectively, for Part 2 of the Risk Evaluation. Each of these sections provides an overview of cohorts available and describes the relevant non-cancer POD or IURs and the underlying data and specific cohort upon which they are based. The approach to be applied in Part 2 of the Risk Evaluation for Asbestos for non-cancer and cancer outcomes is also described in each of these sections. Page 14 of 102 ------- 465 466 467 468 469 470 471 472 473 474 475 476 All 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 4 NON-CANCER DOSE-RESPONSE FOR ASBESTOS Section 4.1 presents an overview of the literature identified for non-cancer dose-response information for asbestos exposures. Section 4.2 presents an overview of the non-cancer dose-response analysis from the IRIS LAA Assessment (U.S. EPA. 2014b). while Appendix C provides additional discussion of other cohorts for which dose-response data were available. Ultimately, new dose-response analyses were not warranted for Part 2. Section 4.3 describes the non-cancer quantitative approach to be applied in Part 2 of the Risk Evaluation for Asbestos. 4.1 Systematic Approach for Identification of Epidemiologic Cohorts for Non-cancer Effects Application of the systematic review approach described in Section 3 resulted in the identification of seven cohorts for consideration in assessing dose response of non-cancer outcomes related to asbestos exposures. All of the cohorts identified examined inhalation exposures. Epidemiologic studies examining oral or dermal exposures with dose-response information were not identified by the systematic review approach. The outcomes assessed in the identified cohorts included non-cancer mortality (including asbestosis and pneumoconiosis), pleural changes/thickening, and lung function changes. Some of these cohorts were identified and considered in the IRIS LAA Assessment (U.S. EPA. 2014a). which is the only EPA assessment that quantitatively considered non-cancer effects. The cohorts are listed and briefly described in Table 4-1 and are more thoroughly presented in Appendix C. Based on the considerations described in Appendix C, it was determined that the O.M. Scott Marysville, OH, Plant Cohort provides the most robust data for dose-response assessment for non-cancer outcomes. This determination was based on reliable individual-level measurements of asbestos exposures and detection of pleural thickening, an early adverse effect. This cohort and the selection of the POD, uncertainty factors, and derivation of RfC are described further in Section 4.2. The other six cohorts OPPT identified, which were not within the scope of the IRIS LAA Assessment, were less suitable for non- cancer dose-response assessment because the outcomes examined were less sensitive (i.e., mortality- related outcomes) and/or because there was greater uncertainty in the exposure data (e.g., community- based measurements rather than personal sampling). Generally, for dose-response assessment, preference is given to studies examining the most sensitive outcome(s), so although mortality can be used in the assessment, it is less sensitive than a well-described outcome preceding mortality from a disease state. Appendix C provides more details on the dose-response considerations for each cohort. Table 4-1. Cohorts Identified for Consideration in Asbestos Part 2 Non-cancer Dose-Response Analysis Cohort Name (Reference [s]) Cohort Description Non-cancer Outcome(s) Data Quality Evaluation Rating IRIS Libby Amphibole Asbestos Assessment, 2014 O.M. Scott Marysville, OH, Plant Cohort (Lockev et al.. 1984) (Rohs et al.. 2008) • Cohort included 530 workers with known vermiculite exposure participated in the 1980 investigation. Eight different worksite operations at the ore processing plant were represented. • Monitoring of industrial hygiene at the facility started in 1972, including personal breathing zone sampling. PCM measurements beginning after 1976. • Job exposure matrix used to determine cumulative exposures. Pulmonary function Mortality High Page 15 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Cohort Name (Reference [s]) Cohort Description Non-cancer Outcome(s) Data Quality Evaluation Rating • Follow-up including chest x-rays and interview information from 280 of the 431 workers who were known to be alive between 2002 and 2005. • Followed up on the respiratory effects in the cohort conducted in 2012. Libby, MT, Vermiculite Mining and Milling Cohort • Participants were white men who had worked for at least 1 year in the mine and mill. • Reports based on follow-up data from 1960 to 2006. • Air sampling data were used to build a job-exposure matrix assigning daily exposures (8-hour time-weighted average [TWA]) for selected job codes. • Individual work histories and the mine and mill job-exposure matrix were used to determine individual exposure metrics. Mortality Medium Cohorts not included in previous EPA assessments for non-cancer effects SC Textiles Cohort • Textile plant in Charleston, SC and used asbestos from 1909 to 1977. • Original cohort of textile workers limited to white males employed for at least 1 month between 1940 and 1965. Later expanded to included non-whites and females. • Individual-level exposures estimates derived from detailed work histories and extensive air measurements using PCM and conversion of dust measurements from analysis of paired sampling. Mortality Medium SC Vermiculite Miners Cohort (W. R. Grace & Co. 1988) • Cohort composed of 194 men hired between 1949 and 1974 in mining/milling of vermiculite in Enoree, SC. • 58 air samples collected in 1986 and analyzed by PCM. Mortality, parenchymal abnormalities including pleural thickening and sputum analysis Medium Anatolia, Turkey, Villagers Cohort (Metintas et al.. 2005) • Field-based, cross-sectional study of 991 villagers from 10 randomly selected villages with known asbestos-containing white soil. • Indoor and outdoor air sample taken for each village; fibers counted by PCM. Pleural plaques, asbestosis, diffuse pleural fibrosis High Wittenoom, Australia, Residents Cohort • Residential cohort included 4659 individuals residing for at least 1 month in Wittenoom between 1943 and 1992. Mine workers excluded. Mortality Medium Page 16 of 102 ------- 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Cohort Name (Reference [s]) Cohort Description Non-cancer Outcome(s) Data Quality Evaluation Rating • Follow-up in 1993, 2000, and 2004 • Ambient exposures from nearby crocidolite assigned based on dates of residence, assigned exposure intensity, and period personal monitoring after operations ceased. Chinese Chrysotile Textile Factory Cohort (Huana. 1990) • Cohort of 776 workers employed for at least 3 years in chrysotile textile product factory; Shanghai. • 17 workplaces in the factory selected for routine sampling; dust and fiber measurements collected by membrane filters. • Follow-up through September 1982 for asbestos diagnosis. Asbestosis incidence Medium 4.2 IRIS Libby Amphibole Assessment: Non-cancer Dose-Response The IRIS LAA Assessment conducted a dose-response assessment for non-cancer effects utilizing data from a cohort of workers in the O.M. Scott plant in Marysville, Ohio. The O.M. Scott plant was a site that received vermiculite from Libby, Montana, by rail where it was processed into expanded form for use as an inert carrier for herbicides and fertilizers. A total of 512 workers participated in the 1980 investigation of pulmonary effects in Ohio plant workers (Lockev et al.. 1984). Workers were drawn from a variety of departments/facilities, including production and packaging of commercial products, maintenance, research, the front office, and the polyform plant. The initial study of this cohort utilized air sample measurements collected in 1972 to assign cumulative worker exposures based on individual job histories. Outcomes were assessed by radiologist readings of chest x-ray films and spirometry for lung function measures. A follow-up of this cohort was conducted nearly 25 years later, providing more robust exposure-response analyses (Rohs et al.. 2008). In this follow-up analysis (Rohs et al.. 2008). the cohort was limited to men hired after 1972 as there was more certainty in the exposure estimates; post-1972 measurements were taken by industrial hygienists who followed employees during the course of their work with sampling devices. Sampling data were also collected within personal breathing zones beginning in 1977. Detailed employee records were used to construct exposure histories and estimate cumulative asbestos exposures for each individual. Health outcomes were assessed in 1980 and between 2002 and 2005; however, the use of different protocols was considered an uncertainty and the later film readings were deemed more reliable. In addition, the later radiographic films extended the follow-up time by roughly 25 years, which is important given the latency of effects. These considerations resulted in a sub-cohort of 119 men for which robust exposure and outcome data were available for dose-response modeling. With the data from the sub-cohort, a range of dose-response model forms were evaluated, but the most suitable model fitting results were obtained using the Dichotomous Hill model using the mean exposure and pleural thickening. Various covariates were examined in model-fitting; however, none appeared to be a confounder or a significant predictor of outcome risk in the model. One covariate examined, TSFE, has been demonstrated to be an important predictor of asbestos-related effects (Loomis et al.. 2019). However, TSFE in the model did not improve model-fitting results, presumably due to the low variability across the dataset. Given the known importance of TSFE, its impact on outcome was Page 17 of 102 ------- 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 determined using the broader set of cohort data (including those hired prior to 1972), which was then incorporated as a fixed regression coefficient in the model. In the modeling, a benchmark response (BMR) of 10 percent was used based on considerations of adversity for LPT. The benchmark concentration is the level of exposure expected to result in the excess risk defined by the BMR. More specific details and results of model-fitting are presented in Section 5.2.2.6.1 in the IRIS LAA Assessment (U.S. EPA. 2014b). A POD based on a 10 percent BMR for LPT was calculated to be 2.6xl0~2 fiber/cc. The IRIS program noted important uncertainties related to the underlying evidence base for this POD and applied UFs to account for intraspecies variability (UFh of 10), database uncertainty (UFd of 3), and data-informed sub chronic-to-chronic uncertainty (UFs of 10) in the 2014 LAA Assessment (U.S. EPA. 2014b). • Regarding the UFh, the occupational cohort included individuals healthy enough to work, and when taking into account human variability, it is plausible that there are more sensitive individuals in the population. This uncertainty remains at this time; thus, UFh of 10 continues to be applied. • Regarding the UFd of 3, applied in the IRIS LAA Assessment because of the limited number of cohort studies evaluating the most sensitive non-cancer effects of chronic asbestos exposure, the Agency has reevaluated the appropriateness of UFd of 3 in light of the systematic review. As described in Section 4, no new cohort studies have been published that would inform the dose response relationship for hazards beyond pleural effects and asbestosis for the non-cancer POD. Therefore, the Agency will continue to apply a UFd of 3. • Regarding the UFs, it was anticipated that if the cohort had been followed for longer, even more cases of LPT would have been identified. The cohort used to derive the 2014 IRIS RfC, O.M. Scott Marysville, OH, was followed for approximately 30 years. The IRIS LAA Assessment determined that it was appropriate to apply a UFs because even 30 years of observation is insufficient to describe lifetime risk of LPT, which continues to increase over a person's lifetime (see page 5-42 of the IRIS LAA Assessment for further rationale for applying the UFs (U.S. EPA. 2014a)). The IRIS LAA Assessment, therefore, derived a data informed UFs of 10 based on the fact that "the central estimate of the risk at TSFE = 70 years is ~10-fold greater than the central estimate of the risk at TSFE = 28 years (from 6% to 61%)" (see page 5-43 of the IRIS LAA Assessment for further details (U.S. EPA. 2014a)). TSFE in the model was set at 28 years due to limitations in the statistical uncertainty. 4.3 Quantitative Non-cancer Approach for the Risk Evaluation for Asbestos Part 2 As described in Section 3.1, seven epidemiologic cohorts were identified for consideration in dose- response analysis (Table 4-1): two occupational cohorts considered in the IRIS LAA Assessment as well as three additional occupational cohorts and two community-based cohorts. When considering specific attributes of the cohorts and available data (see Appendix B), the two occupational cohorts from the Libby assessment were the most informative for dose-response, and the O.M. Scott Marysville, OH, Fertilizer Plant Workers Cohort continues to be the most robust. This is because of the confidence in the individual-level exposure and outcome data in addition to having sufficient follow-up time, as described more fully in the IRIS LAA Assessment and as summarized in the preceding section (4.2) (U.S. EPA. 2014b). Also of note is that dose-response assessment for non-cancer effects is typically conducted for the most sensitive endpoint or the earliest observed adverse effect. Page 18 of 102 ------- 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Given the above, use of the LAA POD from the IRIS assessment in Part 2 of the Risk Evaluation is a reliable approach to quantitatively consider non-cancer risks from asbestos exposures. While there is some uncertainty in application of a Libby-specific POD for exposures to a broader range of asbestos fibers, the uncertainty of using other studies for quantitative assessment would be even greater given the limited exposure characterization for those cohorts (SC Vermiculite Miners Cohort; Anatolia, Turkey, Villagers Cohort) (see Appendix C). For example, for the SC Vermiculite Miners Cohort, non-cancer outcomes were only categorically analyzed as exposed and unexposed. In addition, details of the exposure assessment are insufficient for dose-response assessment, and there is a lack of information on TSFE. The Anatolia, Turkey, Villagers Cohort constructed individual-level exposure estimates, but these were based on broad assumptions of time spent indoors, outdoors, and sleeping. The other cohorts available for dose-response assessment similarly had exposures to a single fiber type and examined mortality as the outcome, which would not be representative of the most sensitive effects known to result from asbestos exposures. Based on the comprehensive approach to identify and evaluate the relevant epidemiologic literature for dose-response assessment of non-cancer effects resulting from asbestos exposures, use of the POD presented in the IRIS LAA Assessment for Part 2 of the Risk Evaluation is proposed. In the IRIS LAA Assessment, LPT was selected as the critical non-cancer effect for POD selection with a BMR of 10 percent extra risk. LPT, as indicated by the presence of pleural plaques is the most effective endpoint to select because it is the outcome that generally appears at lower doses after asbestos inhalation exposure. In summary, EPA is proposing use of the IRIS LAA POD, 2.6x10-2, in Part 2 of the Risk Evaluation and will compare this value to MOEs that will take into account asbestos concentrations from the different exposure scenarios and a benchmark of 300 (UFh =10, UFd = 3, UFs =10) based on the IRIS LAA Assessment as described in Section 4.2. Those specific details will be further developed and described in the draft Part 2 Risk Evaluation that will subsequently be released for public comment. Page 19 of 102 ------- 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 5 CANCER DOSE-RESPONSE FOR ASBESTOS 5.1 Identification of Epidemiologic Cohort for Cancer Dose-Response As described in Section 3 and Appendix B, epidemiologic cohorts providing information for dose- response assessment were identified for non-cancer and cancer outcomes. This process included a comprehensive literature search, PECO-based screening at the TIAB and full-text level, and further filtering of epidemiologic cohorts for exposure measurement and assignment methods, as well as the study analysis. Studies identified describing hazards but not informative for dose-response will be addressed in Part 2 of the Risk Evaluation for Asbestos. Overall, 16 cohorts were identified for consideration in assessing dose response of cancer outcomes related to asbestos exposures. Most of these cohorts were identified and considered in previous assessments, including the 1988 IRIS Asbestos Assessment, the 2014 IRIS LAA Assessment, and the 2020 Part 1 of the Risk Evaluation for Asbestos. Only one cohort was identified that was not previously considered in an EPA assessment—and as a community-based cohort (Wittenoom, Australia, Residents Cohort), rather than an occupational cohort—was unique. All 16 cohorts are listed and briefly described in Table 5-1 and are more thoroughly presented in Appendix C. Because the cohorts identified for dose-response were considered in the derivation of the existing IURs, OPPT focused on these existing IURs and their derivation, as described below in Section 5.2. The single cohort identified that was not considered in any of the existing IURs, while meeting systematic review criteria, did not have exposure data that was better suited for dose-response analysis given the uncertainties in community-based exposure assignment (see Appendix D.4). Thus, this study did not warrant an updated quantitative analysis. The proposed quantitative approach for cancer in Part 2 of the Risk Evaluation is described in Section 5.3 and accounts for each of the existing IURs (see Section 5.2). Page 20 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 623 Table 5-1. Cohorts Identified for Consideration in Asbestos Part 2 Cancer Dose-Response Analysis Cohort Name Cohort Description Cancer Outcomes* Overall Quality Determination (OQD) Rating Risk Evaluation for Asbestos Part 1: Chrysotile Asbestos, 2020 NC Textiles Cohort • Four textile plants imported raw chrysotile fibers to make yarns and woven goods. • 5,770 workers employed for at least 1 day between 1950 and 1973. • Cohort followed through 2003. Mesothelioma, pleural cancer, lung cancer High SC Textiles Cohort • Textile plant in Charleston, SC, and used asbestos from 1909 to 1977. • Original cohort of textile workers limited to white males employed for at least 1 month between 1940 and 1965. Later expanded to included non-white and females. • Individual-level exposures estimates derived from detailed work histories and extensive air measurements using PCM and conversion of dust measurements from analysis of paired sampling. Lung cancer, mesothelioma Medium Quebec, Canada Asbestos Mines and Mills Cohort • Study of chrysotile miners and mill in Thetford mines in Quebec, Canada. • The original cohort was made up of men who were born between 1891 and 1920 and who had worked for at least 1 month in the mines and mills. • Cohort followed from first employment in 1904 to May 1992. • Detail work histories as well as total dust measurement from 4,000 midget impinger dust counts in mppcf per year were analyzed. Mesothelioma, lung cancer Medium Qinghai, China Asbestos Mine Cohort • Study of chrysotile mine in Qinghai Province, China. • Cohort made up of 1,539 male workers who were on the registry January 1, 1981, and who had worked for at least 1 year. • Occupational and work history of cohort was obtained from personnel records and employee. • Cohort followed for vital stats from 1981 to 2006. • Total dust concentrations were measured by area sampling in fixed locations and converted to fiber/cc. Lung cancer, gastrointestinal cancer Medium ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Cohort Name Cohort Description Cancer Outcomes* Overall Quality Determination (OQD) Rating Chongqing, China Asbestos Products Factory Cohort • Chrysotile asbestos plant in Chongqin, China, which produces textile, asbestos cement products, friction materials, rubber products and heat-resistant materials. • Cohort of 515 men were followed from January 1, 1972, to December 31, 1996; workers (men and women) who had worked for less than 1 year were excluded. • Cohort followed until 2008 when women who were employed between 1970 and 1972 were added to analysis. • Airborne dust and fiber concentrations were measured from personal samplers. Lung cancer High Balangero, Italy Mining Cohort • Balangero mine and mill of the Amiantifera Company started in 1916 and produced pure chrysotile asbestos. • Cohort consisted of 1,056 men who worked in mines for at least 1 year between January 1, 1930, and December 31, 1975. • Cohort followed up from January 1, 1946, or date of first employment, to December 31, 2003, or when subjects reached 80 years of age. • Information on cohort collected from mine records. • First fiber counts were first carried out in 1969 and exposure levels before 1969 were reconstructed to represent earlier years. Lung cancer, laryngeal cancer, gastrointestinal cancer, lip cancer, oral cavity and pharynx cancer, esophageal cancer, liver cancer, stomach cancer, colon cancer, rectal cancer peritoneal cancer, pleural cancer, bladder cancer, nervous system cancer, kidney cancer, mesothelioma Medium (lung cancer, laryngeal cancer, oral cavity and pharynx cancer, esophageal cancer, liver cancer, peritoneal cancer, pleural cancer, kidney cancer, mesothelioma) Salonit Anhovo, Slovenia Asbestos Factory Cohort • Salonit Anhovo factory in western Slovenia produced asbestos- cement products made from chrysotile and amphibole asbestos. • Cohort made up of 6,714 workers who had worked for at least 1 day between 1964 and 1994. • Air sampling measurements taken at fixed location close to worker's breathing zone. • Work histories were obtained from personnel files. Lung cancer Medium Page 22 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Cohort Name Cohort Description Cancer Outcomes* Overall Quality Determination (OQD) Rating IRIS Libby Amphibole Asbestos Assessment, 2014 Libby, MT, Vermiculite Mining and Milling Cohort • Cohort included 1,871 vermiculite miners, millers, and processors hired prior to 1970 and employed for at least 1 year at the Montana site. • Subjects followed through December 2006. • Historical air sampling data used to estimate 8-hour TWA. • Work histories including job title and dates of employment were obtained and used to calculate cumulative fiber exposures. Lung cancer, mesothelioma Medium (lung cancer) High (mesothelioma) IRIS Asbestos Assessment, 1988 US Asbestos Company Employees Cohort • Cohort consisted of 1,075 men obtained from company records. • Subjects were retired between 1941 and 1967 and receiving a pension from company. • Cohort followed through 1973. • Total dust measured in mppcf. Mesothelioma, lung cancer, digestive cancer Medium New Orleans Asbestos Cement Building Material Plants Cohort • Includes two asbestos cement building material plant producing products containing chrysotile, crocidolite, and amosite asbestos. • Cohort consisted of 5,645 men who had worked in either plant and had at least 20 years of follow up. • Detail work history obtained from plant records. Lung cancer, mesothelioma, digestive cancer High Ontario, Canada Asbestos Cement Factory Cohort • Cohort included 241 production and maintenance employees who worked for at least 9 years at the factory prior to 1960. • Impingers were used to prior to 1973 and membranes fiber counts used thereafter. • Mortality was followed through October 1980. Lung cancer, mesothelioma, gastrointestinal cancer Medium NY-NJ Asbestos Insulation Workers Cohort • Cohort located in Paterson, NJ, and manufactured amosite products. • Cohort included 820 men that worked for at least 5 years in factory. • Cohort followed through 1982. • No fiber counts available, but used counts for similar plant in Tyler, TX. Lung cancer Medium Page 23 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Cohort Name Cohort Description Cancer Outcomes* Overall Quality Determination (OQD) Rating Asbestos Textile Workers Cohort • Cohort consisted of white males who worked at the plant for at least 1 month prior to January 1, 1959. • Work histories obtained from this U.S. textile cohort included all 1,261 white males who worked at the plant for at least a month between January 1, 1940, and December 31, 1965. All workers who had a social security administration (SSA) record and had worked for at least 1 month prior to January 1, 1959, were considered to be part of the cohort. The cumulative dust exposures were assigned to each study participant using the same data that (Dement et al.. 2008) used to calculate historical exposures. Lung cancer, mesothelioma Medium International Association of Heat and Frost Insulators and Asbestos Workers Cohort • Plant located in the NY-NJ metro area and produced chrysotile and amosite products between 1943 and 1976. • Cohort included 623 men employed prior to 1943 and 833 men employed after 1943. • Follow-up in 1962 and 1976. • Asbestos concentration in facilities not measured but used counts from other U.S. insulation facilities that operated between 1968 and 1971. Mesothelioma Medium Cohort not included in existing EPA assessments Wittenoom, Australia, Residents Cohort • Residential cohort included 4,659 individuals residing for at least 1 month in Wittenoom between 1943 and 1992. Mine workers excluded. • Follow-up in 1993, 2000, and 2004. • Ambient exposures from nearby crocidolite assigned based on dates of residence, assigned exposure intensity, and period personal monitoring after operations ceased. Lung cancer, ovarian cancer, mesothelioma, brain cancer, leukemia Medium *As indicated in Section 1.3 and the Final Scope document. Part 2 of the Risk Evaluation will focus on mesothelioma and lung, ovarian and laryngeal cancers. 624 Page 24 of 102 ------- 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 5.2 1988 IRIS Asbestos Assessment The IRIS Asbestos Assessment, released in 1988 (U.S. EPA. 19881 utilizes the Airborne Asbestos Health Assessment Update from 1986 (U.S. EPA. 1986). The latter was developed as the scientific foundation to support EPA's review and revision of the designation of asbestos as a hazardous air pollutant under the 1973 National Emission Standards for Hazardous Air Pollutants (NESHAP) under the 1977 Clean Air Act Amendments (U.S. EPA. 1986). The original designation of asbestos was based upon a qualitative review of the evidence prior to 1972 establishing associations between exposure and carcinogenicity. The objectives of the Airborne Asbestos Health Assessment Update (U.S. EPA. 1986) were to identify any new asbestos-related health effects from studies published after 1972, examine the dose-response relationship, and establish unit risk values for asbestos, if warranted. At the time of assessment, the prevailing thought was that creating an exposure-response relationship for asbestos could be done in one of two ways. The first would be to choose the study or studies that have the best exposure data, presuming a sufficient measure of effect. The second approach would use all studies that provide exposure-response information along with estimates of the uncertainty of the data. In this approach, an overall exposure-response relationship is produced by taking an appropriate weighted average of the relationships discovered across studies accounting for observable variations in exposure conditions. The benefits of taking into account all research for which exposure-response data can be generated are as follows: 1. any bias in the selection of the research to be analyzed is largely eliminated; 2. information on the degree of uncertainty in the estimate of the average Kl value can be acquired; and 3. more accurate estimations of the impact of different fiber types or manufacturing processes can be made. Based on this information, the assessment utilized data from all studies that provided exposure response data, rather than basing the assessment on a single study with the strongest exposure assessment (as was done in the later EPA assessments on Libby and chrysotile). The assessment included occupational studies with exposures to any of the principal commercial varieties of asbestos fibers (i.e., amosite, anthophyllite, crocidolite, and chrysotile). A total of 14 occupational studies for lung cancer and 4 occupational studies for mesothelioma provided data for a dose-response assessment. The data for a best estimate of increased risk of lung cancer per unit exposure are provided by 14 studies across a range of occupational activities. The mixed fiber cohorts are explicitly described in Appendix D.3; however, the cohorts in the 1988 Asbestos Assessment that were chrysotile-specific were not explicitly described because they had been extended and encompassed by studies included in Part 1 of the Risk Evaluation for Asbestos (see also Appendix D.4). In the 1988 Asbestos Assessment, studies of mining and milling were excluded due to a substantial difference in risk observed and the notion that exposure assessment in these operations is significantly more challenging due to a wide array of fibers being present. Factories have a more limited set of sources of dust and fibers, making fiber counts more straightforward. In deriving the overall Kl (slope factor for lung cancer), the geometric mean was calculated from the 14 epidemiologic studies, representing exposures to chrysotile, amosite, and crocidolite. Of the four studies examining mesothelioma mortality in occupational cohorts (see Table II.C.2 in the IRIS Asbestos Summary (U.S. EPA. 1988)). three of these cohorts had mixed-fiber exposures and also examined lung cancer mortality. However, mesothelioma risk was calculated for the 10 studies examining lung cancer and not mortality by developing an adjustment factor (the ratio of Km [slope factor for mesothelioma] to Kl in the 4 studies examining both mortality outcomes) and applying that ------- 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 adjustment factor to the Kl for each study (see Table 3-31 in the Airborne Asbestos Health Assessment Update (U.S. EPA. 1986). The resulting relative mesothelioma hazard was closely examined across cohorts and occupational categories (e.g., mining/milling, insulation workers, textiles, etc.) and because there were no obvious outliers, a geometric mean was calculated considering all studies. The assessment discusses the postulation that crocidolite was thought to have higher potency with regard to mesothelioma, but quantitative investigation of this concern demonstrated that the overall impact of this uncertainty was minimal, and an overall adjustment was not made for cohorts with potential crocidolite exposures. Because under-ascertainment of mesothelioma was also a concern, a quantitative adjustment was made to account for this uncertainty. The cancer slope factors for lung cancer and mesothelioma were separately derived and then statistically combined. Subsequently, a life table analysis was conducted using the Kl and Km to represent the epidemiologic data, a relative risk model for lung cancer, and an absolute risk model for mesothelioma with linear low dose extrapolation to arrive at an IUR of 0.23 per fiber/cc. It is important to note that in the original studies identified in this assessment, exposure data was commonly collected as a measure of dust, and some studies additionally presented fiber counts using filter or membrane-based techniques, allowing for the development of a conversion factor. This conversion factor is necessary in order to conduct quantitative assessment of asbestos exposure in studies where measurements were initially taken for dust. These are further described in Appendix D.4, where applicable. Additionally, the assessment found that the risk from lung cancer increased with time since first exposure and death from mesothelioma increased rapidly after onset of exposure—an important observation. Limitations of the analysis that were described include (1) variability in the exposure-response relationship at high exposure; (2) uncertainty in extrapolating to much lower exposures (i.e., background exposures that can be l/100th the levels seen in occupational settings); and (3) uncertainties in converting between detection methods (e.g., optical fiber counts, mass determination). The asbestos IUR is widely recognized and is used in other EPA programs, including Superfund risk assessments conducted under the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) (U.S. EPA. 2021b). 