EPA 402-R-93-076
ESTIMATING RADIOGENIC CANCER RISKS
June 1994
U.S. Environmental Protection Agency
401 M Street S.W.
Washington, DC 20460
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The scientific basis for this report has been reviewed formally by the Radiation
Advisory Committee (RAC) of the EPA Science Advisory Board (SAB). The
following paragraph is a synopsis of that review.
On January 10, 1992, Margo T. Oge, Director, Office of Radiation Programs
(now the Office of Radiation and Indoor Air or ORIA) requested that the RAC
review an issues paper comparing health risk estimates due to low level
exposures of low-LET radiation based on models recently published by the
Radiation Effects Research Foundation, the United Nations, the National
Radiological Protection Board of the UK, the National Academy of Sciences,
the US Nuclear Regulatory Commission, and the International Commission on
Radiation Protection. Following discussions on February 12, 1992 with the
RAC, ORIA staff prepared a document titled "Proposed Methodology for
Estimating Radiogenic Cancer Risk" and forwarded it to the RAC for their
review on May 1, 1992. In their letter to the EPA Administrator dated
December 9, 1992, Dr. Raymond C. Loehr, Chairman, SAB Executive
Committee, and Dr. Oddvar E. Nygaard, Chairman, SAB Radiation Advisory
Committee, provided the Committee's evaluation of the proposed ORIA
methodology for estimating radiogenic cancer risks. They concluded that,
"Although no single data set and model for predicting radiogenic cancer risk is
ideal, the method of analysis chosen by EPA is adequately supported by
present evidence." They also offered some comments and suggestions for
future consideration. In her letter of April 19, 1993, Carol M. Browner,
Administrator, EPA, provided responses to those comments and suggestions.
This report, which was prepared by EPA staff members Jerome S. Puskin and
Christopher B. Nelson, Office of Radiation and Indoor Air, Criteria and
Standards Division, presents radiation risks calculated with the models
proposed to the RAC. It also includes risks due to radionuclide intakes and
external exposures calculated with those models.
The authors gratefully acknowledge constructive reviews by Charles E. Land,
National Cancer Institute; Donald A. Cool and Shlomo S. Yaniv, Nuclear
Regulatory Commission; and Harold T. Peterson, Jr., Department of Energy.
The mailing address for the authors is:
U.S. Environmental Protection Agency
Office of Radiation and Indoor Air (6602J)
Washington, DC 20460
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ABSTRACT
This document presents a revised methodology for EPA's estimation of cancer risks
due to low-LET radiation exposures developed in light of information that has become
available since the publication of BEIR III, especially new information on the Japanese
atomic bomb survivors. For most cancer sites, the risk model is one in which the age-specific
relative risk coefficients are obtained by taking the geometric mean of coefficients derived
from the atomic bomb survivor data employing two different methods for transporting risks
from Japan to the U.S. (multiplicative and NIH projection methods). Using 1980 U.S. vital
statistics, the risk models are applied to estimate organ-specific risks, per unit dose, for a
stationary population. With the exception of breast cancer, low-LET radiogenic cancer risks
are assumed to be reduced by a dose and dose rate effectiveness factor (DDREF) of 2 at low
doses and dose rates compared to risks at high acute dose exposure conditions. The DDREF
assumed for breast cancer is 1. For low dose (or dose rate) conditions, the calculated risk of a
premature cancer death attributable to uniform, whole-body, low-LET irradiation is about
5.1 x 10"2 Gy"1. The corresponding incidence risk (neglecting nonfatal skin cancers) is about
7.6x 10"2 Gy"1. High-LET (alpha particle) risks are presumed to increase linearly with dose
and to be independent of dose rate. Except for leukemia and breast cancer, a relative
biological effectiveness (RBE) factor of 20 is adopted for the risk of high-LET radiation
relative to that for low-LET radiation at low dose or low dose rate conditions. For leukemia,
an effective high-LET RBE of 1 is used; for breast cancer, the high-LET RBE is 10. Using
the revised methodology, lifetime cancer risks associated with constant exposure rate
conditions are estimated for over 300 radionuclides.