5.3 IRIS Libby Amphibole Assessment Cancer Dose-Response The IRIS LAA Assessment, released in 2014, included a detailed toxicological review that provides the scientific foundation to support the risk and dose-response assessment of chronic inhalation exposure specific to LAA in the Rainy Creek complex and from the vermiculite mine near Libby, Montana (U.S. EPA. 2014b). The LAA Assessment evaluated the possible risks associated with exposure to LAA, including those related to cancer and non-cancer health effects, and presents risk values for use in risk assessments, including an RfC for non-cancer health effects (summarized in Section 4.2 above) and an IUR to address cancer risk. The LAA Assessment considered several occupational and community- based cohorts for dose-response assessment (see Figure 4-1 in the LAA Assessment); however, OPPT identified two of those occupational cohorts as being most relevant for dose-response consideration (Appendix C.2). For derivation of the IUR, the Libby, Montana, workers cohort (including miners and millers) was ultimately selected as the cohort with the most robust data for dose-response assessment (i.e., individual- level exposure data based on impinger and PCM measurements, complete demographic data, and vital status with extended follow-up through 2006). For mesothelioma mortality in this dataset, Poisson modeling was conducted to fit mortality data and exposure data with a range of exposure metrics. The best model was based upon a subcohort with employment beginning in 1959 and a cumulative exposure metric with a 5-year half-life and a 10-year Page 26 of 102 ------- 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 lag time. The central estimate for Km was 3.11 x 10~4 per fibers/cc. Following selection of the Km, a life table procedure was applied to the U.S. general population using age-specific mortality statistics to estimate the exposure levels that would be expected to result in a 1 percent increase in absolute risk of mesothelioma over a lifetime of continuous exposure. Linear low-dose extrapolation was used to find an effective concentration corresponding to the central tendency, which was estimated to be 0.032 per fiber/cc and 0.074 per fiber/cc when adjusted to account for under-ascertainment of mesothelioma. Lung cancer unit risk values were also calculated separately and based on a subcohort of the Libby, Montana, workers hired after 1959. Multivariate extended Cox models were run with a range of exposure metrics, and the best fit was based on cumulative exposure with a 10-year half-life and a 10- year lag. The resulting Kl from this model was 0.0126 per fiber/cc-yr. As was done for the mesothelioma cancer slope factor, a life-table analysis was applied to the KLto determine an exposure level of asbestos expected to result in a 1 percent increase in relative cancer risks when taking into account age-specific background risk. The corresponding effective concentration relating to the central tendency was 0.0399 per fiber/cc for a lifetime continuous exposure with an upper bound unit risk of 0.0679 per fiber/cc. The upper bound unit risks for mesothelioma and lung cancer were statistically combined to yield an appropriate upper bound value representing overall cancer risk for continuous lifetime asbestos exposure. Importantly, the statistical derivation of a combined upper bound unit risk value accounted for overprediction resulting from combining individual upper bound estimates. The upper bound combined risk from the best fitting models applied to individual-level data from the Libby, Montana, workers was 0.17 per fiber/cc. The 2014 IRIS LAA Assessment notes some limitations, including the difficulty in controlling for smoking as a confounder, the potential for under-ascertainment of mesothelioma, and uncertainties in the exposure measurements in the facility. The LAA IUR is widely recognized and is specifically used in Superfund risk assessments conducted under the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) (U.S. EPA. 2021b). 5.4 Part 1 Risk Evaluation for Asbestos: Dose-Response The most recent asbestos IUR was developed as part of the Risk Evaluation for Asbestos Part 1: Chrysotile Asbestos that was finalized in 2020 (U.S. EPA. 2020). As previously described, asbestos was identified as one of the first 10 substances to undergo risk evaluation under the amended TSCA. The consideration and evaluation of human health evidence primarily focused epidemiologic studies of lung cancer or mesothelioma resulting from inhalation exposures to chrysotile asbestos. Thus, OPPT made a distinction between (1) studies of exposure settings where only commercial chrysotile asbestos was used or where workers exposed only to commercial chrysotile asbestos could be identified, and (2) situations where chrysotile asbestos was used in combination with amphibole asbestos forms and the available information would not allow exposures to chrysotile and amphibole asbestos forms to be separated. The studies that were found to be useful for the study of mesothelioma and lung cancer were all based on historical occupational cohorts with use of the longest follow-up for each cohort or the most pertinent exposure-response when a cohort had been the subject of more than one publication. In Part 1, an IUR of 0.16 per fiber/cc was derived based upon thorough consideration and analysis of data from epidemiological studies on mesothelioma and lung cancer in cohorts of workers using chrysotile. As described in Appendix D.l and presented in Table 5-1, data from several cohorts was available for dose-response modeling following a systematic approach to literature identification and evaluation. Ultimately, data from cohorts of workers in textile plants in North and South Carolina were selected for IUR derivation. For the NC cohort, individual-level exposure-response data was available for lung cancer in Loomis et al. (2009) and Elliott et al. (2012) as well as mesothelioma in Loomis et al. Page 27 of 102 ------- 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 (2019). For these studies, the Part 1 Risk Evaluation presents cancer potency values based on Poisson regressions of the individual-level data using both logistical and additive relative rate model forms with adjustment for age, sex, race, calendar period, and birth cohort (see Table 3-4 in (U.S. EPA. 2020)). For the SC cohort, individual-level data was available for lung cancer in Hein et al. (2007) and Elliott et al. (2012) as well as for mesothelioma from Berman and Crump (2008). Lung cancer potency values for these studies were based on Poisson regression models using a linear relative rate model form with adjustment for sex, race, and age. Mesothelioma cancer potency values were reported in Berman and Crump (2008) based on analyses of the original cohort data using the Peto model (see Table 3-3 in U.S. EPA (2020)). Part 1 also describes uncertainty related to under-ascertainment of mesothelioma as an International Classification of Diseases (ICD) code specific to mesothelioma that was not available prior to 1999. Thus, some cases of mesothelioma are missed on death certificates prior to 1999 and likely even during the initial use of the ICD code. This uncertainty was also considered in the IRIS LAA Assessment (U.S. EPA. 2014b) and a multiplier was derived (1.39) based on data from the Libby cohort that was not fiber- specific, but rather specific to outcome ascertainment for mesothelioma. This multiplier was used to adjust IURs in Part 1 of the Risk Evaluation (see Section 3.2.3.8.1 in U.S. EPA (2020)). Part 1 also describes uncertainty related to under-ascertainment of mesothelioma as an International Classification of Diseases (ICD) code specific to mesothelioma that was not available prior to 1999. Thus, some cases of mesothelioma are missed on death certificates prior to 1999 and likely even during the initial use of the ICD code. This uncertainty was also considered in the IRIS LAA Assessment (U.S. EPA. 2014b) and a multiplier was derived (1.39) based on data from the Libby Cohort that was not fiber-specific, but rather specific to outcome ascertainment for mesothelioma. This multiplier was used to adjust IURs in Part 1 of the Risk Evaluation (see Section 3.2.3.8.1 in U.S. EPA (2020)). Additionally, the IUR was adjusted to account for cancer risk from other cancer endpoints beyond lung cancer and mesothelioma. As explained in Section 3.2.3.8.1 of Part 1, IARC concluded that exposure to asbestos is causally related to lung cancer and mesothelioma as well as laryngeal and ovarian cancer (U.S. EPA. 2020; Straif et al.. 2009). Data was not available to derive potency factors for laryngeal and ovarian cancer, so an adjustment factor was developed to account for potential underestimation of cancer risk when only considering data for lung cancer and mesothelioma. The combined adjustment factor applied to lung cancer to address other cancers was 1.06 (see Table 3-11 in U.S. EPA (2020)). For each modeling result from the NC and SC datasets, the unit risks were calculated separately for lung cancer and mesothelioma. Lung cancer unit risks were adjusted to account for other cancers and mesothelioma unit risks were adjusted to account for under-ascertainment. The unit risks were then statistically combined for central unit risk and upper bound risk. Overall, six IUR values were available for the datasets and modeling results, and the median IUR was ultimately selected because there was low model uncertainty (see Table 3-12 in U.S. EPA (2020)). The median lifetime cancer incidence IUR was 0.16 per fiber/cc based upon a linear model of the data from the NC textile workers cohort (Elliott et al.. 2012). Part 1 notes a few important uncertainties in the IUR (see Section 4.3.5 in U.S. EPA (2020)). First, PCM measurements were used despite TEM being a more precise analytical technique. However, it was determined that when TEM and PCM were available in the same dataset, TEM and PCM model results were similar. Thus, this uncertainty was considered to be low for the NC textile worker cohort. Another source of uncertainty in exposure measurements is the use of impinger sampling data for early asbestos exposures. The most robust approach to account for this is to use paired and concurrent sampling data to derive a conversation factor, and this was performed in the analysis of the NC and SC textile cohorts Page 28 of 102 ------- 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 resulting in low uncertainty. When considering uncertainties related to outcome data, use of mortality data rather than incidence, which was not available, was of concern. To account for this, background rates of lung cancer incidence were used in lifetable analyses. However, this was not possible for mesothelioma. While this remains a bias, it is noteworthy that median survival for mesothelioma is less than 1 year. Finally, confounding must be considered with regard to uncertainties. Smoking is considered a strong confounder for lung cancer related to asbestos exposure, but in the NC and SC cohorts, confounding was deemed to be low because regression models accounted for birth cohort that would reflect changes in smoking rates over time. Additionally, it is likely that smoking rates among workers were similar across facilities and occupations. Smoking is not a confounder for mesothelioma. In Part 1 of the Risk Evaluation, this IUR was applied for all chrysotile asbestos exposure scenarios, with less-than-lifetime adjustments applied where appropriate for less-than-lifetime exposures. Risk determinations were based, in part, on quantitative risk characterization computer with this IUR. Risk management rulemaking that is currently underway will address the unreasonable risk identified in Part 1 of the Risk Evaluation for Asbestos (U.S. EPA. 2020). 5.5 Part 2 Risk Evaluation for Asbestos: Quantitative Cancer Approach Across decades of epidemiologic research in various occupational settings, employing diverse exposure measurement methods and approaches to exposure assignment, and based upon a wide range of dose- response modeling with application of adjustment factors, all three IURs are numerically very similar (Table). Inherent strengths and uncertainties pertain to each IUR, and all were developed for a distinct purpose and application. The IUR of 0.16 per fiber/cc presented in Part 1 of the Risk Evaluation for Asbestos (U.S. EPA. 2020) benefits from the most recent data available and generally, the longest follow-up periods. Advanced exposure measurement methods are reflected in the underlying data resulting in exposure estimates that are of high confidence. Furthermore, longer follow-up times increase the statistical power of the study as more mortality is observed. Other notable strengths include accounting for laryngeal and ovarian cancers, which are causally associated with asbestos exposure, and accounting for under-ascertainment of mesothelioma. However, this IUR was strictly limited to exposures to chrysotile asbestos and is therefore most appropriately applied in cases where exposures are chrysotile- specific. The IUR of 0.17 per fiber/cc presented in the IRIS LAA Assessment (U.S. EPA. 2014b) has similar strengths and limitations as the chrysotile IUR. EPA ORD was able to conduct robust analyses based on very detailed individual-level exposure measurements and outcome data for lung cancer and mesothelioma as the cohort was established from one operation, the mine in Libby, Montana. There were not sufficient data on laryngeal or ovarian cancers in this cohort for quantitative consideration5, but under-ascertainment of mesothelioma was accounted for. As described in Section 5.2, herein, the comprehensiveness of the data yielded quantitative analyses of high confidence. However, this IUR is based on data specific to scenarios of exposure to only LAA, and therefore, is most appropriately applied in risk estimates based on Libby-specific exposures. 5 The quantitative adjustment for lung cancer to address laryngeal and ovarian cancers developed in Part 1 of the Risk Evaluation for Asbestos would not have impacted the LAA IUR and proposed IUR for application in Part 2 because it was small and is only appropriate for lung cancer, which accounts for the minority of risk relative to mesothelioma in the Libby IUR. Page 29 of 102 ------- 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 The earliest IUR of 0.23 per fiber/cc presented in the IRIS Asbestos Assessment (U.S. EPA. 1988) was developed to describe risks related to all asbestos fiber types. Development of this IUR was based on historically robust data at a time when standard fiber measurement methods had not yet been established and reporting and publication standards were highly variable. Although additional uncertainty exists in the exposure measurement provided in these published studies, it is important to note that EPA technical experts were diligent in advancing their understanding and use of data beyond what was available in original publications to reduce uncertainties, as reflected in the 1988 Asbestos Assessment and related publications. A major strength of this IUR is that it represents exposures to a range of fiber types and is most appropriately applied to describe risks related to mixed-fiber exposures, which is pertinent to exposure scenarios in Part 2 of the Risk Evaluation for Asbestos. The authors of the report acknowledged this objective when they described the use of data from all cohorts and not isolating data from the cohort with the most detailed exposure assessment that may have been specific to only a single fiber. Table 5-2. Comparison of EPA Inhalation Unit Risk Values for Asbestos IUR per fiber/cc EPA Assessment Fiber Type Cancer Outcomes 0.23 IRIS Asbestos Assessment (U.S. EPA. 1988) Mixed fiber (chrysotile, amosite, crocidolite) Lung cancer and mesothelioma 0.17 IRIS LAA Assessment (U.S. EPA. 2014b) Libby Amphibole Asbestos fiber Lung cancer and mesothelioma 0.16 Risk Evaluation for Asbestos Part 1: Chrysotile Asbestos (U.S. EPA. 2020) Chrysotile fiber Lung cancer and mesothelioma, with quantitative adjustment to account for laryngeal and ovarian cancers When considering the strengths and uncertainties of each IUR, OPPT is proposing to use an IUR of 0.2 per fiber/cc in Part 2 of the Risk Evaluation for Asbestos based on the existing IURs. When considering standard practice of reporting IURs with precision to one significant digit, each of the existing IURs would round to 0.2 per fiber/cc. This approach is well-supported in taking into account a broad range of information that is applicable to Part 2. This value reflects exposures in a variety of settings and levels, an array of asbestos fibers, and relevant cancer outcomes. Furthermore, the exposures that will be analyzed based on the conditions of use in Part 2 (U.S. EPA. 2022) will predominantly be for legacy uses of asbestos, or those uses for which there is no current manufacture, process, or distribution. These exposure scenarios will not pertain to specific fiber types (e.g., chrysotile and LAA). Specifically, for asbestos-containing building materials, exposure to mixed fiber types is described. In applying an IUR of 0.2 per fiber/cc in the Part 2 of the Risk Evaluation for Asbestos, it is recognized that this value applies to risks associated with a continuous lifetime exposure, which will not be expected for all exposure scenarios in Part 2. Thus, as was done in Part 1 of the Risk Evaluation, partial or less-than-lifetime (LTL) values corresponding to the IUR will be applied. The general equation for estimating cancer risks for LTL exposure from inhalation of asbestos, from the OLEM Framework for Investigating Asbestos-contaminated Superfund Sites (U.S. EPA. 2008). is: ELCR = EPC x TWF x IURLtl where: ELCR = Excess lifetime cancer risk, the risk of developing cancer as a consequence of the site- related exposure Page 30 of 102 ------- 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 EPC = Exposure point concentration, the concentration of asbestos fibers in air (fiber/cc) for the specific activity being assessed IURltl = Less-than4ifetime inhalation unit risk per fiber/cc For example: the notation for the LTL IUR could start at age 16 with 40 years duration IUR(i6.40). TWF = Time weighting factor, this factor accounts for less-than-continuous exposure during a one-year exposure, and is given by: TWF = [Exposure time (hours per day) / 24 hours] x [Exposure frequency (days per year) / 365 days] For more information on the general approach for estimating cancer risk for less-than-lifetime exposure from inhalation of asbestos, see Section 4.4.1 in Part 1 of the Risk Evaluation (U.S. EPA. 2020). Assessing asbestos-related health effects is unique because of the timing of exposure related to outcomes as TSFE plays an important role in risk modeling. Exposures occuring decades prior to the observed outcome are most relevant—particularly for understanding risk. Following the approach described in the Part 1 of the Risk Evaluation (see Appendix K), which was reviewed by the SACC, LTL values will be determined based on age of first exposure and duration of exposure. These will be presented in the risk characterization of the draft Part 2 of the Risk Evaluation for Asbestos. Page 31 of 102 ------- 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 6 SUMMARY AND NEXT STEPS As described in preceding sections of this white paper, prior to OPPT's efforts to develop Part 2 of the Risk Evaluation, the Agency has developed three IURs describing the relationship between cancer and asbestos exposure and an RfC for non-cancer effects related to asbestos exposure. To ensure that the consideration of human health effects in Part 2 is based upon the best available science, OPPT employed a systematic approach to identify and evaluate the epidemiologic evidence available for dose-response assessment and to consider if an updated IUR is warranted. OPPT determined that the most appropriate epidemiologic cohorts available for dose-response assessment were previously considered in deriving the existing IURs and RfC. Thus, OPPT is proposing that an updated dose-response assessment for cancer and non-cancer effects related to asbestos exposures is not needed at this time and that the existing, peer-reviewed EPA values are appropriate for application in Part 2 of the Risk Evaluation for Asbestos. As described in Section 4.3, for non-cancer effects, application of the LAA POD of 2.6x 10~2 fiber/cc is proposed for application in Part 2 with three associated UFs (UFh= 10, UFd = 3, UFs = 10). Because there are three relevant IURs for cancer effects that are all numerically similar, EPA is proposing use of an IUR of 0.2 per fiber/cc in Part 2 as this value at one significant figure reflects an appropriate level of precision when considering the range of IURs (Section 5.5). OPPT is soliciting input through a letter peer-review. Following peer review of this proposed approach, OPPT will release a draft Part 2 Risk Evaluation for Asbestos that will be made available for public comment. Peer reviewer input and public comment will be taken into consideration and appropriate revisions will be made to finalize the Part 2 Risk Evaluation for Asbestos on or before December 1, 2024, consistent with the consent decree timeline in ADAO, et al. v. Regan, No. 4:21-cv-03716 (N.D. Cal. Oct. 2021). Ultimately, in the finalized Part 2 risk evaluation, OPPT will determine, based on assessments of risk for the conditions of use examined, whether or not unreasonable risks are posed to human health or the environment. As required by TSCA, any unreasonable risk must be addressed via subsequent risk management rulemaking. Page 32 of 102 ------- 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 REFERENCES ATSDR. (2001). Toxicological profile for asbestos (Update, September 2001) [ATSDR Tox Profile], Atlanta, GA: U.S. Department of Health and Human Services, Public Health Service. http://www.atsdr.cdc.gov/ToxProfiles/tp61.pdf Berman. DW. (2010). Comparing milled fiber, Quebec ore, and textile factory dust: has another piece of the asbestos puzzle fallen into place [Review], Crit Rev Toxicol 40: 151-188. http://dx.doi.org/10.3109/104084409Q3349137 Bennan. DW: Crump. KS. (2008). Update of potency factors for asbestos-related lung cancer and mesothelioma. Crit Rev Toxicol 38: 1-47. http://dx.doi.org/10.1080/104084408Q2276167 Blettner. M; Heuer. C: Razum. O. (2001). Critical reading of epidemiological papers. A guide. Eur J Public Health 11: 97-101. Borton. EK; Lemasters. GK; Hilbert TJ; Lockev. JE; Dunning. KK; Rice. CH. (2012). Exposure estimates for workers in a facility expanding Libby vermiculite: updated values and comparison with original 1980 values. J Occup Environ Med 54: 1350-1358. http://dx.doi. org/10.1097/JQM. ObO 13 e31824fe 174 Cooper. GS: Lunn. RM; Agerstrand. M; Glenn. BS: Kraft. AD: Luke. AM: Ratcliffe. JM. (2016). Study sensitivity: Evaluating the ability to detect effects in systematic reviews of chemical exposures. Environ Int 92-93: 605-610. http://dx.doi.Org/10.1016/i.envint.2016.03.017 Dement. JM: Kuempel. ED: Zumwalde. RD; Smith. RJ; Stavner. LT; Loomis. D. (2008). Development of a fibre size-specific job-exposure matrix for airborne asbestos fibres. Occup Environ Med 65: 605-612. http://dx.doi.org/10.1136/oem.2007.033712 Dunning. KK: Adiei. S: Levin. L; Rohs. AM: Hilbert. T; Borton. E; Kapil. V: Rice. C: Lemasters. GK: Lockev. JE. (2012). 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G; Tan. Y; Teeguarden. J; Tornero-Velez. R; Weisel. CP. (2014). A proposal for assessing study quality: Biomonitoring, Environmental Epidemiology, and Short-lived Chemicals (BEES-C) instrument. Environ Int 73: 195-207. http://dx.doi.Org/10.1016/i.envint.2014.07.011 Leidel. NA; Bayer. SG; Zumwalde. RD; Busch. KA. (1979). USPHS/NIOSH membrane filter method for evaluating airborne asbestos fibers. Leidel, NA; Bayer, SG; Zumwalde, RD; Busch, KA. Lockev. JE; Brooks. SM; Jarabek. AM; Khoury. PR; McKay. RT; Carson. A; Morrison. JA; Wiot. JF; Spitz. HB. (1984). Pulmonary changes after exposure to vermiculite contaminated with fibrous tremolite. Am Rev Respir Dis 129: 952-958. http://dx.doi.Org/10.l 164/arrd. 1984.129.6.952 Loomis. D; Dement. JM; Wolf. SH; Richardson. DB. (2009). Lung cancer mortality and fibre exposures among North Carolina asbestos textile workers. Occup Environ Med 66: 535-542. http://dx.doi.Org/10.l 136/oem.2008.044362 Loomis. D; Richardson. DB; Elliott. L. (2019). Quantitative relationships of exposure to chrysotile asbestos and mesothelioma mortality. Am J Ind Med 62: 471-477. http://dx.doi.org/10.10Q2/aiim.22985 Metintas. M; Metintas. S; Hillerdal. G; Ucgun. I; Erginel. S; Alatas. F; Yildirim. H. (2005). Nonmalignant pleural lesions due to environmental exposure to asbestos: a field-based, cross- sectional study. Eur Respir J 26: 875-880. http://dx.doi.Org/10.l 183/09031936.05.00136404 NTP. (2015). Handbook for conducting a literature-based health assessment using OHAT approach for systematic review and evidence integration. Research Triangle Park, NC: U.S. Deptartment of Health and Human Services, National Toxicology Program, Office of Health Assessment and Translation, https://ntp.niehs.nih.gov/ntp/ohat/pubs/handbookian2015 508.pdf Peto. J; Seidman. H; Selikoff. IJ. (1982). Mesothelioma mortality in asbestos workers: implications for models of carcinogenesis and risk assessment. Br J Cancer 45: 124-135. http://dx.doi.org/10.1038/bic.1982.15 Piolatto. G; Negri. E; La Vecchia. C; Pira. E; Decarli. A; Peto. J. (1990). An update of cancer mortality among chrysotile asbestos miners in Balangero, northern Italy. Br J Ind Med 47: 810-814. http://dx.doi.Org/10.l 136/oem.47.12.810 Page 34 of 102 ------- 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054 1055 1056 1057 1058 1059 1060 1061 1062 1063 1064 1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 1076 1077 1078 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Pira. E; Pelucchi. C; Piolatto. PG; Negri. E; Bilei. T; La Vecchia. C. (2009). Mortality from cancer and other causes in the Balangero cohort of chrysotile asbestos miners. Occup Environ Med 66: 805- 809. http://dx.doi.Org/10.l 136/oem.2008.044693 Pira. E; Romano. C: Donat F; Pelucchi. C: La Vecchia. C: Boffetta. P. (2017). Mortality from cancer and other causes among Italian chrysotile asbestos miners. Occup Environ Med 74: 558-563. http://dx.doi.Org/10.l 136/oemed-2016-103673 Reid. A: Berry. G: de Klerk. N: Hansen. J: Hevworth. J: Ambrosini. G: Fritschi. L; Olsen. N: Merler. E; Musk. A. (2007). Age and sex differences in malignant mesothelioma after residential exposure to blue asbestos (crocidolite). Chest 131: 376-382. http://dx.doi.org/10.1378/chest.06-1690 Reid. A: Franklin. P; Olsen. N: Sleith. J: Samuel. L; Aboagye-Sarfo. P; de Klerk. N: Musk. AW. (2013). All-cause mortality and cancer incidence among adults exposed to blue asbestos during childhood. Am J Ind Med 56: 133-145. http://dx.doi.org/10.1002/aiim.22103 Reid. A: Hevworth. J: de Klerk. N: Musk. A. (2008). The mortality of women exposed environmentally and domestically to blue asbestos at Wittenoom, Western Australia. Occup Environ Med 65: 743-749. http://dx.doi.org/10.1136/oem.2007.035782 Rohs. A: Lockev. J: Dunning. K; Shukla. R; Fan. H; Hilbert. T; Borton. E; Wiot. J: Meyer. C: Shipley. R; Lemasters. G: Kapil. V. (2008). Low-level fiber-induced radiographic changes caused by Libby vermiculite: a 25-year follow-up study. Am J Respir Crit Care Med 177: 630-637. http://dx.doi.Org/10.l 164/rccm.200706-84 IOC Rubino. GF; Piolatto. G: Newhouse. ML: Scansetti. G: Aresini. GA; Murray. R. (1979). Mortality of chrysotile asbestos workers at the Balangero Mine, northern Italy. Occup Environ Med 36: 187- 194. http://dx.doi.Org/10.l 136/oem.36.3.187 SAB. (2008). SAB consultation on EPA's proposed approach for estimation of bin-specific cancer potency factors for inhalation exposure to asbestos. (EPA-SAB-09-004). U.S. Environmental Protection Agency. http://nepis.epa.gov/exe/ZyPURL.cgi?Dockev=P 1002EAG.txt Seidman. H. (1984). Short-term asbestos work exposure and long-term observation. Seidman, H. Seidman. H; Selikoff. IJ; Hammond. EC. (1979). Short-term asbestos work exposure and long-term observation. Ann NY Acad Sci 330: 61-89. Selikoff. IJ: Hammond. EC: Seidman. H. (1979). Mortality experience of insulation workers in the United States and Canada, 1943-1976. In IJ Selikoff; EC Hammond (Eds.), Annals of the New York Academy of Sciences, vol 330 (pp. 91-116). New York, NY: New York Academy of Sciences. http://dx.doi.Org/10.l 111/i. 1749-6632.1979.tb 18711.x Stavner. L; Kuempel. E; Gilbert. S: Hein. M; Dement. J. (2008). An epidemiological study of the role of chrysotile asbestos fibre dimensions in determining respiratory disease risk in exposed workers. Occup Environ Med 65: 613-619. http://dx.doi.Org/10.l 136/oem.2007.035584 Straif. K; Benbrahim-Tallaa. L; Baan. R; Grosse. Y; Secretan. B; El Ghissassi. F; Bouvard. V: Guha. N: Freeman. C: Galichet. L; Cogliano. V. (2009). A review of human carcinogens: Part C: Metals, arsenic, dusts, and fibres. Lancet Oncol 10: 453-454. http://dx.doi.org/10.1016/S147Q- 2045(09)70134-2 U.S. EPA. (1985). Measuring airborne asbestos following an abatement action [EPA Report], (EPA 600/4-85-049). Washington, DC. https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockev=9100PM9J.PDF U.S. EPA. (1986). Airborne asbestos health assessment update. (EPA/600/8-84/003F). Washington DC: U.S. Environmental Protection Agency, Environmental Criteria and Assessment. U.S. EPA. (1988). IRIS summary for asbestos (CASRN 1332-21-4). Washington, DC: U.S. Environmental Protection Agency, Integrated Risk Information System. http ://www. epa. gov/iri s/ sub st/03 71 .htm U.S. EPA. (2008). Framework for investigating asbestos-contaminated superfund sites (pp. 71). (OSWER Directive #9200.0-68). Washington, DC: U.S. Environmental Protection Agency, Office of Solid Waste and Emergency Response. Page 35 of 102 ------- 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 1092 1093 1094 1095 1096 1097 1098 1099 1100 1101 1102 1103 1104 1105 1106 1107 1108 1109 1110 1111 1112 1113 1114 1115 1116 1117 1118 1119 1120 1121 1122 1123 1124 1125 1126 1127 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 http://www.epa.gov/superfund/health/contaminants/asbestos/pdfs/framework asbestos guidance .pdf U.S. EPA. (2014a). Integrated Risk Information System (IRIS) chemical assessment summary: Libby amphibole asbestos; CASRN not applicable, https://www.epa.gov/iris/supporting-documents- libbv-amphibole-asbestos U.S. EPA. (2014b). Toxicological review of libby amphibole asbestos: In support of summary information on the Integrated Risk Information System (IRIS) [EPA Report], (EPA/635/R- 11/002F). Washington, DC: Integrated Risk Information System, National Center for Environmental Assessment, Office of Research and Development. https://cfpub.epa.gov/ncea/iris/iris documents/documents/toxreviews/1026tr.pdf U.S. EPA. (2017a). Procedures for chemical risk evaluation under the amended Toxic Substances Control Act. Fed Reg 82: 33726-33753. U.S. EPA. (2017b). Scope of the risk evaluation for asbestos [EPA Report], (EPA-740-R1-7008). Washington, DC: Office of Chemical Safety and Pollution Prevention. https://www.epa.gov/sites/production/files/2017-06/documents/asbestos scope 06-22-17.pdf U.S. EPA. (2020). Risk evaluation for asbestos, Part I: Chrysotile asbestos [EPA Report], (EPA-740-R1- 8012). Washington, DC: Office of Chemical Safety and Pollution Prevention. https ://www.regulations. gov/document/EP A-HQ-QPPT-2019-0501 -0117 U.S. EPA. (2021a). Draft systematic review protocol supporting TSCA risk evaluations for chemical substances, Version 1.0: A generic TSCA systematic review protocol with chemical-specific methodologies. (EPA Document #EPA-D-20-031). Washington, DC: Office of Chemical Safety and Pollution Prevention, https://www.regulations. gov/document/EPA-HQ-QPPT-2021 -0414- 0005 U.S. EPA. (2021b). Framework for investigating asbestos-contaminated Comprehensive Environmental Response, Compensation, and Liability Act act sites. (OLEM Directive No. 9200.0-90). Asbestos Committee of the Technical Review Workgroup, Office of Land and Emergency Management. https://semspub.epa.gov/work/HQ/100002942.pdf U.S. EPA. (2022). Final scope of the risk evaluation for asbestos. Part 2: Supplemental evaluation including legacy uses and associated disposals of asbestos [EPA Report], (EPA Document# EPA-740-R-21-002). n.p.: U.S. Environmental Protection Agency, Office of Chemical Pollution and Safety Prevention, https://www.epa.gov/svstem/files/documents/2022- 06/Asbestos%20Part%202 FinalScope.pdf U.S. EPA. (2023). Quantitative approach to the human health assessment for the Risk Evaluation for Asbestos Part 2: Supplemental evaluation including legacy uses and associated disposals of asbestos — Systematic review of data quality evaluation information for human health hazard epidemiology. Washington, DC: Office of Pollution Prevention and Toxics (OPPT). Von Elm. E; Altman. DG: Egger. M; Pocock. SJ: G0tzsche. PC: Vandenbroucke. JP. (2008). The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol 61: 344-349. http://dx.doi.Org/10.1016/i.iclinepi.2007.l 1.008 W. R. Grace & Co. (1988). Health of vermiculite miners exposed to trace amounts of fibrous tremolite with cover letter dated 022988 [TSCA Submission], (OTS0514047. 86880000158. TSC ATS/305260). Wang. X: Lin. S: Yano. E; Yu. IT: Courtice. M; Lan. Y; Christians DC. (2014). Exposure-specific lung cancer risks in Chinese chrysotile textile workers and mining workers. Lung Cancer 85: 119-124. http://dx.doi.Org/10.1016/i.lungcan.2014.04.011 Wang. X: Yano. E; Lin. S: Yu. IT: Lan. Y; Tse. LA: Qiu. H; Christiani. DC. (2013). Cancer mortality in Chinese chrysotile asbestos miners: Exposure-response relationships. PLoS ONE 8: e71899. http://dx.doi.org/10.1371/iournal.pone.0071899 Page 36 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 1128 Weill H; Hughes. J; Waggenspack. C. (1979). Influence of dose and fiber type on respiratory 1129 malignancy risk in asbestos cement manufacturing. Am Rev Respir Dis 120: 345-354. 1130 http://dx.doi.Org/10.1164/arrd.1979.120.2.345 1131 Page 37 of 102 ------- 1132 1133 1134 1135 1136 1137 1138 1139 1140 1141 1142 1143 1144 1145 1146 1147 1148 1149 1150 1151 1152 1153 1154 1155 1156 1157 1158 1159 1160 1161 1162 1163 1164 1165 1166 1167 1168 1169 1170 1171 1172 1173 1174 1175 1176 1177 1178 1179 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 APPENDICES Appendix A ABBREVIATIONS AND ACRONYMS ADME ATSDR BMR CAA CERCLA COPD Cr6+ CT DLCO DPT ELCR EPA EPC f/cc f/mL FEV FT FVC GC-ECD GC-FID GC-HRMS GC-MS GC-MS/MS HRCT IARC ICD ILO IRIS IUR JEM KL KM LAA LC-MS/MS LPT LTL Me so [j,m mppcf MT NC NASEM NESHAP NIOSH NJ Absorption, distribution, metabolism, and excretion Agency for Toxic Substances and Disease Registry Benchmark response Clean Air Act Comprehensive Environmental Response, Compensation, and Liability Act Chronic obstructive pulmonary disease Hexavalent chromium Computerized tomography Diffusing capacity of the lungs for carbon monoxide Diffuse pleural thickening Excess lifetime cancer risk Environmental Protection Agency Exposure point concentration Fibers per cubic centimeter Fibers per milliliter Forced expiratory volume Full text Forced vital capacity Gas chromatography with electron capture detector Gas chromatography with flame-ionization detection spectrometry Gas chromatography/high-resolution mass spectrometry Gas chromatography mass spectrometry Gas chromatography with tandem mass spectrometry High resolution computed tomography International Agency for Research on Cancer International Classification of Diseases International Labour Organization Integrated Risk Information System Inhalation unit risk Job exposure metric Lung cancer potency factor Mesothelioma potency factor Libby Amphibole Asbestos Liquid chromatography with tandem mass spectrometry Localized pleural thickening Less-than-lifetime Mesothelioma Micrometers Million particles per cubic foot of air Montana North Carolina National Academies of Sciences, Engineering, and Medicine National Emission Standards for Hazardous Air Pollutants National Institute for Occupational Safety and Health New Jersey Page 38 of 102 ------- 1180 1181 1182 1183 1184 1185 1186 1187 1188 1189 1190 1191 1192 1193 1194 1195 1196 1197 1198 1199 1200 1201 1202 1203 1204 1205 1206 1207 1208 1209 1210 1211 1212 1213 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 NY New York OCSPP Office of Chemical Safety and Pollution Prevention OH Ohio OLEM Office of Land and Emergency Management OPPT Office of Pollution Prevention and Toxics OQD Overall quality determination ORD Office of Research and Development OSHA Occupational Safety and Health Administration PA Pennsylvania PBPK Physiologically based pharmacokinetic PCM Phase-contrast microscopy PCMe Phase-contrast microscopy equivalent PECO Population, exposure, comparator, and outcome POD Point of departure QC Quality control RfC Reference concentration SACC Science Advisory Committee on Chemicals SC South Carolina SIR Standardized incidence ratio SMR Standardized mortality ratio SSA Social Security Administration TSFE Time since first exposure TEM Transmission electron microscopy TIAB Title/abstract (screening) TLV Total Liquid Ventilation TSCA Toxic Substances Control Act TWA Time-weighted average TWF Time weighting factor TX Texas UF Uncertainty factor UFd Database uncertainty factor UFh Intraspecies uncertainty factor UFs Subchronic uncertainty factor U.S. United States Page 39 of 102 ------- 1214 1215 1216 1217 1218 1219 1220 1221 1222 1223 1224 1225 1226 1227 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Appendix B SYSTEMATIC REVIEW APPROACH The sections below describe the process used to identify, screen, and evaluate the reasonably available information. Many aspects of this process are described thoroughly in the 2021 Draft Systematic Review Protocol (U.S. EPA. 2021a). However, some aspects of the process were modified or extended in a fit- for-purpose manner. The modifications were performed to build off of systematic review efforts from Asbestos Part 1 and utilize data evaluation elements from the prior assessment while providing a similar structure for evaluating new and existing studies for other noncancer and cancer endpoints of concern not evaluated in Asbestos 1. In addition, based upon recommendations from NASEM and SACC on systematic review methodology, OPPT identified high quality studies based on previous assessments by the IRIS program and evaluated these critical studies in a systematic way leading to robust set of cohort studies for this dose response analysis. FigureApx B-l and FigureApx B-2 present schematics of the process. Further descriptions below in B.1.2 explain how the 338 peer-reviewed, 3 gray literature, and 2 data sources pursuant to TSCA (total 343 data sources) that met PECO screening criteria (Figure Apx B-l) were considered for dose-response screening (Figure Apx B-2). Page 40 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 0 Supplemental at TIAB Screening © aso Stud; Case Sen © No Original Data © Conference Abstract © Susceptible Population © © Human © © © Plant © Meets PECO Criteria at FT Screening © Human © © Human (um) Meets PECO Criteria at TIAB Screening © © Mechanistic © ADME/TK/PBPK © © Case Study or Case Series © No Original Data Conference Abstract ( xioxa \ Asbestos Part 2 Risk Evaluation: Environmental and Human Health Hazard ^19748^ Does Not Meet PECO Criteria at TIAB Screening © PDF Unavailable (1970J Mechanistic © ADME/TK/PBPK © Susceptible Population © Field Study © Non-English Record © 1228 1229 1230 1231 1232 1233 \\ " ® Field Study ® Non-English Record © Tate or Magnesium Silicate Figure Apx B-l. Literature Inventory Tree - Environmental and Human Health Hazard for Asbestos Part 2 View the interactive literature inventory tree in HAWC. Data in this figure represent all references obtained from the publicly available databases and gray literature references searches that were included in systematic review as of March 20, 2023. Additional data may be added to the interactive version as they become available. Page 41 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Literature Search T1AB Screening FT Screening Epidemiologic studies ^ with PFCO ^ with PFCO Include N = 343 references from 156 cohorts _C *c ai CD U 3 exposure groups 1 Cohorts WITHOUT appropriate exposure measurementor assignment, N = 127 references from 62 cohorts r CANCER Cohorts selected for final dose- response consideration • Libby, MT, Mining and Milling Cohort • NC Textile Cohort • SC Textile Workers ¦ Balangero, Italy, Mining Cohort • Chongqing, China, Asbestos Products Factory Cohort • Qinghai, China, Asbestos Mine Cohort ¦ Quebec, Canada,Asbestos Mines and Mills Cohort • Salonit Anhovo, Slovenia, Asbestos Factory Cohort ¦ Wittenoom, Australia, Residents Cohort T NON-CANCER Cohorts selected for final dose- response consideration for non-cancer • O.M. Scott Marysville, OH, Plant Cohort • Libby, MT, Mining and Milling Cohort • SC Textiles Cohort ¦ SCVermiculite Miners Cohort ¦ Anatolia, Turkey, Villagers Cohort • Wittenoom, Australia. Residents Cohort • Chinese Chrysotile Textile Factory Cohort 1 Cohorts not selected for final dose-responSe consideration, N = 32 • Exposure assessment is for dust • Exposure assessment is for lung tissue • Confirmation - exposure not assessed using PCM or TEM • Rated low or un in formative in SR • Confirmation - <3 exposure groups 1 References with mixed-fiber exposures from EPA IRIS Asbestos Assessment, 1988 N = 6 1234 1235 FigureApx B-2. Literature Flow Diagram Presenting the Identification, Screening, and 1236 Evaluation of Literature Page 42 of 102 ------- 1237 1238 1239 1240 1241 1242 1243 1244 1245 1246 1247 1248 1249 1250 1251 1252 1253 1254 1255 1256 1257 1258 1259 1260 1261 1262 1263 1264 1265 1266 1267 1268 1269 1270 1271 1272 1273 1274 1275 1276 1277 1278 1279 1280 1281 1282 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 B.l Data Search and Screening B.l.l Data Search As described in Section 4 of the 2021 Draft Systematic Review Protocol Supporting TSCA Risk Evaluations for Chemical Substances (U.S. EPA. 202 la). EPA conducts a comprehensive search for reasonably available information to support TSCA risk evaluations. Details on the methodology used to search for chemical-specific peer-reviewed and gray literature are available in Sections 4.2 and 4.3 of the 2021 Draft Systematic Review Protocol (U.S. EPA. 2021a). Of note, the search for and screening of hazard information considered for Part 2 of the Risk Evaluation for Asbestos includes all receptors (humans, animals, plants, and other organisms); however, this section focuses on specific details for the systematic review of epidemiologic (human) data to identify the most relevant information for informing both the cancer and non-cancer dose-response human health hazard assessments. Appendix Section C.1.24 of the 2021 Draft Systematic Review Protocol contains the specific strategy and search string used to identify reasonably available hazard information for asbestos in Part 2 (U.S. EPA. 2021a). Literature searches for asbestos hazard information were conducted in April 2021 (U.S. EPA. 2021a). As stated in the 2021 Draft Systematic Review Protocol, "[t]he literature strategy for Asbestos Part 2 is composed of three pieces: (1) reevaluation of all references used in Part 1 [of the Risk Evaluation for Asbestos]; (2) evaluation of new literature produced by performing a Part 1 search update; and (3) evaluation of new literature produced by inclusion of additional asbestos fiber types." (U.S. EPA. 2021a p. 240). Although references from Part 1 were included in the literature search for Part 2, these references were only reevaluated for outcomes that had not been previously evaluated in Part 1. All reasonably available information submitted to EPA under TSCA authorities was also considered for Part 2 of the Risk Evaluation. Appendix Section C.1.24 of the 2021 Draft Systematic Review Protocol contains the specific strategy and search string used to identify reasonably available hazard information for asbestos in Part 2 (U.S. EPA. 2021a). Literature searches for asbestos hazard information were conducted in April 2021 (U.S. EPA. 2021a). As stated in the 2021 Draft Systematic Review Protocol, "[t]he literature strategy for Asbestos Part 2 is composed of three pieces: (1) reevaluation of all references used in Part 1 [of the Risk Evaluation for Asbestos]; (2) evaluation of new literature produced by performing a Part 1 search update; and (3) evaluation of new literature produced by inclusion of additional asbestos fiber types." (U.S. EPA. 2021a p. 240). Although references from Part 1 were included in the literature search for Part 2, these references were only reevaluated for outcomes that had not been previously evaluated in Part 1. All reasonably available information submitted to EPA under TSCA authorities was also considered for Part 2. Following the data search, SWIFT-Review was used to identify peer-reviewed references predicted to be relevant for human health hazard (epidemiology) for asbestos. SWIFT-Review is a freely available text mining and machine learning software that can be used for topic modeling, categorization, and prioritization of search results (Howard et al.. 2016). Search strings were developed and validated in collaboration with ORD and Sciome. The generic search strings used in SWIFT-Review to automatically tag and categorize references can be found on the SWIFT-Review website. Peer-reviewed references proceeded to TIAB screening if the SWIFT-Review search string terms were present in the title, abstract, or keywords of a given reference. Additional details about the SWIFT-Review application itself are described in the 2021 Draft Systematic Review Protocol (U.S. EPA. 2021a) B.1.2 Data Screening Sections 4.2.5 and 4.3.2 of the 2021 Draft Systematic Review Protocol describe TIAB and full-text screening, respectively, were conducted to identify references that may contain relevant information for Page 43 of 102 ------- 1283 1284 1285 1286 1287 1288 1289 1290 1291 1292 1293 1294 1295 1296 1297 1298 1299 1300 1301 1302 1303 1304 1305 1306 1307 1308 1309 1310 1311 1312 1313 1314 1315 1316 1317 1318 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 use in risk evaluations under TSCA using discipline-specific screening criteria (U.S. EPA. 2021a). Screening of environmental and human health hazard data sources was conducted using the specialized web-based software programs: SWIFT-Active-Screener6-7 and DistillerSR.8 Specifically, for Part 2, TIAB screening was conducted using SWIFT-Active-Screener that utilizes a machine-learning algorithm to automatically compute which unscreened documents are most likely to be relevant based on the results of manual screening conducted by two independent screeners. Subsequent to TIAB screening, full-text screening was conducted manually by two independent reviewers for each reference using DistillerSR, and conflict resolution was conducted for any discrepancies in screening results. The same PECO screening criteria (presented in Appendix F) were utilized during both TIAB and full- text screening of data sources containing environmental and human health hazard information relevant for Part 2. During screening, calibration was conducted to increase consistency in interpretation of PECO screening criteria between reviewers. Calibration allowed for clarifying modifications to be made to the PECO screening criteria, published in Appendix H.5.13 of the 2021 Draft Systematic Review, to reduce discrepancies in interpretation where identified (U.S. EPA. 2021a). The PECO screening criteria for asbestos include a requirement for quantitative asbestos exposure concentration. Although the PECO screening criteria encompass considerations and updates following screening calibration for both environmental and human health hazard data, the PECO screening criteria modifications relevant for the screening of environmental hazard data will be described in the forthcoming systematic review protocol supplemental document included in the Part 2 of the Risk Evaluation for Asbestos. As shown in the literature inventory tree above in Figure Apx B-l, 343 references met full-text PECO criteria (338 peer-reviewed studies, 3 gray literature references, and 2 data sources pursuant to TSCA). These references were further screened as described in Section 3.3 to identify a subset of these studies potentially informative for dose-response that proceeded to data quality evaluation and extraction. Studies were considered by cohort groupings. For example, if multiple publications were available on a particular occupational cohort, they were considered as a set of information rather than as independent publications. B.2 Identification of Studies Potentially Informative for Dose-Response Analysis An additional screening was conducted after full-text screening to identify the subset of studies that met PECO screening criteria that contained dose-response data. In an effort to streamline the identification of studies relevant to dose-response assessment, EPA implemented modifications to the process described in the 2021 Draft Systematic Review Protocol (U.S. EPA. 2021a). The modifications included conducting further screening of studies that met PECO criteria to identify the most relevant evidence 6 SWIFT-Active Screener is another systematic review software that EPA uses in the TSCA systematic review process. From Sciome's SWIFT-Active Screener web page: "As screening proceeds, reviewers designate articles as having met or not having met criteria, while an underlying statistical model in SWIFT-Active Screener automatically computes which of the remaining unscreened documents are most likely to be relevant. This 'Active Learning' model is continuously updated during screening, improving its performance with each reference reviewed. Meanwhile, a separate statistical model estimates the number of relevant articles remaining in the unscreened document list." 7 SWIFT is an acronym for "Sciome Workbench for Interactive Computer-Facilitated Text-mining." SWIFT-Active Screener uses machine learning approaches. 8 As noted on the DistillerSR web page, this systematic review software "automates the management of literature collection, triage, and assessment using AI and intelligent workflows...to produce transparent, audit ready, and compliant literature reviews." EPA uses DistillerSR to manage the workflow for screening and evaluating references; the literature search is conducted external to DistillerSR. Page 44 of 102 ------- 1319 1320 1321 1322 1323 1324 1325 1326 1327 1328 1329 1330 1331 1332 1333 1334 1335 1336 1337 1338 1339 1340 1341 1342 1343 1344 1345 1346 1347 1348 1349 1350 1351 1352 1353 1354 1355 1356 1357 1358 1359 1360 1361 1362 1363 1364 1365 1366 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 prior to conducting data quality evaluation. The further screening was based on the data analysis method used in the study (regression and SMR studies were included), the method of exposure measurement (based on Data Quality Evaluation Metric 4), and the range, distribution, and levels of exposure in the analysis (based on Data Quality Evaluation Metric 5). Step 1 of Further Screening for Fit for Purpose Context: Identification of Studies that Used Standardized Mortality Ratios and Regression Analysis Prior asbestos assessments, including Part 1 of the Risk Evaluation for Asbestos (U.S. EPA. 20201 focused their dose-response analyses on studies that assessed exposure-response relationships using either SMRs or multivariate regression analyses. An SMR is a ratio or percentage of the observed mortality in a given study sample relative to the mortality in a specified general population (examples include males in Montana, U.S. adults, etc.). Multivariate regression analyses generally estimate the average relationship between an exposure and an outcome in a given study population, while holding other factors constant (adjusting for other variables). Both SMRs and regression analyses can be used to assess a dose-response relationship, particularly when the modeled relationship has either three or more exposure groups or is continuous. Because of the utility of SMR and regression studies in dose-response assessment, EPA further screened PECO-relevant studies to identify the subset of these studies that used SMR and/or regression analyses. During this screening, study inventorying was also conducted, capturing details on route of exposure, endpoint analyzed, study type, study design, cohort name/location, and analysis characterization. The Distiller Form for this binning/inventory is included in Appendix E. Studies that were tagged as SMR studies or regression analyses based on this binning/inventory process moved on to the next step of further screening. Step 2 of Further Screening for Fit for Purpose Context: Identification of Studies with Sufficient Exposure Measurement and Range For all studies identified as either regression or SMR studies, for each outcome in the paper or cohort group, Metrics 4 and 5 were evaluated before other data quality evaluation metrics. Each paper or cohort group of papers was evaluated by two epidemiologists: an initial evaluator and a quality control (QC) reviewer. If the paper or cohort group was rated as Medium or High for Metrics 4 and 5, then the initial evaluator moved on to data quality evaluation for all metrics, and then all data quality evaluation metrics and comments went on to QC review. If either Metric 4 or 5 was rated Low or Uninformative, then the initial reviewer submitted for QC without evaluation of the remaining metrics. If the QC reviewer determined that Metrics 4 and 5 should have been rated Medium or High, then the paper or cohort group was sent back to the initial reviewer for evaluation of the remaining metrics prior to completion of QC. Exposure Measurement: In epidemiology studies, asbestos exposure is typically expressed as the product of the amount of asbestos dust in the air (fibers or particles per mL) and the total amount of time (years) exposed to each concentration (fibers/mL-years). Prior to 1968, the midget impinger method was (Dement et al.. 2008) the most commonly used method for determining the level of asbestos in occupational air. With no details on fiber type or particle size distribution, data from midget impingers only give a rough estimation of the amount of asbestos in the air (SAB. 2008). With advancement in methodological techniques, it was later determined that use of PCM was a more accurate method to detect and quantify asbestos fibers in air samples (Leidel et al.. 1979). PCM identifies fibers according to the NIOSH 7400 Method. More specific characterization of asbestos can be achieved using TEM. In contrast to optical microscopy, which uses a beam of light, TEM uses a high-energy electron beam to view structures that are considerably smaller. Compared to PCM, the majority of TEM instruments used Page 45 of 102 ------- 1367 1368 1369 1370 1371 1372 1373 1374 1375 1376 1377 1378 1379 1380 1381 1382 1383 1384 1385 1386 1387 1388 1389 1390 1391 1392 1393 1394 1395 1396 1397 1398 1399 1400 1401 1402 1403 1404 1405 1406 1407 1408 1409 1410 1411 1412 1413 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 for asbestos analysis feature technology that enables a more thorough characterization of a particle. The total number of fibers counted on a sample grid as well as the number of PCM equivalent (PCMe) fibers are typically recorded and estimated using TEM in order to measure the fiber size, distribution, and dimension. TEM examination of mineral fibers is often used to confirm fiber analysis by PCM. By comparing the fiber's ionic spectrum to a recognized standard and determining the mineralogy of a target fiber, TEM analysis enables microscopists to identify the target fiber (U.S. EPA. 2014a). In addition, multiple measurements taken by PCM or TEM for a given exposure setting is preferred over a single measurement. Although some studies collect measurements of dust using midget impingers, these exposure measurements alone are less reliable in the context of dose-response assessment because the differentiation of fiber types is not possible. In cases where exposure data collected by midget impingers was used in analyses, it is strongly preferred that a conversion factor is applied based on paired sampling measurements using impingers and PCM. Because of the importance of the of exposure measurement in dose-response assessment, OPPT evaluated the exposure measurement (Metric 4) before evaluating other data quality evaluation metrics to focus on the