in
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IV
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CONTENTS
Section Page
ABSTRACT iii
LIST OF TABLES vii
I. Introduction 1
II. Scientific Basis for Risk Estimates 1
A. Epidemiological Data 1
B. Modeling the Epidemiological Data 2
Age and Temporal Dependence 2
Transport of Risk Estimates Across Populations 3
Dose Response Function and Dependence on Dose Rate 3
C. Risk from Alpha Particles 6
III. Comparison of Alternative Risk Models 8
A. Model Descriptions 8
B. Comparison of Risk Projections 12
C. Extrapolation to Low Doses and Dose Rates 16
D. High-LET Risk Estimates (RBE) 17
IV. Methodology for Estimating Radiogenic Cancer Risks 17
A. Selection of Risk Models 17
B. Transport of Risk Estimates from Japan 18
C. Adjustments to Models 21
D. Other Cancer Sites 22
E. Summary of Site Specific Cancer Mortality Risk Estimates 24
F. Incidence Risk Estimates 24
G. Dose and Dose Rate Effectiveness Factor (DDREF) 26
H. Alpha Particle RBE 27
I. Summary of Revisions in EPA Low Dose Risk Estimates 28
References 31
Appendix A: Calculational Methods 35
A. Introduction 35
B. Risk Model Formulation 36
C. Revised Methodology Risk Models 36
D. Risk Calculations 39
E. Baseline Force of Mortality Calculations 44
F. Radionuclide Risk Coefficients 45
References for Appendix A 58
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VI
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LIST OF TABLES
Table Title Page
1 Low-LET U.S. population fatal cancer risk (deaths per 104 person-Gy) for five
models 13
la Low-LET U.S. population risks (deaths per 104 person-Gy) of stomach and
colon cancer mortality for two ICRP Publication 60 models 15
2 Comparison of fatal cancer risks (deaths per 104 person-Gy) for the geometric
mean coefficient (GMC) projection model with Land & Sinclair (ICRP)
and NUREG/CR-4214 models 20
3 Residual site mortality risk coefficients for the additive and multiplicative
projections of Land and Sinclair (1991) 21
4 Site specific mortality risk estimates (per 104 Gy) for proposed EPA model
compared with those for ICRP and NUREG/CR-4214 models (male and
female combined, DDREF=1) 25
5 Lethality data for adult cancers by site 26
6 EPA low dose, low dose rate cancer mortality risks (10"4 per Gy) 29
A. 1 Coefficients for the Revised Methodology mortality risk model (male and
female by age group) 37
A.2 Dose regions associated with cancer types in the Revised Methodology risk
models 43
A.3 ICD codes used to define cancer types 47
A.4a Revised Methodology radionuclide mortality risk coefficients 49
A.4b Revised Methodology radionuclide incidence risk coefficients 53
A.5 Default inhalation clearance class and ingestion f\ values by element 57
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I. Introduction
Since 1984, EPA's estimates of risk from low-LET radiation have been based on the
1980 National Academy of Sciences' (NAS) BEIR III Report (NAS 1980, EPA 1984, EPA
1989). Subsequently, important new data have become available, especially revised
dosimetry and further epidemiological follow-up on the Japanese atomic bomb survivors.
Risk estimates derived in light of the new data have now been presented in several recent
reports (Shimizu et al. 1988, 1990; IMSCEAR 1988; Stather et al. 1988; NAS 1990; ICRP
1991; Land and Sinclair 1991; Gilbert 1991). We critically examine here the information in
those reports, and some ancillary information, with the aim of developing a revised
methodology for EPA's calculations of radiogenic cancer risks. Radiogenic benign neoplasm
risks are not considered in this report.
In Section II, the main scientific issues are outlined and discussed. Section III
compares the assumptions and numerical projections of risk pertaining to alternative models
found in the above reports. Section IV presents EPA's revised methodology for estimating
radiogenic cancer risks at low doses and dose rates. The Appendix discusses calculational
methods and includes risk estimates for individual radionuclides.
Calculated values in this report are typically shown to three significant figures or one
decimal place. This practice is intended to facilitate comparisons and to simplify tabulations
only. The number of significant figures should not be considered to indicate the level of
certainty in the tabulated values.
II. Scientific Basis for Risk Estimates
A. Epidemiological Data
By far the most important source of data upon which to base estimates of risk from
low-LET ionizing radiation is the Atomic Bomb Survivor Study (ABSS). Noteworthy
features of this study include: a large, relatively healthy population at the time of exposure; all
ages and both sexes; a wide range of doses, believed to be well estimated on an individual
basis, to all organs of the body; existence of a good control group, consisting of people who
were present in Hiroshima or Nagasaki at the time of bombing but who received only small
doses of radiation; detailed, long-term (40 y) epidemiological follow-up. A statistically
significant excess cancer mortality associated with radiation has been found among the bomb
survivors for the following types of cancer: leukemia, esophagus, stomach, colon, liver, lung,
breast, ovary, urinary tract, and multiple myeloma.