subset of studies with the most reliable asbestos fiber detection and quantification methods (i.e., PCM or TEM). Studies that were rated Low or Uninformative for Metric 4 did not move on to data quality evaluation. The data quality evaluation criteria for Metric 4 are as follows: Mark as High if: For all study types: Quantitative estimates of exposure were consistently assessed (i.e., using the same method and sampling time-frame) during multiple time periods and using either PCM or TEM. OR A combination of methods were used over time (i.e., midget impinger, PCM or TEM), but side-by-side sampling and analyses were conducted to develop appropriate conversion criteria. AND For an occupational population, contains detailed employment records and quantitative estimates of exposure using either PCM or TEM which allows for construction of job-matrix for entire work history of exposure (i.e., cumulative or peak exposures and time since first exposure). Mark as Medium if: For all study types: Exposure was assessed during one time period but this time period is judged to be reasonably representative of the entire study time period. Page 46 of 102 ------- 1414 1415 1416 1417 1418 1419 1420 1421 1422 1423 1424 1425 1426 1427 1428 1429 1430 1431 1432 1433 1434 1435 1436 1437 1438 1439 1440 1441 1442 1443 1444 1445 1446 1447 1448 1449 1450 1451 1452 1453 1454 1455 1456 1457 1458 1459 1460 1461 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 AND Exposure was assessed using a combination of midget impingers, PCM, and/or TEM measurements, but side-by-side sampling and analyses were not conducted for all operations and thus there is a lack of confidence in the conversion factors.) OR For an occupational study population, contains detailed employment records and quantitative estimates of exposure using a combination of midget impingers and PCM or TEM measurements for only a portion of participant's work history of exposure (i.e., only early years or later years), such that extrapolation of the missing years is required. Mark as Low if: For all study types: Exposure was estimated solely using professional judgement. OR Exposure was directly measured and assessed using a quantitative method other than PCM or TEM and conversion factors were not determined. OR The method of quantifying/counting fibers was not specified (PCM, TEM, or other method not specified). *If "acceptable," refer to the evaluation guide to see confidence level criteria. Mark as Uninformative if: For all study types: Methods used to quantify the exposure were not well defined, and sources of data and detailed methods of exposure assessment were not reported (STrengthening the Reporting of OBservational studies in Epidemiology rSTROBE! Checklist 7 and 8 ("Von Elm et al.. 2008). OR There was no quantitative measure or estimate of exposure. OR There is evidence of substantial exposure misclassification that would significantly bias the results. Mark asN/A if: Page 47 of 102 ------- 1462 1463 1464 1465 1466 1467 1468 1469 1470 1471 1472 1473 1474 1475 1476 1477 1478 1479 1480 1481 1482 1483 1484 1485 1486 1487 1488 1489 1490 1491 1492 1493 1494 1495 1496 1497 1498 1499 1500 1501 1502 1503 1504 1505 1506 1507 1508 1509 1510 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Do not select for this metric. Range, Distribution, and Levels of Exposure: To derive a dose-response relationship from an epidemiologic study, it is necessary for the study analysis to inform how a unit change in exposure relates to a unit change in risk for a health outcome. This is most easily accomplished with studies that estimate the relationship between a continuous measure of exposure and a health outcome. However, a dose-response relationship can also be estimated for studies that report the relationship between a categorical measure of exposure and a health outcome as long as there are a sufficient number of exposure groups to approximate a continuous relationship. This is done by estimating a dose-response line that passes through the mid-points of each of the exposure categories. Three or more exposure groups, including one unexposed or lower-exposed group and at least two additional exposed groups, is considered the minimum for being able to adequately approximate a dose-response relationship in this manner. Thus, studies that were rated Low or Uninformative for Metric 5 did not move on to data quality evaluation. Metric 5 explicitly evaluates whether the study includes sufficient exposure data for dose-response assessment, regardless of potential bias or lack of bias in the study methodology. Thus, Metric 5 was evaluated before the other data quality evaluation metrics, and only those studies that were rated as Medium (High is not an option) for Metric 5 moved on to data quality evaluation. The data quality evaluation criteria for Metric 5 are: Mark as High if: Do not select for this metric. Mark as Medium if: For all study types: The range and distribution of exposure is sufficient or adequate to develop an exposure-response estimate (Cooper et al.. 2016). AND Reports 3 or more levels of exposure (i.e., referent group +2 or more) or an exposure-response model using a continuous measure of exposure. Mark as Low if: For all study types: The range of exposure in the population is limited. OR Reports 2 levels of exposure (e.g., exposed/unexposed)) (Cooper et al.. 2016) (Source: IRIS) Mark as Uninformative if: Page 48 of 102 ------- 1511 1512 1513 1514 1515 1516 1517 1518 1519 1520 1521 1522 1523 1524 1525 1526 1527 1528 1529 1530 1531 1532 1533 1534 1535 1536 1537 1538 1539 1540 1541 1542 1543 1544 1545 1546 1547 1548 1549 1550 1551 1552 1553 1554 1555 1556 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 For all study types: The range and distribution of exposure are not adequate to determine an exposure-response relationship (Cooper et al.. 2016). OR No description is provided on the levels or range of exposure. Mark asN/A if: Do not select for this metric. B.3 Data Quality Evaluation All references that met PECO screening criteria, as described above in Section 3.2 and that used regression or SMR analyses and were rated as Medium or High for Metrics 4 and 5 underwent full data quality evaluation as an individual reference or as part of a cohort group, as described in Appendix R of the 2021 Draft Systematic Review Protocol and the Draft Risk Evaluation for Asbestos Part 1 Systematic Review Supplemental File: Data Quality Evaluation of Raman Health Hazard Studies: Mesothelioma and Lang Cancer Studies (March 2020), with some modifications described below (U.S. EPA. 2021a). Part 1 of the Risk Evaluation for Asbestos evaluated the association between inhalation exposures to asbestos and the outcomes of mesothelioma, lung cancer, laryngeal cancer, and ovarian cancer. Part 2 included additional outcomes including other cancers and asbestosis, pulmonary function/spirometry results, pleural plaques, and other non-cancer outcomes. For mesothelioma, the mesothelioma data quality evaluation form used in Part 1 of the Risk Evaluation for Asbestos was used for Part 2, with some modifications based on the calibration for data quality evaluation. For other outcomes, the lung cancer data quality evaluation form from Part 1 was used with additional modifications to evaluate other outcomes that were not considered in Part 1. Prior to beginning calibration and then data quality evaluation for asbestos, the data quality evaluation criteria from the Draft Risk Evaluation for Asbestos: Systematic Review Supplemental File: Data Quality Evaluation of Human Health Hazard Studies: Mesothelioma and Lang Cancer Studies (March 2020) were reviewed, and changes were made to the criteria to address the additional outcomes included in Part 2. In Part 1 of the Risk Evaluation for Asbestos, there were separate data quality evaluation forms for mesothelioma and lung cancer due to the differences between these health outcomes. In comparison to lung cancer and other health outcomes, mesothelioma has a lower incidence and a longer latency period. Furthermore, mesothelioma has few known causes other than asbestos and few potential confounders, and thus has different data quality considerations than lung cancer as well as other outcomes. Therefore, for Part 2 of the Risk Evaluation, a separate data quality evaluation form was maintained for mesothelioma, and the lung cancer data quality evaluation form was modified to include considerations of other cancer and non-cancer outcomes. Calibration was then conducted, resulting in additional clarifying modifications to the data quality evaluation criteria. The data quality evaluation criteria for Asbestos Part 2 are presented in Appendix G. TableApx G-l presents the data quality evaluation criteria for mesothelioma and Table Apx G-2 presents the data quality evaluation criteria for other outcomes. Page 49 of 102 ------- 1557 1558 1559 1560 1561 1562 1563 1564 1565 1566 1567 1568 1569 1570 1571 1572 1573 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 B.4 Consideration of Epidemiologic Cohorts for Dose-Response Analysis Following the data quality evaluation of each cohort, those receiving Medium or High OQD ratings were further reviewed to confirm suitability for dose-response assessment. The cohorts were categorized for examination of cancer and/or non-cancer outcomes. Additionally, the exposure and outcome data and analysis performed were reviewed to confirm the use of PCM or TEM for measurement of asbestos fibers or application of an appropriate conversion factor, use of air measurements in the analysis, analysis conducted with outcome data, and adequate assessment of the outcome (e.g., sufficient follow- up time). At this point, some cohorts were removed from further consideration because the quantitative analyses were not done with PCM or TEM measurements or a conversion factor even though the study may have presented some PCM or TEM data (e.g., passing Metric 4). Other cohorts were removed from consideration because they had received a Low or Uninformative OQD rating in data quality evaluation. Cohorts that were used in the derivation of the existing IURs or RfC were automatically included for dose-response consideration so that a complete assessment of each IUR and RfC could be achieved, noting strengths and uncertainties related to the underlying data. Sections 4 and 5 provide detailed descriptions of the cohorts and the existing IURs and RfC, respectively. Page 50 of 102 ------- 1574 1575 1576 1577 1578 1579 1580 1581 1582 1583 1584 1585 1586 1587 1588 1589 1590 1591 1592 1593 1594 1595 1596 1597 1598 1599 1600 1601 1602 1603 1604 1605 1606 1607 1608 1609 1610 1611 1612 1613 1614 1615 1616 1617 1618 1619 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Appendix C NON-CANCER EPIDEMIOLOGIC COHORTS C.l Cohorts Included in the IRIS Libby Amphibole Assessment The IRIS LAA Assessment presents the cohorts considered in Figure 4-1 of the Toxicological Review (U.S. EPA. 2014b). There were two distinct occupational cohorts including miners and millers in Libby, Montana, and fertilizer plant workers in Marysville, Ohio, where vermiculite from Libby was received, processed, and packaged for distribution. Libby, MT, Mining and Milling Cohort As described in Section 5.2.2, the Libby, MT, Mining and Milling Cohort included men who worked in the open-pit vermiculite mine outside of Libby in either mining or milling operations. There were several different investigations of this cohort that differed in inclusion criteria; however, each examined non-cancer morbidity and mortality. The exposure assessment data used in analyses the non-cancer outcomes are the same as those described for the cancer mortality as described in Section 5.2.2 and in greater detail in Table 4-1 and Section 4.1.1.1 of the IRIS LAA Assessment (U.S. EPA. 2014b). For outcome assessment in all investigations, mortality was determined by death certificates with a certified underlying cause of death. Examination of pulmonary outcomes in workers were assessed by chest x- ray. Films were randomized and independently read by three qualified readers using the 1980 ILO classification system to identify parenchymal abnormalities. O.M. Scott, Marysville, OH, Fertilizer Plant Workers The O.M. Scott plant in Marysville, Ohio, was a site that received vermiculite ore by rail where it was process into expanded form for use as an inert carrier for herbicides and fertilizers. A total of 512 workers participated in the 1980 investigation on the pulmonary effects in Ohio plant workers (Lockev et al.. 1984). Follow-up of the original cohort including chest x-rays and interview was conducted in 2004 (Rohs et al.. 2008) and vital status for mortality in 2011 (Dunning et al.. 2012). For this cohort, there were eight main departments at the vermiculite ore processing plant in Marysville, Ohio, including production and packaging of commercial products, maintenance, research, the front office, and the polyform plant. The vermiculite ore was delivered by train or truck to the facility, processed and packaged, and stored. Dust controls were implemented beginning in 1967 leading to a marked improvement in dust management during the course of the 1970s. Monitoring of industrial hygiene at the facility started in 1972 which consisted of an industrial hygienist following a worker with a sampling device. After 1976, personal breathing-zone samples were collected and analyzed by PCM. Cumulative exposures for each worker were estimated using detailed work histories and industrial hygiene data. Overall, employees were divided into three different exposure groups: nonexposed workers (chemical processing, research, front office), low exposed workers (central maintenance, packing, and warehouse), and high exposed workers (expander, plant maintenance, and pilot plant) (U.S. EPA. 2014b; Lockev et al.. 1984). In 2009, the exposure analyses were updated based on the inclusion of newly available information on sampling and industrial hygiene records resulting from litigation records related to Libby vermiculite (U.S. EPA. 2014b; Borton et al.. 2012). Exposure-response analyses were conducted for respiratory outcomes and mortality based on the detailed exposure estimates in 2004, and 2009, respectively. Comprehensive, individual-level data was available from physical examination and interviews with each participant, allowing more control for confounding in the analysis. Also notable is that the extended follow-up periods provided time from first exposure that ranged from 23 to 47 years (U.S. EPA. 2014b). Page 51 of 102 ------- 1620 1621 1622 1623 1624 1625 1626 1627 1628 1629 1630 1631 1632 1633 1634 1635 1636 1637 1638 1639 1640 1641 1642 1643 1644 1645 1646 1647 1648 1649 1650 1651 1652 1653 1654 1655 1656 1657 1658 1659 1660 1661 1662 1663 1664 1665 1666 1667 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 C.2 Cohorts Not Previously Considered in Non-cancer Assessments SC Textiles Cohort The workers included in the SC Textile Cohort studies described in Appendix D.l and included in Part 1 of the Risk Evaluation for Asbestos were also followed for non-cancer outcomes, primarily asbestosis pneumoconiosis mortality. The exposure measurement and assignment methods for the non-cancer analyses are the same as those used in the exposure-response analyses for cancer. Hein et al. (2007) and Stavner et al. (2008) included the longest follow-up for non-cancer mortality in this cohort with vital status through 2001. These studies included an extension of the original cohort to include non-white workers and females. Strong associations between asbestos exposure and asbestosis and pneumoconiosis-related mortality were demonstrated in the analysis of this cohort. SC Vermiculite Miners and Millers Cohort W.R. Grace & Company conducted a study of vermiculite miners in Enoree, South Carolina, in 1988 drawing comparisons to the health effects observed in the Libby, Montana, mines (W. R. Grace & Co. 1988). The study included a cohort of 194 men involving in milling and mining vermiculite with exposures to tremolite fibers. The mine opened in 1946 and employment was at 80 men in the 1960s. Dust control procedures were implemented in 1970. In 1985 and 1986, 21 bulk samples and 58 static air samples were collected. Bulk sample analysis showed the presence of tremolite-actinolite, vermiculite fragments, talc/anthophyllite, and iron rich fibers. Air samples form 10 different areas were analyzed by PCM, all below 0.01 f/cc. Additionally, the study references other exposure measurement data, including 125 air samples from Mine Safety and Health Administration and personal samples of longer durations than static samples, but details are not provided. Estimates of exposure were calculated based on work history and calculated fibers concentrations in wet and dry zones. Mortality data was collected through 1985, providing a minimum latency of 15 years. Radiographic films were taken and sputum collected in April to May 1986. Overall, mean length of employment for the cohort was 9.2 years and mean length of time between start of employment and death was 19.7 years. Exposure-response analyses were conducted for mortality and excess mortality was observed. Results for sputum and parenchymal abnormalities were only categorically reported for exposed and unexposed employees. Anatolia, Turkey, Villagers Cohort In Anatolia, Turkey, there are deposits of asbestos, known as white soil, that has been used in as many as 196 villages in the past, Metintas et al. (2005) conducted a study to examine respiratory outcomes among villagers in a subset of villages with ongoing environmental exposures to asbestos. Ten villages were randomly selected and 991 residents at least 30 years of age were included in the cohort. Assessment of soil samples showed the presence of tremolite, anthophyllite, actinolite, and chrysotile asbestos. For each village, indoor and outdoor air samples were collected and fibers counted by PCM. Cumulative fiber estimates for each villager were calculated based on the assumption of an 8-hour workday outside of the home, 8 hours sleeping within the home, 8 hours of household activity, and 11 months spent in the village each year. Villagers completed questionnaires and had clinical and radiological examining conducted with a portable roentgenogram and had additional follow-up if abnormalities were detected. Outcomes of interest included pleural plaques, diffuse pleural fibrosis, and asbestosis. Multivariate logistic regression analysis was performed, but few details of the analysis are provided in the study. Additionally, TSFE was not characterized for the cohort. Chinese Chrysotile Textile Factory Cohort In the suburb of Shanghai, China, a chrysotile textile product factory opened in 1958 that employed 1,059 workers between opening and follow-up in September of 1982. Huang (1990) examined exposures to workers and asbestosis. In the exposure-response analysis, exposures for each of the 776 Page 52 of 102 ------- 1668 1669 1670 1671 1672 1673 1674 1675 1676 1677 1678 1679 1680 1681 1682 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 workers with at least 3 years of employment with sufficient documentation for study inclusion were determined by combining detailed work histories with asbestos routine air measurements collected from 17 worksites across the factory using membrane filters. For earlier asbestos exposures, fiber estimates were derived from dust concentrations converted based on site-specific conversion factors and linear regression. Onset of asbestosis was assessed based on chest x-ray films using ILO classification. Linear regression showed strong correlation between asbestos exposure and asbestosis in this cohort. Wittenoom, Australia, Residents Cohort As described in Appendix D.4, the Wittenoom, Australia, Residence Cohort comprised all individuals residing in Wittenoom for at least 1 month between 1943 and 1992. The exposure assessment data used in analyses the non-cancer mortality outcomes are the same as those described for the cancer mortality. Only one study identified for this this cohort examined non-cancer mortality; Reid et al. (2008) described excess mortality in women and girls of the cohort for a variety of causes including pneumoconiosis. Overall, there is only limited non-cancer data available from this cohort for dose- response consideration. Page 53 of 102 ------- 1683 1684 1685 1686 1687 1688 1689 1690 1691 1692 1693 1694 1695 1696 1697 1698 1699 1700 1701 1702 1703 1704 1705 1706 1707 1708 1709 1710 1711 1712 1713 1714 1715 1716 1717 1718 1719 1720 1721 1722 1723 1724 1725 1726 1727 1728 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Appendix D CANCER EPIDEMIOLOGIC COHORTS D.1 Cohorts Included in the Risk Evaluation for Asbestos Part 1 South Carolina Textiles Cohort, U.S. Many publications have reported on the mortality of a group of workers at a textile plant in Charleston, South Carolina, which produced asbestos. The plant produced textiles from raw chrysotile asbestos fibers that were imported from Rhodesia (Zimbabwe) and Canada. Crocidolite yarns were also used in a small operation within the plants, but overall, only accounted for 0.03 percent of the annual asbestos processed. In terms of exposure assessment for the cohort, beginning in the 1930s, the facility implemented engineering measures to manage dust levels, and at the time, it was regarded as the industry's "gold standard." Based on 5,952 industrial hygiene air samples taken between 1930 and 1975, estimates of personal exposure were derived. Prior to 1965, only midget impinger samplers were used to collect all samples. From 1965 to 1971, both impinger and membrane filter samplers were employed. Post-1971, only membrane filter samplers were employed (U.S. EPA. 2020). To determine the concentrations of fibers 5 [j,m or longer, PCM and membrane filter sampling were used. Conversion factors between membrane and impinger samples were derived to calculate job and operation-specific asbestos measurements. In 1965, 120 paired samples were collected, and between 1968 and 1971, 986 concurrent samples were also collected, and statistical analysis showed no significant changes in the fiber/dust ratios over time or between operations. Overall, asbestos measurements were estimated for nine departments and four job categories using linear regression with adjustment for time-related changes in process and dust control, and individual cumulative exposures for workers were determined based on detailed occupation histories and the constructed job exposure matrix (U.S. EPA. 2020V A follow-up of 3,072 workers through 2001 provided the most recent data for lung cancer and mesothelioma in the cohort. For study inclusion, workers needed to be employed for at least 1 month between 1940 and 1965, which primarily consisted of white men initially, but later study years included non-white men and women. Using Poisson regression modeling and a linear relative rate form, quantitative exposure-response associations for lung cancer were calculated. Chrysotile asbestos exposure cumulative in f/cc-yr was entered as a continuous variable with sex, race, and age as variables, and it was lagged by 10 years (U.S. EPA. 2020). Of the available information and data in publications, individual-level lung cancer and mesothelioma data from Hein et al. (2007). Elliot et al. (2012). and Berman and Crump (2008) were used in linear and exponential modeling to derive Kl and Km values. North Carolina Textiles Cohort, U.S. In four North Carolina textile mills that used asbestos, authors reported on mortality in a cohort of workers that had not been previously researched. Three of these plants produced yarns and woven goods from raw chrysotile fibers while one, smaller plant produced asbestos products using purchased yarns. One of the larger factories also used amosite fibers, however, this was a separate operation from that using raw chrysotile. These factories, unlike the South Carolina plants, did not use exposure controls. Company records listed 5,770 workers (3,975 men and 1,795 women) with at least 1 day of employment between 1950 and 1973 and vital status and state or national health agency records were collected Page 54 of 102 ------- 1729 1730 1731 1732 1733 1734 1735 1736 1737 1738 1739 1740 1741 1742 1743 1744 1745 1746 1747 1748 1749 1750 1751 1752 1753 1754 1755 1756 1757 1758 1759 1760 1761 1762 1763 1764 1765 1766 1767 1768 1769 1770 1771 1772 1773 1774 1775 1776 1777 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 through 2003. These records included ICD codes indicating cause of death, including intermediate causes and any relevant conditions. Of note, prior to the introduction of a unique code for mesothelioma in 1999, death certificate data were reviewed for any mention of mesothelioma and for ICD codes frequently used to indicate mesothelioma (U.S. EPA. 2020). Between 1935 and 1986, 3,420 air samples were collected and the presence of asbestos fibers was assessed. Both impinger sampling and membrane filter sampling were utilized up until 1971, when impinger sampling was no longer used. Sampling prior to 1964 was done using impingers. To estimate concentrations, fibers longer than 5 [j,m were counted on membrane filters. To determine plant-, operation-, and period-specific parameters for converting dust to PCM-equivalent fiber concentrations, paired and contemporaneous samples by both methods were used. Fiber/dust ratios did not change significantly (U.S. EPA. 2020). Multivariable mixed models were used to assess fiber concentration data and estimate average concentrations by factory, department, job, and time period. The employment-exposure matrix's functioning and job categories were the same as those created for South Carolina. To determine each worker's average and cumulative exposure to asbestos fibers, these estimations were correlated with their individual work history records. Where records lacked detailed job titles within departments (27% of employees, primarily those with short-term positions), exposure was calculated using the averages for the plant, time, and department. Exposures during the years before 1935, when there were no exposure measurements and little work history records available, were presumed to be the same as those in 1935, before dust restrictions were put in place (U.S. EPA. 2020). A Poisson regression analysis with both log-linear and additive relative rate model types, was used to examine exposure-response relationships for lung cancer in the North Carolina cohort. Age, sex, race, the year of birth, and birth cohort were taken into account during modeling. With lags of 0, 10, or 20 years, the results were presented per 100 f/cc-yr of cumulative fiber exposure. Kl and Km values were reported for the individual-level data presented in Loomis et al. (2009) and Elliott et al. (2012) based on linear and exponential model results. A Poisson regression analysis with both log-linear and additive relative rate model types, was used to examine exposure-response relationships for lung cancer in the North Carolina cohort. Age, sex, race, the year of birth, and birth cohort were taken into account during modeling. With lags of 0, 10, or 20 years, the results were presented per 100 f/cc-yrs of cumulative fiber exposure. Kl and Km values were reported for the individual-level data presented in Loomis et al. (2009) and Elliott et al. (2012) based on linear and exponential model results. Quebec, Canada, Asbestos Mines and Mills Cohort Several investigations of workers at various mining, milling, and production facilities in Quebec, Canada, are available. The oldest publication included 11,379 Canadian miners and mill workers from Quebec who were born between 1891 and 1920 and had worked for at least a month in the mines and mills. The cohort was followed to 1975 where additional findings were published based on the cohort's follow-up through 1988, and extended analysis to include data through 1992 (U.S. EPA. 2020). In these studies, exposure assessment methods varied. Midget impinger readings from 1948 to 1966 were used to estimate total dust concentrations in mppcf, and studies report a range of 3,096 to 10,205 samples for 5,782 unique job assignments according to a 13-point scale ranging from 0.5 to 140 mppcf. Although the categories are described by the authors as "approximating the mean," the procedures used to analyze the exposure measures and assign categories are not described. Different methods were employed to estimate exposures in earlier and later years when dust data were deemed to be insufficient or not available. Exposures in years prior to 1948 were based on expert assessment from interviews with Page 55 of 102 ------- 1778 1779 1780 1781 1782 1783 1784 1785 1786 1787 1788 1789 1790 1791 1792 1793 1794 1795 1796 1797 1798 1799 1800 1801 1802 1803 1804 1805 1806 1807 1808 1809 1810 1811 1812 1813 1814 1815 1816 1817 1818 1819 1820 1821 1822 1823 1824 1825 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 employees and company personnel, while those in years following 1966 were extrapolated from the previously measured levels (U.S. EPA. 2020). The initial publications reported exposure-response analyses based on dust concentrations in mppcf. Some of the later investigations applied conversion factors ranging from approximately 3 to 7 f/cc per mppcf. The basis for these conversion factors, however, is not well described and the reported confidence in these conversion factors also varies. In addition, later examination of dust samples from Quebec mines reported by (Berman. 2010). demonstrated that a third of the structures in samples were not asbestos in PCM and TEM analysis. These findings raise serious doubts about the accuracy of the f/cc estimates of exposure from the Quebec investigations, combined with issues surrounding the selection of an appropriate conversion factor. Ultimately, Kl values were estimated based on modeling with data from Berman and Crump (2008). but because of uncertainties, they were not used in final IUR derivations (U.S. EPA. 2020). Qinghai, China, Asbestos Mine Cohort The Qinghai Mine first opened in 1958 and produced raw commercial chrysotile. The examination of workers from this mine included individuals that were on the registry in 1981 and were employed for at least 1 year. They were followed from 1981 to 2006. Periodically between 1984 and 1995, area sampling at specified places was used to measure total dust concentrations, though the number of measurements was not reported. In addition, 28 measurements in 6 different workshops were taken in 2006. Dust concentrations were converted to f/cc using a linear regression model built from 35 paired measurements taken in 1991. Fiber concentrations were determined for each workshop and job description from 1984 to 2006 using a single conversion factor, though the estimation techniques are not fully explained in English-language publications. In the Part 1 of the Risk Evaluation for Asbestos, Kl values were calculated using data from Wang et al. (2013) and Wang et al. (2014). A strength of the analysis in these studies was the use of continuous exposure variables in log-linear Cox proportional hazards models adjusted for age and smoking. Despite the statistically robust analysis, results from these investigations were not selected for final IUR derivations due to uncertainties in the exposure measurements and assignment. Balangero, Italy, Mining Cohort This historical cohort was the subject of four relevant publications (Pira et al.. 2017; Pira et al.. 2009; Piolatto et al.. 1990; Rubino et al.. 1979); however, the cohort studies from Balangero, Italy, were omitted due to the models' failure to produce findings when exposure was measured continuously. The Balangero Mine and Mill, was located northwest of Turin, and workers were exposed to chrysotile asbestos. The mine began operations in 1916, expanded to produce an average of 130,000 to 160,000 tons of chrysotile asbestos per year in the 1970s, and shut down in 1990, before all forms of asbestos, including chrysotile, were outlawed in Italy in 1992. The cohort included 952 workers who had each worked at least 30 calendar days between January 1, 1930, and December 31, 1965, and were still living on January 1, 1946. Additionally, a small number of contract workers who were occasionally employed on the Balangero site and subjects who worked for less than a year were not included in the cohort. The factory's personnel records provided information on employment, and population registrations and copies of death certificates from municipal registration offices provided information on vital status and causes of death for this cohort. Date of birth, employment history, cause of death (including contributing factors for deaths that happened since 1988), job category, and latest information for subjects who were lost to follow-up were all accessible. Since researchers were unable to determine when subjects' Page 56 of 102 ------- 1826 1827 1828 1829 1830 1831 1832 1833 1834 1835 1836 1837 1838 1839 1840 1841 1842 1843 1844 1845 1846 1847 1848 1849 1850 1851 1852 1853 1854 1855 1856 1857 1858 1859 1860 1861 1862 1863 1864 1865 1866 1867 1868 1869 1870 1871 1872 1873 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 employment ended after December 31, 1987, they used the assumption that those who were still employed at the mine on that day would continue there until production stopped in 1990. Data on exposure were quantified using the cumulative dose of inhaled fibers reported in fiber-years. This was calculated using environmental observations from 1969 onward and synthetically reconstructed working conditions for earlier times. In order to determine the cohort's mortality experience through 1975, 98 percent of the cohort was tracked down. Overall, 332 deaths were recorded versus 214.4 predicted, which is an extraordinarily high mortality rate. Nevertheless, non-malignant respiratory disorders, cardiovascular diseases, and accidents accounted for the majority of the extra mortality. Only laryngeal cancer was found to be considerably overrepresented in the entire sample, with the overall SMR for all malignant neoplasms being 106. Chongqing, China, Asbestos Products Factory This cohort started with a preliminary study on worker fatalities at a Chongqing, China, facility that manufactured a range of asbestos-containing items. Using plant data, a fixed cohort of 515 males who had been working for at least a year and were active as of January 1, 1972, was formed. Since no women were hired before 1970, none were part of the founding cohort. In later studies, additional analyses based on extensive follow-up were presented. The cohort's 2008 follow-up included 279 more women who had jobs between 1970 and 1972 (U.S. EPA. 2020). The Chongqing Plant produced a variety of asbestos-containing items including textiles, friction materials, rubber-impregnated commodities, and cement after it first opened in 1939 and then expanded in the 1950s. The plant reportedly used chrysotile asbestos from two mines in Sichuan Province, and it is unlikely that there was amphibole or tremolite contamination. Techniques of exposure assessment that were reported in this cohort were based on 556 area measurements at 4-year intervals between 1970 and 2006. Fiber concentrations for four activities (processing raw materials, textile carding and spinning, textile weaving and maintenance, and manufacturing rubber and cement) were estimated. Prior to 1999, only total dust was recorded; after that year, measurements of both dust and fibers were done in tandem. In total, there were 223 measurements of fiber concentration made using PCM. To estimate dust to PCM fiber-equivalent concentrations for the period 1970 to 1994, paired dust and fiber samples from 1999 to 2006 was used; however, no information was provided on what operations and jobs these estimations reflect. Cumulative individual fiber exposures were calculated based on the concentration information and the length of time employees spent in each section of the factory, which was generally stable over time (U.S. EPA. 2020). Several articles have presented exposure-response information for lung cancer in the Chongqing cohort for various time periods of the study, and Kl values were estimated. However, model fitting could not be conducted for the minimal amount of data on mesothelioma. Furthermore, due to potential for exposure misclassification resulting from the low number of exposure measures, the absence of fiber measurements prior to 1999, and the use of area sampling as opposed to personal sampling, this cohort was not selected for use in IUR derivation (U.S. EPA. 2020). Salonit Anhovo, Slovenia, Asbestos Factory Cohort This historical cohort was the subject of two relevant publications examining asbestos exposure to workers in asbestos cement factory that included factories producing cement, cement pipes, and corrugated sheets. The factory opened in 1921 and began using asbestos in 1922. In 1996, asbestos was Page 57 of 102 ------- 1874 1875 1876 1877 1878 1879 1880 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 1891 1892 1893 1894 1895 1896 1897 1898 1899 1900 1901 1902 1903 1904 1905 1906 1907 1908 1909 1910 1911 1912 1913 1914 1915 1916 1917 1918 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 banned by law in Slovenia. Uniquely, the plant kept record of asbestos use separately for chrysotile and amphibole. The cohort comprised all 6,714 employees who started working at the Salonit Anhovo factory after December 31, 1946, and who did so for at least 1 day between 1964 and 1994. From the cohort, 58 primary lung cancer cases with histological confirmation and 290 healthy controls were chosen. The working life exposure histories to the asbestos form amphibole (10% exposure) and chrysotile (90% exposure) were estimated independently. Some employees in Salonit Anhovo were also exposed to cement dust, which contains hexavalent chromium (Cr6+), and silica dust, which is free SiC>2. For either silica or chromium, airborne concentration data were not available; nonetheless, each contaminant's presence or absence could be determined for each work and each year. The facility-maintained records and tracked of the amount of asbestos utilized throughout production (separately for chrysotile and amphibole). Chrysotile was blended with amphiboles in minor but recognized quantities after being primarily acquired from Canada, Rhodesia, Italy, Russia, and then Yugoslavia. The first records of employment are from 1939, when the factory employed 731 people. The total workforce was down to 520 by the end of World War II, although it quickly increased after the war. By 1953, there were more than 1,000 employees, and in 1981, that number peaked at 2,651. Women made up about 30 percent of the employee population. Between 300 and 800 workers were directly exposed to asbestos each year, with the number fluctuating. From 1961 until 1996, the facility's airborne fiber concentrations were observed for compliance. It was not until 1986 that the workers' exposure conditions significantly changed as a result of the installation of an efficient ventilation system and the introduction of respirators (although they were not used consistently at the time). A total of 1,030 air measurements were taken at the asbestos facility between 1961 and 1995, using a variety of monitoring techniques, including 78 pairs of measurements where the gravimetric and membrane filter methods were utilized side-by-side. Every air sampling measurement was made at a set point that was close to the worker's breathing zone. The side-by-side samples were used to develop conversion factors, which incorporated the information acquired by the various exposure assessment techniques. Part 1 of the Risk Evaluation considered this cohort for exposure to commercial chrysotile and found that it was uninformative for further consideration because it did not adequately allow exposures to chrysotile and amphibole asbestos forms to be separated. However, this limitation is not relevant to Part 2. Thus, these studies were considered further for use in dose-response assessment. Additional limitations in the data are available from these cohorts relevant to the criteria described in Section 5.1. Job exposure matrices were constructed based on worker histories and fiber concentrations from area sampling measurements. However, some jobs did not have relevant air sampling data as they moved between or outside of facilities, and in these instances, a consultation group was used to develop exposure matrices. It is unclear what percentage of study participants for which this applied. Another limitation of this cohort for use in dose-response assessment is the use dichotomous exposure or categorical exposures based on the 90th percentile. As described in Section 5.1, preference is for studies with continuous exposure based on individual-level data (Fikfak et al.. 2007; Fikfak. 2003). Page 58 of 102 ------- 1919 1920 1921 1922 1923 1924 1925 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 D.2 Cohorts Included in the IRIS Libby Amphibole Asbestos Assessment Libby, MT, Vermiculite Mining and Milling Cohort Several studies are available that examine occupational asbestos exposures to LAA. These studies were conducted in Libby, Montana to assess the mining and milling operations or at a plant in Marysville, Ohio, which received vermiculite mined in Libby, Montana. The Libby vermiculite mine opened in 1923 and remained open until 1990. The operations in the open pit mine produced high dust exposures that were reduced in 1970 with new drilling technology. Vermiculite from the mine was shipped by rail beginning in 1935 and enclosed hoppers were only used beginning in 1960. The relevant studies examining this occupational cohort are summarized in Table 4-2 of the IRIS LAA Assessment (U.S. EPA. 2014b). The studies were similar in examining asbestos exposure and outcomes in male workers, but varied in the inclusion criteria (e.g., length of employment, employment date), asbestos quantification, and job-exposure classification. However, in all studies, the asbestos quantification included fiber counts by PCM in later study years and impinger measurements in earlier study years that were converted to f/cc based on analysis of location-specific sampling. Publications on the cohort included various follow-up periods for mortality and pulmonary outcomes, with the longest follow-up in 2006. For lung cancer and mesothelioma, exposure-response relationships were analyzed to derive an IUR. By 2006, approximately 54 percent of the cohort had died, and a detailed individual-level work history and asbestos exposure measurements were available. As described in Section 6.2.2 of the IRIS LAA Assessment (U.S. EPA. 2014b). the data were fit with various models with a range of exposure metrics because there was not a biological basis for model selection. Ultimately, a subcohort was established that included workers hired after 1959, which improved model fitting. Data prior to 1959 did not include as detailed work history which likely contributed to exposure misclassification in the dataset. This subcohort included 880 workers, of which 26 percent had died at time of follow-up. These model fitting results were retained for consideration in the IUR derivation. D.3 Cohorts (Mixed-Fiber) Included in the IRIS Asbestos Assessment Insulation Manufacturing, Paterson, NJ (Amosite) Between 1941 and 1945, men were recruited to work at an amosite asbestos factory in Paterson, New Jersey, to supply the U.S. Navy with insulation materials for ships in World War II. Seidman et al. (1979) and Seidman (1984) examined the mortality among 820 of these men that met study inclusion criteria, including attaining 5 years of employment at the factory. The cohort was followed through 1982 and mortality data was collected. While no air concentrations were available for the Paterson, New Jersey, plant, fiber counts were available from similar plants located in Tyler, Texas, and Port Allegany, Pennsylvania. Data collection in these other plants was conducted by the U.S. Public Health Service in 1967, 1970, and 1971 and reported in the Asbestos Criteria Document of the National Institute for Occupational Safety and Health. Although the number of samples collected and the methods used for fiber counting are not described, it is known that dust control measures were not in place. Exposure- response analysis was conducted with data for this cohort using SMR based on expected and observed cancer deaths in the population. For this cohort, workers with less than 6 months of history had an abnormally high observed mortality rate; thus, adjustments were made yielding a Kl of 0.043 and a Km of 3.2xl0~8(U.S. EPA. 1986). Page 59 of 102 ------- 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Insulation Application, United States (Chrysotile and Amosite) Selikoff et al. (1979) and Peto et al. (1982) studied the mortality experience in members of the International Association of Heat and Frost Insulators and Asbestos Workers in the New York-New Jersey metropolitan area between 1943 and 1976. The cohort included 623 men employed prior to 1943 and 833 men employed after 1943, the latter group reflecting work experience in post-war conditions. Expected and observed cancer deaths were estimated at follow-up in 1962 and 1976. Asbestos concentrations in these specific work facilities were not measured; however, asbestos air concentration measurements were obtained through study of insulation work facilities by three different laboratories in the United States between 1968 and 1971 using the NIOSH and OSHA method (published in 1979; phase contrast illumination) (Leidel et al.. 1979). The average fiber concentration of asbestos dust in insulation work, ranged from roughly 3 to 6 f/mL with 2 to 5 minutes peak concentrations exceeding 100 f/mL. However, it was recognized that asbestos exposures prior to these measurement dates could have been significantly higher due to changes in asbestos products over time (e.g., less asbestos in later years). Because of this, the overall average concentration used was 15 f/mL. For this cohort, a Kl of 0.0075 per fiber/cc was estimated, which included reduction to adjust for death certificate diagnoses rather than best estimates as well as substantial smoking rates in insulation workers. For this cohort, a Km of 1.5x1 0-8 was estimated (U.S. EPA. 1986; Peto et al.. 1982) Asbestos Products Manufacturing, United States (Chrysotile and Crocidolite) Henderson and Enterline (1979) studied a cohort of men who had worked in product or maintenance for a U.S. asbestos company. This cohort was established from company records, including those who retired between 1941 and 1967 and were receiving a company pension. The average length of employment in the asbestos industry for these 1,075 men was 25 years. The cohort was followed through 1973, using company records and SSA files for tracing. For this cohort, total dust concentrations were measured in mppcf and no specific conversion factor was available to present air concentrations in f/mL or f/cc. Thus, in U.S. EPA (1986). air concentration data from other relevant studies was considered. It was determined conversion factors from other industrial settings (i.e., cement plants) was useful and a conversion factor of 1.5 f/mL/mppcf was used. In deriving the KLfor this cohort, it was additionally noted that a retrospective analysis starting from retirement would likely underestimate the actual deaths. After adjustment to account for this, a Kl of 0.0049 was presented. (U.S. EPA. 1986). New Orleans Asbestos Cement Building Material Plants Cohort (Chrysotile and Crocidolite) In the early 1920s, two asbestos cement building materials plants opened in New Orleans, Louisiana, producing flat shingles and corrugating sheets in one plant, and shingles, pipes, and asphalt flooring materials in the other plant. Overall, products contained between 15 and 28 percent asbestos, predominantly chrysotile with crocidolite and amosite in some products. Weill et al. (1979) studied the mortality experience in 5,645 men who had worked in either or both of these plants that had at least 20 years of follow-up from beginning employment. Plant records included demographic information and complete work history for each person and were mostly complete with the exception of poor records before 1942 in one plant. Tracing of the cohort was done in 1974 through SSA records, and only 75 percent could be verified as deceased or living. While study authors considered the ages and potential occupations of those loss to follow-up, there is likely an underestimation of mortality especially when considering that the deaths prior to 1970, more so for blacks, were not reported to SSA. Expected and observed mortality rates were used in exposure-response calculations. Exposure data for this cohort consisted of dust measurements collected with impingers, reported in mppcf. Sampling was initiated in the 1950s and impinger measurements were taken at various locations in both plants. Exposure profiles for each workers were developed using impinger sampling data combined with estimated fiber content for each job by month and year. The dose-response modeling of this data Page 60 of 102 ------- 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042 2043 2044 2045 2046 2047 2048 2049 2050 2051 2052 2053 2054 2055 2056 2057 2058 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 resulted in a Kl of 0.0053, which included adjustment for loss to follow-up and application of a fiber- particle conversion factor of 1.4. Ontario, Canada, Asbestos Cement Factory Cohort (Chrysotile and Crocidolite) An Ontario asbestos-cement factory that began production in 1948 was the manufacturing site for a variety of product including cement board and insulation materials made with both chrysotile and crocidolite. Finkelstein (1983) examined mortality in a cohort of men hired before 1960 and who had been employed for nine or more years. The cohort included production and maintenance workers in asbestos operations as well as workers in rock wool operations that had minimal asbestos exposure. Workers who could not be classified based on work history were excluded from the cohort. Air measurements were collected in the factory using impingers for area sampling from 1949 through the 1960s and membrane filters in personal sampling starting in 1969. Based on crude analysis of the impinger data, fiber concentrations from 1955 to 1961 were assumed to be 30 percent higher and from 1948 to 1954 twice as high. These exposure estimates were matched with detailed work history for each workers based on company records to calculate an annual exposure concentration; however, extrapolations were used for maintenance workers. Even with these uncertainties, exposure estimates were assumed to be accurate to within a factor of 3 to 5. Exposure-response analysis was conducted based on individual-level cumulative exposures over an 18-year period with follow-up through 1980. Local tracing and Statistic Canada were used to determine confirm the deceased and living. Of note, only 2 to 7 percent of the cohort were lost to follow-up and smoking status was obtained for 70 percent of men. Calculations resulted in a Kl of 0.067 and Km of 1,2x 10~7 (U.S. EPA. 1986). D.4 Cohorts Not Included in Existing EPA Assessments Wittenoom, Australia, Residents Cohort From 1937 to 1966, crocidolite (blue asbestos) was mined in Western Australia's Wittenoom Gorge. A single proprietor, the Australian Blue Asbestos firm, which employed about 7,000 people during that time period, owned the plant. The township of Wittenoom was established in 1946 and initially situated just 1.6 km from the mine but was relocated to 12 km away in 1947. Tailings from the mine were high in crocidolite fibers and distributed throughout the town for a variety of uses through the 1960s. The Wittenoom, Australia, Residents Cohort comprised all individuals residing within the town for at least a month between 1943 and 1992 and were not employed in asbestos work. Of the 4,659 former residents in the cohort, follow-up by questionnaire in 1993 resulted in 2,173 responses, confirmed 460 deaths and 549 that could not be traced. By 1993, there only 45 residents remained in the town. The Mines Department of Western Australia used a konimeter to measure dust levels in the mine and mill on a number of occasions between 1948 and 1958. A Casella long running thermal precipitator was used to conduct the first fiber count of the mine, mill, and Wittenoom area in 1966. Using a combination of personal and fixed positional monitors, additional monitoring was conducted in and around the township in 1973, 1977, 1978, 1980, 1984, 1986, and 1992. Based on the monitoring conducted in 1966, inhabitants were allocated an intensity of exposure of 0.5 fiber/milliliter (f/mL) of air between 1958 and 1966, when the mine closed. In light of the assumption that fiber levels were roughly twice as high when the original mill was in operation, a level of 1.0 f/mL was assigned for the period 1943 to 1957. Exposures were interpolated from 0.5 f/ml in 1966 to 0.01 f/mL in 1992 based on dust surveys that employed personal monitors. The product of the fiber content for each year and the amount of time spent in Wittenoom during that year was multiplied by the number of years each resident lived there to determine their cumulative exposure, adjusted to account for a continuous 24-hour exposure. By Page 61 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 2059 demonstrating concordance with lung fiber burdens, the estimations of asbestos exposure have been 2060 internally validated. 2061 2062 The earliest identified publication on the cohort was conducted by Hansen et al. (1998) and 2063 demonstrated a strong relationship between mesothelioma mortality that increased with time from first 2064 exposure and duration of exposure. Additional publications examined differences between age and sex 2065 in mesothelioma mortality in the cohort (Reid et al.. 2007). mortality observed only in women and girls 2066 in the cohort (Reid et al.. 2008). as well as childhood exposures and adult mortality (Reid et al.. 2013). Page 62 of 102 ------- 2067 2068 2069 2070 2071 2072 2073 2074 2075 2076 2077 2078 2079 2080 2081 2082 2083 2084 2085 2086 2087 2088 2089 2090 2091 2092 2093 2094 2095 2096 2097 2098 2099 2100 2101 2102 2103 2104 2105 2106 2107 2108 2109 2110 2111 2112 2113 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Appendix E LITERATURE INVENTORY FORM Asbestos Human Lit Inventory Distiller Form Is this study a candidate for re-screening? {i.e., PECO-relevance related issues) If yes, please stop inventorying. • Case-only, case-case, or other case-report • No quantitative exposure concentration • Other Exposure routes (check all that apply) • Inhalation • Dermal • Oral Endpoints analyzed (check all that apply) • Cancer (check all that apply) o Mesothelioma (ICD-9: 163) o Lung (ICD-9: 162) o Laryngeal (ICD-9: 161) o Ovarian o Other • Non-cancer (check all that apply) o Pleural Plaques o Asbestosis • Other Respiratory (check all that apply) o Spirometry (forced expiratory volume [FEV], total liquid ventilation [TLV], FVC, etc.) o Chest x-ray o Asthma/wheeze o Chronic obstructive pulmonary disease (COPD) o Other • Non-respiratory Study type (focus on the study population) • Occupational o Study Design ¦ Prospective Cohort • Study Identifiers o Cohort/Study Name: o Cohort/Study Location: ¦ Retrospective Cohort • Study Identifiers o Cohort/Study Name: o Cohort/Study Location: ¦ Case-control ¦ Other • Other Page 63 of 102 ------- 2114 2115 2116 2117 2118 2119 2120 2121 2122 2123 2124 2125 2126 2127 2128 2129 2130 2131 2132 2133 2134 2135 2136 2137 2138 2139 2140 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 o Study Design ¦ Prospective Cohort • Study Identifiers o Cohort/Study Name: o Cohort/Study Location: ¦ Retrospective Cohort • Study Identifiers o Cohort/Study Name: o Cohort/Study Location: ¦ Case-control ¦ Other Analysis characterization • SMR studies • Incidence rate or number of cases of the outcome and person-years for each interval - Are the incidence rates broken out by? (check all that apply) o Interval of time since first exposure (TSFE) o Cumulative exposure o Duration of employment or exposure o Other • Regression analyses - What was the unit of analysis for the regression (i.e., form of the exposure term)? (check all that apply) o Analyzed by intervals of times since first exposure (TSFE) o Analyzed by intervals of cumulative exposure o Analyzed by duration of employment/exposure o Other • Other Page 64 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 2141 Appendix F POPULATIONS, EXPOSURES, COMPARATORS, AND 2142 OUTCOMES (PECO) CRITERIA FOR PART 2 OF THE 2143 RISK EVALUATION FOR ASBESTOS 2144 2145 Table Apx F-l. PECO Criteria for Asbestos Part 2 (Legacy Uses and Associated Disposals) PECO Element Evidence P Human: Any population and lifestage (e.g., occupational or general population, including children and other sensitive populations). Animal: Aquatic and terrestrial species (live, whole organism) from any lifestage (e.g., preconception, in utero, lactation, peripubertal, and adult stages). Animal models will be inventoried according to the categorization below: • Ecotoxicoloaical models: invertebrates (e.g., insects, soidcrs. crustaceans, mollusks. and worms) and vertebrates (e.g., mammals and all amphibians, birds, fish, and reptiles). Plants: All aquatic and terrestrial species (live), including algal, moss, lichen, and fungi species. Screener notes: • All non-human animal (e.g., rodents, rabbits, hens, amphibians, fish, insects) and plant models listed above are relevant as an ecotoxicological model. • PECO considerations should be directed toward effects on target species only and not on the indirect effects expressed in taxa as a result of chemical treatment (e.g., substance is lethal to a targeted pest species leading to positive effects on plant growth due to diminished presence of the targeted pest species). Tests of single toxicants in in vitro and ex vivo systems or on gametes, embryos, or plant or fungal sections capable of forming whole, new organisms will be tagged as potentially supplemental (mechanistic studies). Bacteria and yeast studies specific for assessing genotoxicity or mutagenicity (e.g., Ames assay) will also be tagged as potentially supplemental (mechanistic studies) but are otherwise excluded. Studies on viruses will be excluded. E Relevant forms: Asbestos, as defined by the following fiber types (or mixtures of fiber types): • Asbestos: 1332-21-4 • Chrysotile (serpentine): 12001-29-5 • Crocidolite (riebeckite): 12001-28-4 • Amosite (grunerite): 12172-73-5 • Anthophy llite: 17068-78-9 • Tremolite: 14567-73-8 • Actinolite: 12172-67-7 • Winchite: 12425-92-2 • Richterite: 17068-76-7 • Libby amphibole: 1318-09-8 • Exposure reported as PCM or TEM (including conversion factors for dust) • Talc (or magnesium silicate) contaminated with asbestos For svnonvms see and a list of validated svnonvms on the EPA Chemistrv Dashboard. Human: Any exposure to one or more of the nine asbestos fiber types, singularly or mixed, that meets the following conditions: • Exposure based on quantitative (measured or estimated) concentrations of asbestos, such as exposure biomonitoring data (e.g., lung tissue specimens), environmental or occupational monitoring data (e.g., ambient air levels). This may be combined with estimates of duration of exposure. (Generally, studies with quantitative exposure data are included; however, studies that included a quantitative measurement of exposure but did not use that Page 65 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 PECO Element Evidence E quantitative measurement in the analysis of the association between exposure and outcome are excluded.) • For categorical exposures, a minimum of two exposure groups (referent group + 1) Eco Animal: Anv oral exDosure to one or more of the nine asbestos fiber tvDcs. regardless of the exposure media (e.g., water, diet, soil, sediment), singularly or mixed. All other exposure pathways (e.g., dermal, inhalation, injection) are designated as not meeting screening criteria (please select the correct supplemental tag: apical/mechanistic and the non-oral exposure pathway). For organism exposures to asbestos or PECO-relevant asbestos fibers where oral exposures cannot be discerned from other exposure pathways that are more characteristic of mammalian and avian studies, please select include (e.gfish or invertebrates exposed to asbestos in surface water, sediment, and/or soil. Plants: Any exposure to one or more of the 9 asbestos fiber types, regardless of the exposure media (e.g., water, soil, sediment), singularly or mixed Screener notes: • Field studies with media concentrations (e.g., surface water, interstitial water, soil, sediment) and/or body/tissue concentrations of animals or plants are to be identified as Supplemental if anv biological effects are reported. • Controlled outdoor experimental studies (e.g., controlled crop/greenhouse studies, mesocosm studies, artificial stream studies) are considered to be laboratory studies (not field studies) because there is a known and prescribed exposure dose(s) and an evaluation of hazardous effect(s). Whereas field studies (e.g., biomonitoring) where there is no prescribed exposure dose(s) do not meet screening criteria if there is no evaluated hazardous effect, and tagged as Supplemental field, if there is an evaluated hazardous effect. Papers reporting exposure to "asbestos" generally and not specific fiber type of asbestos will be included for further consideration. C Human: The source meets either of the following conditions: • Contains a comparison or referent population exposed to lower levels (or no exposure/exposure below detection limits) of asbestos, and other relevant forms listed above. Eco Animal and Plants: A concurrent control group exposed to vehicle-only treatment and/or untreated control (control could be a baseline measurement). Screener note: • If no control group is explicitly stated or implied (e.g., by mention of statistical results that could only be obtained if a control group was present), the study will be marked as Unclear during TIAB screening. 0 Human: Health outcomes including cancer (e.g., lung cancer, mesothelioma, laryngeal cancer, ovarian cancer) and all non-cancer endpoints at the organ level (e.g., immune, cardiovascular, respiratory) or higher. Eco Animal and Plants: All apical biological effects (effects measured at the organ level or higher) and bioaccumulation from laboratory studies with concurrently measured media and/or tissue concentrations. Apical endpoints include but are not limited to reproduction, survival, and growth. Screener notes: • For Active Screener only: INCLUDE Supplemental references: mechanistic (including in vitro/in silico studies and studies with genotoxicity/mutagenicity assays in yeast/bactcria): absorption, distribution, metabolism, and excretion (ADME)/physiologically based pharmacokinetic (PBPK)/toxicokinetic; case reports or case series; susceptible populations Page 66 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 PECO Element Evidence (with no health outcome; only at full text screening); mixture studies (tagged separately for human health animal and eco animal/plant studies); non-English records, records with no original data (e.g., reviews, editorials, commentaries, assessments); conference abstracts; field studies. • For citations with no abstract, use the following to screen: title relevance and page numbers (articles two pages in length or less are assumed to be conference reports, editorials, or letters and can be tagged as supplemental material). Reviews that do not suggest a specific focus on the chemical of interest can be excluded rather than marked as supplemental material. 2146 2147 2148 2149 Table Apx F-2. Major Categories of "Potentially Relevant Supplemental Material Category Evidence Mechanistic studies All studies that report results at the cellular level and lower in both mammalian and non-mammalian model systems, including in vitro, in vivo, ex vivo, and in silico studies. These studies include assays for genotoxicity or mutagenicity using bacteria or yeast. ADME, PBPK, and toxicokinetic Studies designed to capture information regarding ADME, toxicokinetic studies, or PBPK models. Case reports, case series, case- case, or case-only study designs Case reports, case series, case-case, and case-only study designs will be tracked as potentially relevant supplemental information. (Does NOT include case-control, case-referent, or case-crossover study designs, which would be PECO includes if they meet criteria). Susceptible populations (no health outcome) Studies that identify potentially susceptible subgroups; for example, studies that focus on a specific demographic, lifestage, or genotype. This tag applies primarily during full text screening. Screener note: • If biological susceptibility issues are clearly present or strongly implied in the title/abstract, this supplemental tag may be applied at the title/abstract level. If uncertain at title/abstract, do not apply this tag to the reference during title/abstract screening. Non-English records Non-English records will be tracked as potentially relevant supplemental information. Records with no original data Records that do not contain original data, such as other agency assessments, informative scientific literature reviews, editorials, or commentaries. Conference abstracts Records that do not contain sufficient documentation to support study evaluation and data extraction. Field Studies Field studies with media concentrations (e.g., surface water, interstitial water, soil, sediment) and/or body/tissue concentrations of animals or plants if biological effects reported Other relevant structures If another asbestos fiber type or talc/magnesium silicate are mentioned with resulting biological effects reported. However, please exclude synthetic magnesium silicate (lab-synthesized and thus, not asbestos-relevant) or synthetic magnesium silicate-products. Page 67 of 102 ------- 2150 2151 2152 2153 2154 2155 2156 2157 2158 2159 2160 PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Appendix G DATA QUALITY EVALUATION CRITERIA As described above in Appendix Section B.3, data quality evaluation forms originally used in Part 1 of the Risk Evaluation for Asbestos were updated and used to evaluate references containing epidemiological data for Part 2. In short, the mesothelioma data quality evaluation form used in Part 1, with updates based on calibration, was used for mesothelioma studies in Part 2. The lung cancer data quality evaluation form from Part 1 was modified to include considerations of other cancer and non- cancer outcomes for Part 2. Additional description of the updates to the data quality evaluation forms will be provided in the forthcoming Draft Risk Evaluation for Asbestos Part 2: Supplemental Evaluation including Legacy Uses and Associated Disposals of Asbestos - Systematic Review Protocol. Table Apx G-l. Mesothelioma Criteria Data Quality Rating Description Domain 1. Studv Participation Metric 1. Participant Selection (selection, performance biases) High For all studv tvves: - All key elements of the study design are reported (e.g., setting, participation rate described at all steps of the study, inclusion and exclusion criteria, and methods of participant selection or case ascertainment) AND - The reported information indicates that participant selection in or out of the study (or analysis sample) and participation was not likely to be biased {i.e., the exposure-outcome distribution of the participants is likely representative of the exposure-outcome distributions in the population of persons eligible for inclusion in the study.) Medium For all studv tvves: - Some key elements of the study design were not present but available information indicates a low risk of selection bias (/'. e., the exposure-outcome distribution of the participants is likely representative of the exposure-outcome distributions in the population of persons eligible for inclusion in the study.) Low For all studv tvves: - Key elements of the study design and information on the population (e.g., setting, participation rate described at most steps of the study, inclusion and exclusion criteria, and methods of participant selection or case ascertainment) are not reported (STROBE checklist 4. 5 and 6 (Von Elm et al.. 2008)). -If the study provides little to no information about selection criteria, then rate this metric as Low. Critically Deficient For all studv tvves: The reported information indicates that selection in or out of the study (or analysis sample) and participation was likely to be significantly biased (/'. e., the exposure-outcome distribution of the participants is likely not representative of the exposure-outcome distributions of the population of persons eligible for inclusion in the study). Not Rated/Not Applicable - Do not select for this metric. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Page 68 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Metric 2. Attrition (missing data/attrition/exclusion, reporting biases) High For cohort studies: - There was minimal subject loss to follow up during the study (or exclusion from the analysis sample) and outcome and exposure data were largely complete. OR - Any loss of subjects (i.e., incomplete outcome data) or missing exposure and outcome data were adequately* addressed (as described below) and reasons were documented when human subjects were removed from a study (NTP. 2015). OR - Missing data have been imputed using appropriate methods (e.g., multiple imputation methods), and characteristics of subjects lost to follow up or with unavailable records are not significantly different from those of the study participants (NTP. 2015). For case-control studies and cross-sectional studies: - There was minimal subject withdrawal from the study (or exclusion from the analysis sample) and outcome data and exposure were largely complete. OR - Any exclusion of subjects from analyses was adequately* addressed (as described below), and reasons were documented when subjects were removed from the study or excluded from analyses (NTP. 2015). *NOTE for all study types: Adequate handling of subject attrition can include: Use of imputation methods for missing outcome and exposure data; reasons for missing subjects unlikely to be related to outcome (for survival data, censoring was unlikely to introduce bias); missing outcome data balanced in numbers across study groups, with similar reasons for missing data across groups. Medium For cohort studies: - There was moderate subject loss to follow up during the study (or exclusion from the analysis sample) or outcome and exposure data were nearly complete. AND - Any loss or exclusion of subjects was adequately addressed (as described in the acceptable handling of subject attrition in the high confidence category) and reasons were documented when human subjects were removed from a study. For case-control studies and cross-sectional studies: - There was moderate subject withdrawal from the study (or exclusion from the analysis sample), but outcome and exposure data were largely complete AND - Any exclusion of subjects from analyses was adequately addressed (as described above), and reasons were documented when subjects were removed from the study or excluded from analyses (NTP. 2015). Page 69 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Low For cohort studies: - The loss of subjects (e.g., loss to follow up, incomplete outcome or exposure data) was moderate and unacceptably handled (as described below in the unacceptable confidence category) (Source: OHAT). OR - Numbers of individuals were not reported at important stages of study (e.g., numbers of eligible participants included in the study or analysis sample, completing follow-up, and analyzed). Reasons were not provided for non-participation at each stage (STROBE Checklist Item 13 (Von Elm et al.. 2008)). For case-control and cross-sectional studies: - The exclusion of subjects from analyses was moderate and unacceptably handled (as described below in the unacceptable confidence category). OR - Numbers of individuals were not reported at important stages of study (e.g., numbers of eligible participants included in the study or analysis sample, completing follow-up, and analyzed). Reasons were not provided for non-participation at each stage (STROBE Checklist Item 13 (Von Elm et al., 2008)). Critically Deficient For cohort studies: - There was large subject attrition during the study (or exclusion from the analysis sample). OR - Unacceptable handling of subject attrition: reason for missing outcome data likely to be related to true outcome, with either imbalance in numbers or reasons for missing data across study groups; or potentially inappropriate application of imputation (Source: OHAT). For case-control and cross-sectional studies: - There was large subject withdrawal from the study (or exclusion from the analysis sample). OR - Unacceptable handling of subject attrition: reason for missing outcome data likely to be related to true outcome, with either imbalance in numbers or reasons for missing data across study groups; or potentially inappropriate application of imputation. Not Rated/Not Applicable - Do not select for this metric. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Page 70 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Metric 3. Comparison Group (selection, performance biases) High For ALL stuclv tvves: - Any differences in baseline characteristics of groups were considered as potential confounding or stratification variables and were thereby controlled by statistical analysis (Source: OHAT). OR For cohort and cross-sectional studies: - Key elements of the study design are reported {i.e., setting, inclusion and exclusion criteria, and methods of participant selection), and indicate that subjects were similar (e.g., recruited from the same eligible population with the same method of ascertainment and within the same time frame using the same inclusion and exclusion criteria, and were of similar aae and health status) (NTP. 2015). For case-control studies: - Key elements of the study design are reported indicate that that cases and controls were similar (e.g., recruited from the same eligible population with the number of controls described, and eligibility criteria and are recruited within the same time frame (NTP. 2015). For studies revortins Standardized Mortality Ratios (SMRs) or Standardized Incidence Ratios (SLRs): - Age, sex (if applicable), and race (if applicable) adjustment or stratification is described and choice of reference population (e.g., general population) is reported. Medium For cohort studies and cross-sectional studies: - There is only indirect evidence (e.g., stated by the authors without providing a description of methods) that groups are similar (as described above for the high confidence rating). OR - If there is potential for healthy worker effect. For case-control studies: - There is indirect evidence (i.e., stated by the authors without providing a description of methods) that cases and controls are similar (as described above for the high confidence rating). For studies revortins SMRs or SLRs: - Age, sex (if applicable), and race (if applicable) adjustment or stratification is not specifically described in the text, but results tables are stratified by age and/or sex (i.e., indirect evidence); choice of reference population (e.g., general population) is reported. Low For cohort and cross-sectional studies: - There is indirect evidence (i.e., stated by the authors without providing a description of methods) that groups were not similar (as described above for the high confidence rating). AND - Differences between the exposure groups are not adequately controlled for in the statistical analysis. For case-control studies: Page 71 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description - There is indirect evidence {i.e., stated by the authors without providing a description of methods) that cases and controls were not similar (as described above for the high confidence rating). AND - The characteristics of cases and controls are not reported (NTP. 2015). AND - Differences in groups is not adequately controlled for in the statistical analysis. For studies revortins SMRs or SIRs: - Indirect evidence of a lack of adjustment or stratification for age or sex (if applicable); indirect evidence that choice of reference population (e.g., general population) is inappropriate. Critically Deficient For cohort studies: - Subjects in all exposure groups were not similar. OR - Information was not reported to determine if participants in all exposure groups were similar (STROBE Checklist 6 (Von Elm et al.. 2008)). AND - Potential differences in exposure groups were for a factor that was related to the outcome and not controlled for in the statistical analysis. OR - Subjects in the exposure erouos had verv different participation/response rates (NTP. 2015). AND - Participation rates were related to exposure and outcome For case-control studies: -Controls were drawn from a very dissimilar population than cases or recruited within verv different time frames (NTP. 2015). AND -Potential differences in the case and control groups were not controlled for in the statistical analysis. OR - Rationale and/or methods for case and control selection, matching criteria including number of controls per case (if relevant) were not reported (STROBE Checklist 6 (Von Elm et al.. 2008)). For cross-sectional studies: - Subjects in all exposure groups were not similar, recruited within very different time frames, or had verv different participation/response rates (NTP. 2015). AND - Potential differences in exposure groups were not controlled for in the statistical analysis. OR - Sources and methods of selection of participants in all exposure groups were not reported (STROBE Checklist Item 13 (Von Elm et al.. 2008)). For studies revortins SMRs or SIRs: - Lack of adjustment or stratification for both age and sex (if applicable), race (if applicable), and calendar time or choice of reference population (e.g., general population) is not reported. Page 72 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Not Rated/Not Applicable - For mesothelioma studies, a comparison population is not required, as EPA's interest is in the absolute risk and not the relative risk. All studies of mesothelioma allowing for evaluation of absolute risk should be labeled as "Not rated/not applicable" -Only rate as NA if there is no mesothelioma comparison group. Otherwise, if the study includes a comparison group, rate this metric H, M, L, or U. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Domain 2. Exposure Characterization Metric 4. Measurement of Exposure (detection/measurement/information, performance biases) High For all stuclv tvpes: - Quantitative estimates of exposure were consistently assessed (i.e., using the same method and sampling timeframe) during multiple time periods and using either PCM or TEM. OR - A combination of methods were used over time (i.e., midget impinger, PCM or TEM), but side by side sampling and analyses were conducted to develop appropriate conversion criteria. AND - For an occupational population, contains detailed employment records and quantitative estimates of exposure using either PCM or TEM which allows for construction of job- matrix for entire work history of exposure (i.e.. Cumulative or peak exposures, and time since first exposure). Medium For all stuclv tvpes: - (Exposure was assessed during one time period but this time period is judged to be reasonably representative of the entire study time period. AND - Exposure was assessed using a combination of midget impingers, PCM, and/or TEM measurements, but side by side sampling and analyses were not conducted for all operations and thus there is a lack of confidence in the conversion factors.) OR - For an occupational study population, contains detailed employment records and quantitative estimates of exposure using a combination of midget impingers and PCM or TEM measurements for only a portion of participant's work history of exposure (i.e., only early years or later years), such that extrapolation of the missing years is required. Low For all stuclv tvpes: -Exposure was estimated solely using professional judgement. OR -The method of quantifying/counting fibers was not specified. OR - Exposure was directly measured (e.g., midget impinger) and assessed using a quantitative method other than PCM or TEM and conversion factors were not determined. Page 73 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Critically Deficient For all study types: - Methods used to quantify the exposure were not well defined, and sources of data and detailed methods of exposure assessment were not reported (STROBE Checklist 7 and 8 (Von ElmetaL 2008)). OR - There was no quantitative measure or estimate of exposure. OR - There is evidence of substantial exposure misclassification that would significantly bias the results. Not Rated/Not Applicable - Do not select for this metric. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 5. Exposure Levels (detection/measurement/information biases) High - Do not select for this metric Medium For all study types: - The range and distribution of exposure is sufficient or adequate to develop an exposure- response estimate (CooDer et al.. 2016). Low For all study types: - The range of exposure in the population is limited Critically Deficient For all studv tvpes: - The range and distribution of exposure are not adequate to determine an exposure- response relationship (Cooper et al.. 2016). OR - No description is provided on the levels or range of exposure. Not Rated/Not Applicable - Do not select for this metric. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 6. Temporalitv High For all studv tvpes: - The study presents an appropriate temporality between exposure and outcome (i.e., the exposure precedes the disease). AND - The interval between the exposure (or reconstructed exposure) and the outcome is sufficiently long considering the latency of the disease (i.e.. study follow-up is more than 20 vears for mesothelioma) (LaKind et al.. 2014). Medium For all studv tvpes except cross-sectional studies: - Temporality is established, but it is unclear whether there is adequate follow-up for consideration of latencv (i.e.. onlv 15-20 vears of follow-up) (LaKind et al.. 2014). Low For all studv tvpes: - The temporality of exposure and outcome is uncertain (10-15 years). OR - There is inadequate follow-up of the cohort considering the latency period. Page 74 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Critically Deficient For all study types: - Study lacks an established time order, such that exposure is not likely to have occurred priorto outcome (LaKind et al.. 2014). OR - There was inadequate follow-up of the cohort for the expected latency period (<10 years). OR - Sources of data and details of methods of assessment were not sufficiently reported (e.g., duration of follow-up, periods of exposure, dates of outcome ascertainment, etc.) (Source: STROBE Checklist 8 (Von Elm et al.. 2008)). Not Rated/Not Applicable - Do not select for this metric. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Domain 3. Outcome Assessment Metric 7. Outcome Measurement or Characterization (detection/measurement/information, performance, reporting biases) High For all study types: The outcome was assessed using one or a combination of the following well-established methods: - Mesothelioma cases confirmed by histological or cytological means (including subtypes of mesothelioma) and/or - ICD-10 codes (3-digit) C45 or (4-digit) C45.x (C45.0, C45.1, C45.2, C45.7, C45.9) - All fields on the death certificates of cohort searched for 'mesothelioma" - Appropriate Pre-ICD 10 codes supplemented by additional evidence (e.g., patholoav/autopsv) see Table 1 of (Kopvlev et al.. 2011) - International Classification of Diseases for Oncology Third Edition (ICD-O-3) and Second Edition (ICD-O-2) codes are acceptable because ICD-O-3 and ICD-O-2 include mesothelioma-specific codes. - ICD-O-3 and ICD-O-2 codes 9050-9055 (note if designated as benign or malignant) are acceptable. Medium For all study types: - Examined death certificates searched for mesothelioma for pre-ICD-10 codes that include pleura, peritoneum and site unspecified (ICD code 199) Low - Do not select for this metric. Critically Deficient For all studv tvpes: - Numbers of outcome events or summary measures were not reported (Source: STROBE Checklist 15 (Von Elm et al.. 2008) OR - Only pre ICD-10 codes (without additional information) were used for ascertainment of mesothelioma. OR - Examined death certificates searched for mesothelioma for codes that included only pleura and/or peritoneum OR - Study lacks individual assessment of mesothelioma (i.e, mesothelioma is assessed as a combination with other cancer types, excluding lung and bronchus or trachea) OR - Any self-reported information Page 75 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Not Rated/Not Applicable - Do not select for this metric. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 8. Reporting Bias High For all stuclv tvves: - Mesothelioma findings are reported in the abstract, results or discussion. Effect estimates are reported with confidence intervals and/or standard errors, number of cases/controls or exposed/unexposed reported for each analysis, to be included in exposure-response analysis or fullv tabulated during data extraction and analvses (NTP. 2015). Medium For all stuclv tvves: - All of the study's findings (primary and secondary) outlined in the abstract, results or discussion (that are relevant for the evaluation) are reported but not in a way that would allow for detailed extraction (e.g., results were discussed in the text but accompanying data were not shown). Low For all stuclv tvves: - Mesothelioma outcomes outlined in the methods, abstract, and/or introduction (that are relevant for the evaluation) have not been reported (NTP. 2015). Critically Deficient - Do not select for this metric. Not Rated/Not Applicable - Do not select for this metric. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Domain 4. Potential Confounding/Variability Control'1 Metric 9. Covariate Adjustment (confounding) High For all stuclv tvves: - Appropriate adjustments or explicit considerations were made for potential confounders (e.g., age, sex, SES, race, etc.) (excluding co-exposures, which are evaluated in metric 11) in the final analyses through the use of statistical models to reduce research-specific bias, including matching, adjustment in multivariate models, stratification, or other methods that were appropriately justified (NTP. 2015). For studies revortins SMRs or SIRs: - Adjustments are described and results are age-, race-, and sex-adjusted (or stratified) if applicable. Page 76 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Medium For all study types: - There is indirect evidence that appropriate adjustments were made (i.e., considerations were made for primary covariates (excluding co-exposures) and potential confounders adjustment) without providing a description of methods. OR - The distribution of potential confounders (excluding co-exposures) did not differ significantly between exposure groups or between cases and controls. OR - The major potential confounders (excluding co-exposures) were appropriately adjusted and any not adjusted for are considered not to appreciably bias the results (e.g., smoking rates in an occupational cohort are expected to be generally similar in different departments and thus confounding by smoking is unlikely when internal analyses are applied). For studies reporting SMRs or SIRs: - Results are adjusted (or stratified) for age and sex, unless adjustment or stratification is not necessary because the exposed and control groups are sufficiently similar on the particular demographic variable. Low For all study types: - There is indirect evidence (i.e., no description is provided in the study) that considerations were not made for potential confounders adjustment in the final analyses (NTP. 2015). AND - The distribution of primary covariates (excluding co-exposures) and potential confounders was not reported between the exposure groups or between cases and controls (NTP. 2015). For studies reportins SMRs or SIRs: - Results are adjusted or stratified for age, race, OR sex (any one of the three), unless adjustment or stratification is not necessary because the exposed and control groups are sufficiently similar on the particular demographic variable. Critically Deficient For all study types: - The distribution of potential confounders differed significantly between the exposure groups. AND - Confounding was demonstrated and was not appropriately adjusted for in the final analyses (NTP. 2015). For studies reportins SMRs or SIRs: - No discussion of adjustments. Results are not adjusted for both age and sex (or stratified) if applicable. Not Rated/Not Applicable - Rate this metric as "N/A" if no analyses of the association between exposure and outcome were performed or if there are no potential confounders. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Page 77 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Metric 10. Covariate Characterization (measurement/information, confounding biases) For occupational studies, it can be assumed that personnel records were used to obtain covariate data if not otherwise specified. High For all stuclv tvpes: - Potential confounders (excluding co-exposures; e.g., age, sex, SES) were assessed using valid and reliable methodology where appropriate (e.g., validated questionnaires, biomarker). Medium For all stuclv tvpes: - A less-established method was used to assess confounders (excluding co-exposures) and no method validation was conducted against well-established methods, but there was little to no evidence that that the method had poor validity and little to no evidence of confounding. Low For all stuclv tvpes: - The confounder assessment method is an insensitive instrument or measure or a method of unknown validity. Critically Deficient For all stuclv tvpes: - Confounders were assessed using a method or instrument known to be invalid. Not Rated/Not For all study types: Applicable - Covariates were not assessed. OR - Metric 9 is rated "Not applicable" Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 11. Co-exposure Reliability (measurement/information, confounding biases) High - Do not select for this metric. Medium For all stuclv tvpes: - Any co-exposures to pollutants that are not the target exposure that would likely bias the results were not likely to be present. OR - Co-exposures to pollutants were appropriately measured or either directly or indirectly adjusted for. - Example: There is confirmation of the likely absence of known co-exposures via mechanisms such as engineering controls (closed systems) for co-pollutants or confirmation of the absence of co-pollutants through monitoring. Low For cohort ancl cross-sectional studies: - There is direct evidence that there was an unbalanced provision of additional co- exposures across the primary study groups, which were not appropriately adjusted for. For case-control studies: - There is direct evidence that there was an unbalanced provision of additional co- exposures across cases and controls, which were not appropriately adjusted for, and significant indication a biased exposure-outcome association. OR For all study types: In an occupational setting, potential co-exposures are not discussed. Critically Deficient - Do not select for this metric. Page 78 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Not Rated/Not Applicable - For mesothelioma studies, evaluations of potential confounders are not required as there are few other causes of mesothelioma (zeolites, viruses, therapeutic or diagnostic radiation) and none that are likely to be correlated in a dose-dependent manner with asbestos. Evaluation of potential confounding in mesothelioma studies should be labeled as "Not rated/applicable" unless there is substantial information to indicate otherwise. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Domain 5. Analysis Metric 12. Studv Desian and Methods High - Do not select for this metric. Medium For all study types: - The study design chosen was appropriate for the research question. OR - The study uses an appropriate statistical method to address the research question(s) (e.g., Cox and Poisson regression for cohort studies and logistic regression analysis for case- control studies. Low - Do not select for this metric. Critically Deficient For all study types: - The study design chosen was not appropriate for the research question. Not Rated/Not Applicable - Do not select for this metric. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 13. Statistical Power (sensitivity) High - Do not select for this metric. Medium For cohort and cross-sectional studies: - The number of participants are adequate to detect an effect in the exposed population and/or subgroups of the total population. OR - The paper reported statistical power is high enough (> 80%) to detect an effect in the exposure population and/or subgroups of the total population. For case-control studies: - The number of cases and controls are adequate to detect an effect in the exposed population and/or subgroups of the total population. OR - The paper reported statistical power is high enough (> 80%) to detect an effect in the exposure population and/or subgroups of the total population. Low - Do not select for this metric. Critically Deficient For cohort and cross-sectional studies: - The number of participants is inadequate to detect an effect in the exposed population and/or subgroups of the total population and the study was negative. For case-control studies: - The number of cases and controls are inadequate to detect an effect in the exposed population and/or subgroups of the total population and the study was negative. Page 79 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Not Rated/Not Applicable - For mesothelioma, EPA is primarily interested in the presentation of data collected in the study, rather than the statistical analysis. EPA will pool data across asbestos studies to conduct for the analysis of mesothelioma risk. Therefore, the power of individual studies will not be considered. This metric may be marked as not rated/applicable. - Mark as NA if there were no statistical analyses or models for mesothelioma. If no analyses were performed because (whether stated or implied) there wasn't sufficient statistical power to do analyses, be sure to note this in the comments. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 14. Reproducibility of Analyses (adapted from Blettner et al. (2001)) High - Do not select for this metric. Medium For all stuclv tvves: - The description of the analysis is sufficient to understand how to conceptually reproduce the analysis with access to the analytic data. Low or all stuclv tvves: - The description of the analysis is insufficient to understand what has been done and to be reproducible OR a description of analyses are not present (e.g., statistical tests and estimation procedures were not described, variables used in the analysis were not listed, transformations of continuous variables (e.g., logarithmic) were not explained, rules for categorization of continuous variables were not presented, exclusion of outliers was not elucidated and how missing values are dealt with was not mentioned). Critically Deficient - Do not select for this metric. Not Rated/Not Applicable - For mesothelioma, EPA is primarily interested in the presentation of data collected in the study, rather than the statistical analysis. If individual data elements (e.g., time since first exposure, number of person-years, etc.) are present in the study that will allow EPA to conduct its own analysis, this metric may be marked as not rated/applicable. - Mark as NA if there were no statistical analyses or models for mesothelioma. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 15. Statistical Models (confounding bias) High - Do not select for this metric. Medium For all stuclv tvves: - The model or method for calculating the risk estimates (e.g., odds ratios, SMRs, SIR) is transparent (i.e., it is stated how/why variables were included or excluded). Low For all stuclv tvves: - The statistical model building process is not fully appropriate OR model assumptions were not met OR a description of analyses and assumptions are not present (STROBE Checklist 12e (Von Elm et al., 2008)). Critically Deficient - Do not select for this metric. Not Rated/Not Applicable - For mesothelioma, EPA is primarily interested in the presentation of data collected in the study, rather than the statistical analysis. If individual data elements (e.g., time since first exposure, number of person-years, etc.) are present in the study that will allow EPA to conduct its own analysis, this metric may be marked as not rated/applicable. - Mark as NA if there were no statistical analyses or models for mesothelioma. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Page 80 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Domain 6. Other (if applicable) Considerations for Biomarker Selection and Measurement (LaKind et al.. 2014) Metric 16. Use of Biomarker of Exposure (detection/measurement/information biases) High - Biomarker in a specified matrix has accurate and precise quantitative relationship with external exposure, internal dose, or target dose. AND - Biomarker is derived from exposure to one parent chemical. Medium - Biomarker in a specified matrix has accurate and precise quantitative relationship with external exposure, internal dose, or target dose. AND - Biomarker is derived from multiple parent chemicals. Low - Evidence exists for a relationship between biomarker in a specified matrix and external exposure, internal dose or target dose, but there has been no assessment of accuracy and precision or none was reported. Critically Deficient - Biomarker in a specified matrix is a poor surrogate (low accuracy, specificity, and precision) for exposure/dose. Not Rated/Not Applicable - Select "N/A" if no human biological samples were assessed or if the only biomarkers assessed were biomarkers of effect or biomarkers of susceptibility. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 17. Effect Biomarker (detection/measurement/information biases) High - Effect biomarker measured is an indicator of a key event in an adverse outcome pathway (AOP). Medium - Biomarkers of effect shown to have a relationship to health outcomes using well validated methods, but the mechanism of action is not understood. Low - Biomarkers of effect shown to have a relationship to health outcomes, but the method is not well validated and mechanism of action is not understood. Critically Deficient - Biomarker has undetermined consequences (e.g., biomarker is not specific to a health outcome). Not Rated/Not Applicable - Select "N/A" if no human biological samples were assessed or if the only biomarkers assessed were biomarkers of exposure or biomarkers of susceptibility. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 18. Method Sensitivitv (detection/measurement/information biases) High - Do not select for this metric. Medium - Limits of detection are low enough to detect chemicals in a sufficient percentage of the samples to address the research question. Analytical methods measuring biomarker are adequately reported. The limit of detection (LOD) and limit of quantification (LOQ) (value or %) are reported. Low - Frequency of detection too low to address the research hypothesis. OR - LOD/LOQ (value or %) are not stated. Critically Deficient - Do not select for this metric. Not Rated/Not Applicable - Do not select "N/A" for this metric if the study assessed biomarkers. If LOD/LOQ are not stated then select Low. Page 81 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 19. Biomarker Stability (detection/measurement/information biases) High - Samples with a known storage history and documented stability data or those using real- time measurements. Medium - Samples have known losses during storage, but the difference between low and high exposures can be qualitatively assessed. Low - Samples with either unknown storage history and/or no stability data for target analytes and high likelihood of instability for the biomarker under consideration. Critically Deficient - Do not select for this metric. Not Rated/Not Applicable - Do not select "N/A" for this metric if the study assessed biomarkers. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 20. Sample Contamination (detection/measurement/information biases) High - Samples are contamination-free from the time of collection to the time of measurement (e.g., by use of certified analyte free collection supplies and reference materials, and appropriate use of blanks both in the field and lab). AND - Documentation of the steps taken to provide the necessary assurance that the study data are reliable is included. Medium - Samples are stated to be contamination-free from the time of collection to the time of measurement. AND - There is incomplete documentation of the steps taken to provide the necessary assurance that the study data are reliable. OR - Samples are known to have contamination issues, but steps have been taken to address and correct contamination issues. OR - There is no information included about contamination (only allowed for biomarker samples not susceptible to contamination). Low - Samples are known to have contamination issues, but steps have been taken to address and correct contamination issues. OR - Samples are stated to be contamination-free from the time of collection to the time of measurement, but there is no use or documentation of the steps taken to provide the necessary assurance that the study data are reliable. Critically Deficient - There are known contamination issues (e.g., phthalate study that used plastic sample collection vials) and no documentation that the issues were addressed. Not Rated/Not Applicable - Do not select "N/A" for this metric if the study assessed biomarkers. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Page 82 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Metric 21. Method Requirements (detection/measurement/information biases) High - Instrumentation that provides unambiguous identification and quantitation of the biomarker at the required sensitivity (e.g., gas chromatography/high-resolution mass spectrometry [GC-HRMS]; gas chromatography with tandem mass spectrometry [GC- MS/MS]; liquid chromatography with tandem mass spectrometry [LC-MS/MS]). Medium - Instrumentation that allows for identification of the biomarker with a high degree of confidence and the required sensitivity (e.g., gas chromatography mass spectrometry [GC-MS], gas chromatography with electron capture detector [GC-ECD]). Low - Instrumentation that only allows for possible quantification of the biomarker, but the method has known interferants (e.g., gas chromatography with flame-ionization detection [GC-FID], spectroscopy). Critically Deficient - Do not select for this metric. Not Rated/Not Applicable - Do not select "N/A" for this metric if the study assessed biomarkers. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 22. Matrix Adjustment (detection/measurement/information biases) High - If applicable for the biomarker under consideration, study provides results, either in the main publication or as a supplement, for both adjusted and unadjusted matrix concentrations (e.g., creatinine-adjusted or specific gravity-adjusted and non-adjusted urine concentrations) and reasons are given for adjustment approach. Medium - If applicable for the biomarker under consideration, study only provides results using one method (matrix-adjusted or not). Low - If applicable for the biomarker under consideration, no established method for matrix adjustment was conducted. Critically Deficient - Do not select for this metric. Not Rated/Not Applicable - If metrics 16 and 17 are both NA, then the remaining biomarker metrics are automatically not rated. Otherwise: Select ""N/A" if matrix adjustment is not required for assessment of the biomarker. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. 2161 2162 2163 Table Apx G-2. Other Outcomes Data Quality Evaluation Criteria Data Quality Rating Description Domain 1. Studv Participation Metric 1. Participant Selection (selection, performance biases) High For all studv tvpes: - All key elements of the study design are reported (e.g., setting, participation rate described at all steps of the study, inclusion and exclusion criteria, and methods of participant selection or case ascertainment) AND - The reported information indicates that participant selection in or out of the study (or analysis sample) and participation was not likely to be biased (i.e., the exposure- outcome distribution of the participants is likely representative of the exposure-outcome distributions in the population of persons eligible for inclusion in the study.) Page 83 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Medium For all study types: - Some key elements of the study design were not present but available information indicates a low risk of selection bias (/'. e., the exposure-outcome distribution of the participants is likely representative of the exposure-outcome distributions in the population of persons eligible for inclusion in the study.) Low For all study types: - Key elements of the study design and information on the population (e.g., setting, participation rate described at most steps of the study, inclusion and exclusion criteria, and methods of participant selection or case ascertainment) are not reported (STROBE Checklist 4. 5. and 6 (Von Elm et al.. 2008)). - If the study provides little to no information about selection criteria, then rate this metric as Low. Critically Deficient For all study types: The reported information indicates that selection in or out of the study (or analysis sample) and participation was likely to be significantly biased (/'. e., the exposure- outcome distribution of the participants is likely not representative of the exposure- outcome distributions of the population of persons eligible for inclusion in the study). Not Rated/Not Applicable - Do not select for this metric. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 2. Attrition (missing data/attrition/exclusion, reporting biases) High For cohort studies: - There was minimal subject loss to follow up during the study (or exclusion from the analysis sample) and outcome and exposure data were largely complete. OR - Any loss of subjects (i.e.. incomplete outcome data) or missing exposure and outcome data were adequately* addressed (as described below) and reasons were documented when human subjects were removed from a studv (NTP. 2015). OR - Missing data have been imputed using appropriate methods (e.g., multiple imputation methods), and characteristics of subjects lost to follow up or with unavailable records are not sianificantlv different from those of the studv participants (NTP. 2015). For case-control studies and cross-sectional studies: - There was minimal subject withdrawal from the study (or exclusion from the analysis sample) and outcome data and exposure were largely complete. OR - Any exclusion of subjects from analyses was adequately* addressed (as described below), and reasons were documented when subjects were removed from the study or excluded from analvses (NTP. 2015). *NOTE for all study types: Adequate handling of subject attrition can include: Use of imputation methods for missing outcome and exposure data; reasons for missing subjects unlikely to be related to outcome (for survival data, censoring was unlikely to introduce bias); missing outcome data balanced in numbers across study groups, with similar reasons for missing data across groups. Medium For cohort studies: - There was moderate subject loss to follow up during the study (or exclusion from the analysis sample) or outcome and exposure data were nearly complete. Page 84 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description AND - Any loss or exclusion of subjects was adequately addressed (as described in the acceptable handling of subject attrition in the high confidence category) and reasons were documented when human subjects were removed from a study. For case-control studies and cross-sectional studies: - There was moderate subject withdrawal from the study (or exclusion from the analysis sample), but outcome and exposure data were largely complete AND - Any exclusion of subjects from analyses was adequately addressed (as described above), and reasons were documented when subjects were removed from the study or excluded from analvses (NTP. 2015). Low For cohort studies: - The loss of subjects (e.g., loss to follow up, incomplete outcome or exposure data) was moderate and unacceptably handled (as described below in the unacceptable confidence category) (Source: OHAT). OR - Numbers of individuals were not reported at important stages of study (e.g., numbers of eligible participants included in the study or analysis sample, completing follow-up, and analyzed). Reasons were not provided for non-participation at each stage (STROBE Checklist Item 13 (Von Elm et al.. 2008)). For case-control and cross-sectional studies: - The exclusion of subjects from analyses was moderate and unacceptably handled (as described below in the unacceptable confidence category). OR - Numbers of individuals were not reported at important stages of study (e.g., numbers of eligible participants included in the study or analysis sample, completing follow-up, and analyzed). Reasons were not provided for non-participation at each stage (STROBE Checklist Item 13 (Von Elm et al.. 2008)). Critically Deficient For cohort studies: There was larae subject attrition during the studv (or exclusion from the analysis sample). OR - Unacceptable handling of subject attrition: reason for missing outcome data likely to be related to true outcome, with either imbalance in numbers or reasons for missing data across study groups; or potentially inappropriate application of imputation (Source: OHAT). For case-control and cross-sectional studies: - There was large subject withdrawal from the study (or exclusion from the analysis sample). OR - Unacceptable handling of subject attrition: reason for missing outcome data likely to be related to true outcome, with either imbalance in numbers or reasons for missing data across study groups; or potentially inappropriate application of imputation. Not Rated/Not Applicable - Do not select for this metric. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Page 85 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Metric 3. Comparison Group (selection, performance biases) High For ALL study tvves: - Any differences in baseline characteristics of groups were considered as potential confounding or stratification variables and were thereby controlled by statistical analysis (Source: OHAT). OR For cohort and cross-sectional studies: - Key elements of the study design are reported {i.e., setting, inclusion and exclusion criteria, and methods of participant selection), and indicate that subjects were similar (e.g., recruited from the same eligible population with the same method of ascertainment and within the same time frame using the same inclusion and exclusion criteria, and were of similar age and health status) (NTP. 2015). For case-control studies: - Key elements of the study design are reported indicate that that cases and controls were similar (e.g., recruited from the same eligible population with the number of controls described, and eliaibilitv criteria and are recruited within the same time frame (NTP. 2015). For studies revortins SMRs or SLRs: - Age, sex (if applicable), and race (if applicable) adjustment or stratification is described and choice of reference population (e.g., general population) is reported. Medium -If there is substantial potential for healthy worker effect. OR For cohort studies and cross-sectional studies: - There is only indirect evidence (e.g., stated by the authors without providing a description of methods) that groups are similar (as described above for the high confidence rating). For case-control studies: - There is indirect evidence (i.e., stated by the authors without providing a description of methods) that cases and controls are similar (as described above for the high confidence rating). For studies revortins SMRs or SLRs: - Age, sex (if applicable), and race (if applicable) adjustment or stratification is not specifically described in the text, but results tables are stratified by age and/or sex (i.e., indirect evidence); choice of reference population (e.g., general population) is reported. Page 86 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Low For cohort and cross-sectional studies: - There is indirect evidence (i.e., stated by the authors without providing a description of methods) that groups were not similar (as described above for the high confidence rating). AND - Differences between the exposure groups are not adequately controlled for in the statistical analysis. For case-control studies: - There is indirect evidence {i.e., stated by the authors without providing a description of methods) that cases and controls were not similar (as described above for the high confidence rating). AND - The characteristics of cases and controls are not reported (NTP. 2015). AND - Differences in groups is not adequately controlled for in the statistical analysis. For studies revortins SMRs or SIRs: - Indirect evidence of a lack of adjustment or stratification for age or sex (if applicable); indirect evidence that choice of reference population (e.g., general population) is inappropriate. Critically Deficient For cohort studies: - Subjects in all exposure groups were not similar. OR - Information was not reported to determine if participants in all exposure groups were similar (STROBE Checklist 6 (Von Elm et al.. 2008)). AND - Potential differences in exposure groups were for a factor that was related to the outcome and not controlled for in the statistical analysis. OR - Subjects in the exposure aroups had verv different participation/response rates (NTP. 2015). AND - Participation rates were related to exposure and outcome For case-control studies: -Controls were drawn from a very dissimilar population than cases or recruited within verv different time frames (NTP. 2015). AND -Potential differences in the case and control groups were not controlled for in the statistical analysis. OR - Rationale and/or methods for case and control selection, matching criteria including number of controls per case (if relevant) were not reported (STROBE Checklist 6 (Von Elm et al.. 2008)). For cross-sectional studies: - Subjects in all exposure groups were not similar, recruited within very different time frames, or had verv different participation/response rates (NTP. 2015). AND - Potential differences in exposure groups were not controlled for in the statistical analysis. Page 87 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description OR - Sources and methods of selection of participants in all exposure groups were not reported (STROBE Checklist 6 (Von Elm et al.. 2008)). For studies reporting SMRs or SIRs: - Lack of adjustment or stratification for both age and sex (if applicable), race (if applicable), and calendar time or choice of reference population (e.g., general population) is not reported. Not Rated/Not Applicable - Do not select for this metric. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Domain 2. Exposure Characterization Metric 4. Measurement of Exposure (detection/measurement/information, performance biases) High For all stuclv tvpes: - Quantitative estimates of exposure were consistently assessed (i.e., using the same method and sampling timeframe) during multiple time periods and using either PCM or TEM. OR - A combination of methods were used over time (i.e., midget impinger, PCM or TEM), but side by side sampling and analyses were conducted to develop appropriate conversion criteria. AND - For an occupational population, contains detailed employment records and quantitative estimates of exposure using either PCM or TEM which allows for construction of job- matrix for entire work history of exposure (i.e.. Cumulative or peak exposures, and time since first exposure). Medium For all studv tvpes: - (Exposure was assessed during one time period but this time period is judged to be reasonably representative of the entire study time period. AND - Exposure was assessed using a combination of midget impingers, PCM, and/or TEM measurements, but side by side sampling and analyses were not conducted for all operations and thus there is a lack of confidence in the conversion factors.) OR - For an occupational study population, contains detailed employment records and quantitative estimates of exposure using a combination of midget impingers and PCM or TEM measurements for only a portion of participant's work history of exposure (i.e., only early years or later years), such that extrapolation of the missing years is required. Low For all studv tvpes: -Exposure was estimated solely using professional judgement. OR - Exposure was directly measured and assessed using a quantitative method other than PCM or TEM and conversion factors were not determined. OR -The method of quantifying/counting fibers was not specified (PCM, TEM, or other method not specified) Page 88 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Critically Deficient For all study types: - Methods used to quantify the exposure were not well defined, and sources of data and detailed methods of exposure assessment were not reported (STROBE Checklist 7 and 8 (Von ElmetaL 2008)). OR - There was no quantitative measure or estimate of exposure. OR - There is evidence of substantial exposure misclassification that would significantly bias the results. Not Rated/Not Applicable - Do not select for this metric. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 5. Exposure Levels (detection/measurement/information biases) High - Do not select for this metric Medium For all study types: - The range and distribution of exposure is sufficient or adequate to develop an exposure-response estimate (Cooper et al.. 2016). AND - Reports 3 or more levels of exposure {i.e., referent group +2 or more) or an exposure- response model using a continuous measure of exposure. Low For all studv tvpes: - The range of exposure in the population is limited OR - Reports 2 levels of exposure (e.g., exposed/unexposed)) (Cooper et al.. 2016) (Source: IRIS) Critically Deficient For all study types: - The range and distribution of exposure are not adequate to determine an exposure- response relationship (Cooper et al.. 2016). OR - No description is provided on the levels or range of exposure. Not Rated/Not Applicable - Do not select for this metric. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 6. Temporalitv 1 detection/measurement/information biases) High For all study types: - The study presents an appropriate temporality between exposure and outcome (i.e.. the exposure precedes the disease). AND - The interval between the exposure (or reconstructed exposure) and the outcome is sufficiently long considering the latency of the disease (i.e., study follow-up is more than 15 vears for luna cancer) (LaKind et al.. 2014). Medium For all study types except cross-sectional studies: - Temporality is established, but it is unclear whether there is adequate follow-up for consideration of latencv (i.e., onlv 10 vears of follow-up) (LaKind et al.. 2014). Low For all studv tvves: - The temporality of exposure and outcome is uncertain. Page 89 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description OR - There is inadequate follow-up of the cohort considering the latency period (5-10 years of follow-up). Critically Deficient For all study types: - Study lacks an established time order, such that exposure is not likely to have occurred priorto outcome (LaKind et al.. 2014). OR - There was inadequate follow-up of the cohort for the expected latency period (<5 years). OR - Sources of data and details of methods of assessment were not sufficiently reported (e.g., duration of follow-up, periods of exposure, dates of outcome ascertainment, etc.) (Source: STROBE Checklist 8 (Von Elm et al.. 2008)). Not Rated/Not Applicable - Do not select for this metric. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Domain 3. Outcome Assessment Each of the following outcomes has separate criteria for Metric 7: Lung Cancer, Ovarian Cancer, Laryngeal Cancer, Other Cancer(s), Asbestosis, Pulmonary Function/Spirometry Results, Pleural Plaques, and Other Non- cancer Outcomes (Mesothelioma criteria are on the Mesothelioma Form) Metric 7. Outcome Measurement or Characterization (detection/measurement/information, performance, reporting biases): Lung Cancer High For all study types: - The outcome was assessed using one or a combination of the following well- established methods: o Lung cancer cases confirmed by histological or cytological means (including subtypes of lung cancer) o ICD-10 C34 (lung and bronchus with or without C33 (trachea) o ICD-9 (5-digit code) 162.2-162.9 or o ICD-8 (4-digit code) 162.1 or o ICD-7 (4-digit code) 162.1 and 163 o ICD-9 (3-digit code) 162 o ICD-8 (3-digit code) 162 o ICD-7 (3-digit code) 162 and 163 Medium For all studv tvpes: - Although authors state they identified lung cancer cases they did not use or report the ICD codes or cases were not confirmed by histological or cytological means. Low - Do not select for this metric Critically Deficient For all study types: - Any self-reported information. OR - Study lacks individual assessment of lung cancer {i.e., lung cancer is assessed as a combination of cancer types, excluding lung and bronchus or trachea). Not Rated/Not Applicable - The study did not assess lung cancer. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Page 90 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Metric 7. Outcome Measurement or Characterization (detection/measurement/information, performance, reporting biases): Ovarian Cancer High For all stuclv tvves: -The outcome was assessed using one or a combination of the following well-established methods: o Ovarian cancer cases confirmed by tissue biopsy o ICD-11 2C73 Malignant neoplasm of ovary o ICD-10 C56 Malignant neoplasm of ovary o ICD-9 183 Malignant neoplasm of ovary o ICD-8 183 Malignant neoplasm of ovary, fallopian tube and broad ligament, supplemented by additional information to validate a diagnosis of ovarian cancer, o Pre-ICD-8 codes supplemented by additional information to validate a diagnosis of ovarian cancer. o All fields on the death certificate were searched for a diagnosis of ovarian cancer. Medium For all stuclv tvves: - Other diagnostic methods such as imaging tests (ultrasound or CT scan) or CA-125 blood tests were used without confirmation by tissue biopsy. OR - The study reports a doctor diagnosis without additional details or validation. Low - Do not select for this metric Critically Deficient For all stuclv tvves: - The only included information is a self-reported diagnosis of ovarian cancer without any additional validation. Not Rated/Not Applicable - The study did not assess ovarian cancer. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Page 91 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Metric 7. Outcome Measurement or Characterization (detection/measurement/information, performance, reporting biases): Laryngeal Cancer High For all study types: - The outcome was assessed using one or a combination of the following well- established methods: o Laryngeal cancer cases confirmed by tissue biopsy, o ICD-11 2C23 Malignant neoplasm of larynx o ICD-10 C32 Malignant neoplasm of larynx o ICD-9 161 Malignant neoplasm of larynx o ICD-8 132 Malignant neoplasm of larynx o ICD-7 161 Malignant neoplasm of larynx o Pre-ICD-7 codes supplemented by additional information to validate a diagnosis of laryngeal cancer. o All fields on the death certificate were searched for a diagnosis of laryngeal cancer. Medium For all stuclv tvpes: - Other diagnostic methods were used without confirmation by tissue biopsy. OR - Doctor diagnosis without additional details or validation. Low - Do not select for this metric Critically Deficient For all studv tvpes: - The only included information is a self-reported diagnosis of laryngeal cancer without any additional validation. Not Rated/Not Applicable - The study did not assess laryngeal cancer. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 7. Outcome Measurement or Characterization (detection/measurement/information, performance, reporting biases): Other Cancer Outcomes High For all studv tvpes: - The cancer was assessed using well-established methods, such as one or a combination of the following: specific ICD Codes cases confirmed using histological or cytological methods, other lab tests, or diagnostic imaging. OR - All fields on the death certificate were searched for the specific diagnosis. Medium For all study types: - The authors state that they identified a specific health outcome, but less-established methods were used and they did not conduct method validation. AND - There is little to no evidence that the method had poor validity and little to no evidence of outcome misclassification. OR - There was a doctor's report or diagnosis, but no ICD code and no additional confirmation or validation of the diagnosis. Low - Do not select for this metric Critically Deficient For all study types: - The study lacks individual assessment of specific cancer types (/'. e., the specific cancer is assessed as a combination with other cancer types). Page 92 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description OR - Only self-reported information was included, without any validation. Not Rated/Not Applicable - The study did not assess other cancer outcomes. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 7. Outcome Measurement or Characterization (detection/measurement/information, performance, reporting biases): Asbestosis High For all stuclv tvves: - The outcome was assessed using one or a combination of the following well- established methods: Diagnostic imaging tests (such as chest x-rays or computed tomography (CT) scans) showing pulmonary fibrosis or scarring of the lung tissue. ICD-11 code CA60.2 Pneumoconiosis due to mineral fibers including asbestos o ICD-10 Code J61 Pneumoconiosis due to asbestos and other mineral fibers o ICD-9 Code 501 Asbestosis o ICD-8 515.2 Asbestosis o Pre-ICD-8 codes supplemented by additional information to validate a diagnosis of asbestosis o All fields on the death certificate were searched for a diagnosis of asbestosis. Medium For all stuclv tvves: - The authors report doctor-diagnosed asbestosis but do not report specific evidence of lung tissue scarring or ICD codes. Low - A less valid method was used to diagnose asbestosis without confirmation using imaging tests. Critically Deficient For all stuclv tvves: - The only included information is a self-reported diagnosis of asbestosis without any additional validation. Not Rated/Not Applicable - The study did not assess asbestosis. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 7. Outcome Measurement or Characterization (detection/measurement/information, performance, reporting biases): Pulmonary Function/Spirometry Testing Results High For all stuclv tvves: - The outcome was assessed using well established methods that include standardized spirometric measurements (FEV1, FVC) and/or diffusing capacity of the lungs for carbon monoxide (DLCO) measurements. Forced expiratory Volume in Is (FEV1) and Forced Vital Capacitv (FVC) (Finnish Institute of Occupational Health. 2014). Medium For all stuclv tvves: - Use of less sensitive and standard methods such as low scanning electron microscopy (SEM), which lacks sensitivity and standardization as it relates to pulmonary function. - There is little to no evidence that the method had poor validity and little to no evidence of outcome misclassification. Low - Do not select for this metric Page 93 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Critically Deficient For all study types: - Any self-reported information without additional validation. - Study lacks individual assessment of pulmonary function and does not use spirometry testing Not Rated/Not Applicable - The study did not assess pulmonary function. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 7. Outcome Measurement or Characterization (detection/measurement/information, performance, reporting biases): Pleural Abnormalities, Pleural Plaques, or Parenchymal Opacities High For all stuclv tvpes: - The outcome was assessed using well-established methods such as x-rays or high- resolution computed tomography (HRCT), with cases defined based on consensus of two or more B-readers* (blinded) for any pleural abnormality or parenchymal opacities QLO. 2000). OR o ICD-11 Code CB20 Pleural Plaque o ICD-10 Code CM J92 Pleural Plaque OR o All fields on the death certificate were searched for the specific diagnosis. Medium For all studv tvpes: - The outcome was assessed using x-rays or HRCT methods: cases defined as one B- reader assessment (with either blinding reported or not) for any pleural abnormality or parenchymal opacities. OR - There was a doctor's report or diagnosis but using other less-established methods. Low - Do not select for this metric Critically Deficient For all study types: - The study lacks assessment of any of the specific pleural abnormality types {i.e., costophrenic angle obliteration or diffuse pleural thickening) or parenchymal opacities {i.e., small opacities or large opacities). OR - Only self-reported information without any validation. Not Rated/Not Applicable - The study did not assess pleural abnormalities, pleural plaques, or parenchymal opacities. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Page 94 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Metric 7. Outcome Measurement or Characterization (detection/measurement/information, performance, reporting biases): Other Non-cancer Outcomes High For all study types: - The outcome was assessed using well-established methods, such as one or a combination of the following: specific ICD Codes, cases confirmed using histological or cytological methods, other lab tests, or diagnostic imaging. OR - All fields on the death certificate were searched for the specific diagnosis. Medium For all stuclv tvpes: - The authors state that they identified a specific health outcome, but less-established methods were used and they did not conduct method validation. AND - There is little to no evidence that the method had poor validity and little to no evidence of outcome misclassification. OR - There was a doctor's report or diagnosis, but no ICD code and no additional confirmation or validation of the diagnosis. Low - Do not select for this metric Critically Deficient For all study types: - Only self-reported information was included, without any validation. Not Rated/Not Applicable - The study did not assess other non-cancer outcomes. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 8. Reporting Bias High For all studv tvpes: - Findings are reported in the abstract, results or discussion. Effect estimates are reported with confidence intervals and/or standard errors, number of cases/controls or exposed/unexposed reported for each analysis, to be included in exposure-response analvsis or fullv tabulated during data extraction and analvses (NTP. 2015). Medium For all studv tvpes: - All of the study's findings (primary and secondary) outlined in the abstract, results or discussion (that are relevant for the evaluation) are reported but not in a way that would allow for detailed extraction (e.g., results were discussed in the text but accompanying data were not shown). Low For all study types: - Outcomes outlined in the methods, abstract, and/or introduction (that are relevant for the evaluation) have not been reported (NTP. 2015). Critically Deficient - Do not select for this metric Not Rated/Not Applicable - Do not select for this metric. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Page 95 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Domain 4. Potential Confounding/Variability Control'1 Metric 9. Covariate Adjustment (confounding) High For all stuclv tvpes: - Appropriate adjustments or explicit considerations were made for potential confounders (e.g., age, sex, SES, race, etc.) (excluding co-exposures, which are evaluated in metric 11) in the final analyses through the use of statistical models to reduce research-specific bias, including matching, adjustment in multivariate models, stratification, or other methods that were appropriatelv justified (NTP. 2015). For studies reporting SMRs or SIRs: - Adjustments are described and results are age-, race-, and sex-adjusted (or stratified) if applicable. Medium For all study types: - There is indirect evidence that appropriate adjustments were made (i.e.. considerations were made for primary covariates (excluding co-exposures) and potential confounders adjustment) without providing a description of methods. OR - The distribution of potential confounders (excluding co-exposures) did not differ significantly between exposure groups or between cases and controls. OR - The major potential confounders (excluding co-exposures) were appropriately adjusted (e.g., SMRs, SIRs, etc.) and any not adjusted for are considered not to appreciably bias the results (e.g., smoking rates in an occupational cohort are expected to be generally similar in different departments and thus confounding by smoking is unlikely when internal analyses are applied). For studies reporting SMRs or SIRs: - Results are adjusted (or stratified) for age and sex, unless adjustment or stratification is not necessary because the exposed and control groups are sufficiently similar on the particular demographic variable. Low For all study types: - There is indirect evidence (i.e., no description is provided in the study) that considerations were not made for potential confounders adjustment in the final analyses (NTP. 2015). AND - The distribution of primary covariates (excluding co-exposures) and potential confounders was not reported between the exposure groups or between cases and controls (NTP. 2015). For studies reporting SMRs or SIRs: - Results are adjusted or stratified for age, race, OR sex (any one of the three), unless adjustment or stratification is not necessary because the exposed and control groups are sufficiently similar on the particular demographic variable. Critically Deficient For all studv tvpes: - The distribution of potential confounders differed significantly between the exposure groups. AND - Confounding was demonstrated and was not appropriately adjusted for in the final analvses (NTP. 2015). For studies reporting SMRs or SIRs: - No discussion of adjustments. Results are not adjusted for both age and sex (or stratified) if applicable. Page 96 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Not Rated/Not Applicable - Do not select for this metric Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 10. Covariate Characterization (measurement/information, confounding biases) High For all stuclv tvpes: - Potential confounders (e.g., age, sex, SES), excluding co-exposures, were assessed using valid and reliable methodology where appropriate (e.g., validated questionnaires, biomarker). Medium For all stuclv tvpes: - A less-established method was used to assess confounders (excluding co-exposures) and no method validation was conducted against well-established methods, but there was little to no evidence that that the method had poor validity and little to no evidence of confounding. Low For all stuclv tvpes: - The confounder assessment method is an insensitive instrument or measure or a method of unknown validity. Critically Deficient For all stuclv tvpes: - Confounders were assessed using a method or instrument known to be invalid. Not Rated/Not For all study types: Applicable - Covariates were not assessed. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 11. Co-exposure Confounding (measurement/information, confounding biases) High - Do not select for this metric. Medium For all study types: - Any co-exposures to pollutants that are not the target exposure that would likely bias the results were not likely to be present. OR - Co-exposures to pollutants were appropriately measured and either directly or indirectly adjusted for. - Example: There is confirmation of the likely absence of known co-exposures via mechanisms such as engineering controls (closed systems) for co-pollutants or confirmation of the absence of co-pollutants through monitoring. Low For cohort and cross-sectional studies: - There is direct evidence that there was an unbalanced provision of additional co- exposures across the primary study groups, which were not appropriately adjusted for. For case-control studies: - There is direct evidence that there was an unbalanced provision of additional co- exposures across cases and controls, which were not appropriately adjusted for, and significant indication a biased exposure-outcome association. OR For all study types: - In an occupational setting, potential co-exposures are not discussed. Critically Deficient - Do not select for this metric Not Rated/Not Applicable - Enter ""N/A" and do not score this metric. Page 97 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Domain 5. Analysis Metric 12. Studv Desian and Methods High - Do not select for this metric. Medium For all study types: - The study design chosen was appropriate for the research question. OR - The study uses an appropriate statistical method to address the research question(s) (e.g., Cox and Poisson regression for cohort studies and logistic regression analysis for case-control studies. Low - Do not select for this metric. Critically Deficient For all study types: - The study design chosen was not appropriate for the research question. OR - Inappropriate statistical analyses were applied to assess the research questions. Not Rated/Not Applicable - Do not select for this metric. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 13. Statistical Power (sensitivity) High - Do not select for this metric. Medium For cohort and cross-sectional studies: - The number of participants are adequate to detect an effect in the exposed population and/or subgroups of the total population. OR - The paper reported statistical power is high enough (> 80%) to detect an effect in the exposure population and/or subgroups of the total population. For case-control studies: - The number of cases and controls are adequate to detect an effect in the exposed population and/or subgroups of the total population. OR - The paper reported statistical power is high enough (>80%) to detect an effect in the exposure population and/or subgroups of the total population. Low - Do not select for this metric. Critically Deficient For cohort and cross-sectional studies: - The number of participants is inadequate to detect an effect in the exposed population and/or subgroups of the total population and the study was negative. For case-control studies: - The number of cases and controls are inadequate to detect an effect in the exposed population and/or subgroups of the total population and the study was negative. Not Rated/Not Applicable - Do not select for this metric. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance Page 98 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Metric 14. Reproducibility of Analyses (adapted from Blettner et al. (2001)) High - Do not select for this metric. Medium For all stuclv tvpes: - The description of the analysis is sufficient to understand how to conceptually reproduce the analysis with access to the analytic data. Low For all stuclv tvpes: - The description of the analysis is insufficient to understand what has been done and to be reproducible OR a description of analyses are not present (e.g., statistical tests and estimation procedures were not described, variables used in the analysis were not listed, transformations of continuous variables (e.g., logarithmic) were not explained, rules for categorization of continuous variables were not presented, exclusion of outliers was not elucidated and how missing values are dealt with was not mentioned). Critically Deficient - Do not select for this metric. Not Rated/Not Applicable - Do not select for this metric Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 15. Statistical Models (confounding bias) High - Do not select for this metric. Medium For all stuclv tvpes: - The model or method for calculating the risk estimates (e.g., odds ratios, SMRs, SIR) is transparent (i.e., it is stated how/why variables were included or excluded). AND - Model assumptions were met. Low For all stuclv tvves: - The statistical model building process is not fully appropriate OR model assumptions were not met OR a description of analyses and assumptions are not present (STROBE Checklist 12e (Von Elm et al., 2008)). Critically Deficient - Do not select for this metric. Not Rated/Not Applicable - Enter ""N/A" if the study did not use a statistical model. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Domain 6. Other (if applicable) Considerations for Biomarker Selection and Measurement (LaKind et al.. 2014) Metric 16. Use of Biomarker of Exposure (detection/measurement/information biases) High - Biomarker in a specified matrix has accurate and precise quantitative relationship with external exposure, internal dose, or target dose. AND - Biomarker is derived from exposure to one parent chemical. Medium - Biomarker in a specified matrix has accurate and precise quantitative relationship with external exposure, internal dose, or target dose. AND - Biomarker is derived from multiple parent chemicals. Low - Evidence exists for a relationship between biomarker in a specified matrix and external exposure, internal dose or target dose, but there has been no assessment of accuracy and precision or none was reported. Page 99 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Critically Deficient - Biomarker in a specified matrix is a poor surrogate (low accuracy, specificity, and precision) for exposure/dose. Not Rated/Not Applicable - Select "N/A" if no human biological samples were assessed or if the only biomarkers assessed were biomarkers of effect or biomarkers of susceptibility. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 17. Effect Biomarker (detection/measurement/information biases) High - Effect biomarker measured is an indicator of a key event in an adverse outcome pathway (AOP). Medium - Biomarkers of effect shown to have a relationship to health outcomes using well validated methods, but the mechanism of action is not understood. Low - Biomarkers of effect shown to have a relationship to health outcomes, but the method is not well validated and mechanism of action is not understood. Critically Deficient - Biomarker has undetermined consequences (e.g., biomarker is not specific to a health outcome). Not Rated/Not Applicable - Select "N/A" if no human biological samples were assessed or if the only biomarkers assessed were biomarkers of exposure or biomarkers of susceptibility. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 18. Method Sensitivitv (detection/measurement/information biases) High - Do not select for this metric. Medium - Limits of detection are low enough to detect chemicals in a sufficient percentage of the samples to address the research question. Analytical methods measuring biomarker are adequately reported. The limit of detection (LOD) and limit of quantification (LOQ) (value or %) are reported. Low - Frequency of detection too low to address the research hypothesis. OR - LOD/LOQ (value or %) are not stated. Critically Deficient - Do not select for this metric. Not Rated/Not Applicable - Do not select "N/A" for this metric if the study assessed biomarkers. If LOD/LOQ are not stated then select Low. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 19. Biomarker Stabilitv (detection/measurement/information biases) High - Samples with a known storage history and documented stability data or those using real-time measurements. Medium - Samples have known losses during storage, but the difference between low and high exposures can be qualitatively assessed. Low - Samples with either unknown storage history and/or no stability data for target analytes and high likelihood of instability for the biomarker under consideration. Critically Deficient - Do not select for this metric. Not Rated/Not Applicable - Do not select "N/A" for this metric if the study assessed biomarkers. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Page 100 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Metric 20. Sample Contamination (detection/measurement/information biases) High - Samples are contamination-free from the time of collection to the time of measurement (e.g., by use of certified analyte free collection supplies and reference materials, and appropriate use of blanks both in the field and lab). AND - Documentation of the steps taken to provide the necessary assurance that the study data are reliable is included. Medium - Samples are stated to be contamination-free from the time of collection to the time of measurement. AND - There is incomplete documentation of the steps taken to provide the necessary assurance that the study data are reliable. OR - Samples are known to have contamination issues, but steps have been taken to address and correct contamination issues. OR - There is no information included about contamination (only allowed for biomarker samples not susceptible to contamination). Low - Samples are known to have contamination issues, but steps have been taken to address and correct contamination issues. OR - Samples are stated to be contamination-free from the time of collection to the time of measurement, but there is no use or documentation of the steps taken to provide the necessary assurance that the study data are reliable. Critically Deficient - There are known contamination issues (e.g., phthalate study that used plastic sample collection vials) and no documentation that the issues were addressed. Not Rated/Not Applicable - Do not select "N/A" for this metric if the study assessed biomarkers. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Metric 21. Method Requirements (detection/measurement/information biases) High - Instrumentation that provides unambiguous identification and quantitation of the biomarker at the required sensitivity (e.g., gas chromatography/high-resolution mass spectrometry [GC-HRMS]; gas chromatography with tandem mass spectrometry [GC- MS/MS]; liquid chromatography with tandem mass spectrometry [LC-MS/MS]). Medium - Instrumentation that allows for identification of the biomarker with a high degree of confidence and the required sensitivity (e.g., gas chromatography mass spectrometry [GC-MS], gas chromatography with electron capture detector [GC-ECD]). Low - Instrumentation that only allows for possible quantification of the biomarker, but the method has known interferants (e.g., gas chromatography with flame-ionization detection [GC-FID], spectroscopy). Critically Deficient - Do not select for this metric. Not Rated/Not Applicable - Do not select "N/A" for this metric if the study assessed biomarkers. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. Page 101 of 102 ------- PUBLIC RELEASE DRAFT - DO NOT CITE OR QUOTE August 2023 Data Quality Rating Description Metric 22. Matrix Adjustment (detection/measurement/information biases) High - If applicable for the biomarker under consideration, study provides results, either in the main publication or as a supplement, for both adjusted and unadjusted matrix concentrations (e.g., creatinine-adjusted or specific gravity-adjusted and non-adjusted urine concentrations) and reasons are given for adjustment approach. Medium - If applicable for the biomarker under consideration, study only provides results using one method (matrix-adjusted or not). Low - If applicable for the biomarker under consideration, no established method for matrix adjustment was conducted. Critically Deficient - Do not select for this metric Not Rated/Not Applicable - If metrics 16 and 17 are both NA, then the remaining biomarker metrics are automatically not rated. Otherwise: Select ""N/A" if matrix adjustment is not required for assessment of the biomarker. Reviewer's Comments Document concerns, uncertainties, limitations, and deficiencies and any additional comments that may highlight study strengths or important elements such as relevance. 11 Smoking fits in Metrics 9 and 10, not Metric 11; Metric 9 addresses whether there was appropriate adjustment or consideration of confounders (such as stratification) (other than co-exposures); Metric 10 addresses how the potential confounders (other than co-exposures) were measured; Metric 11 assesses co-exposure confounding. 2164 Page 102 of 102 ------- |