There is an extensive body of epidemiological data on radiation-exposed populations,
apart from the A-bomb survivors. Most important from the standpoint of developing
quantitative estimates of risk from low-LET radiation are the studies of medical exposures of
the thyroid and breast. For two other sites, bone and liver, low-LET risk estimates are
commonly determined from epidemiological studies of cohorts exposed to alpha particle
irradiation, extrapolating a value of RBE from animal studies. Cohorts ingesting or injected
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radiogenic liver cancer consists of patients receiving Thorotrast (ThO2) injections. There are
additional important epidemiological studies of persons exposed to low-LET radiation, most
notably, perhaps, the ankylosing spondylitis and cervical cancer patients. Currently, however,
the main value of these studies is for comparison to the A-bomb survivors; none of the major
recent efforts at radiation risk estimation (see below) make direct use of these studies in
developing quantitative estimates of risk.
B. Modeling the Epidemiological Data
There are many different ways one could organize and model the ABSS data. Choices
can be made regarding: the grouping of cancer sites and age groups, the mathematical form of
the dose-response, and the general form of the age and temporal dependence. These choices
are generally made after exploratory analyses of the data, which indicate what parameters are
most useful to incorporate into the models. By breaking down the data into smaller subgroups,
interesting features may be revealed, but, at some point, the concomitant increase in statistical
variability precludes any meaningful improvement in the model. This constraint may lead to
certain trade-offs; e.g., to obtain a more detailed analysis of the effects of age and temporal
factors on risk, the BEIR V Committee combined all types of GI cancers into a single
category, even though a single model cannot adequately describe the risk for the different GI
cancers.
Age and Temporal Dependence
Information on the variation of risk of site specific radiogenic cancers among the
atomic bomb survivors with age and time is limited by sampling uncertainties and by the
incomplete period of epidemiological follow-up. For a given age at time of the bomb (ATB),
the excess solid tumor mortality has generally been found to increase with the age at death
(ATD), roughly in proportion to the age-specific baseline rate for the site of interest.
Consequently, models for these tumors are now generally framed in terms of relative risk.
For the period of epidemiological follow-up, the highest relative risks are found in the
youngest exposure categories. But the lifetime risks of solid tumors due to exposures before
age 20 remain highly uncertain. Individuals exposed as children are only now entering the
years of life where the risk of cancer is concentrated. While this group has exhibited a high
relative risk per unit dose, thus far, the observed excess represents a small number of cancer
deaths. Hence, the sampling error for most types of cancers is large for the younger age
cohorts. It is, moreover, unclear to what extent the observed high relative risks will persist.
Theoretical considerations, arising from carcinogenesis modeling, would suggest that the
relative risks will decrease over time (Little and Charles 1991). In addition, there is some
epidemiological evidence suggestive of such a temporal fall-off in groups irradiated as
children (IMSCEAR 1988, Little et al. 1991).
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Conclusions. For cancers other than leukemia, there is strong evidence of an
increasing risk with age at expression, roughly in proportion to the increase with age of
baseline cancer mortality. The data are generally consistent with a constant relative risk
model in which the risk coefficients decrease with age at exposure. There is some suggestive
evidence of a fall-off in relative risk with time after exposure, especially for childhood
exposures (NAS 1990), but further epidemiological surveillance will be necessary to clarify
the pattern of the temporal change (Shimizu et al. 1988).
Transport of Risk Estimates Across Populations
Baseline rates for specific cancer types vary from population to population, as well as
over time, within a population. For example, stomach cancer rates are substantially higher in
Japan than in the U.S., while the reverse is true for lung, colon, and breast cancer; moreover,
the incidence rates for lung and breast cancer, particularly, have been increasing in both
populations during recent years. Despite the observed rough proportionality between radiation
risk and baseline cancer rates by age, one cannot necessarily infer that the radiation risk will
vary in proportion to the baseline rate as one goes from one population to another.
Information on how to "transport" risk estimates across populations is limited by the
quality of data available on irradiated populations other than the bomb survivors. Two cancer
types for which comparison data exist are thyroid and breast: data on the former suggest that
the risk does increase with the baseline rate (NAS 1990), but it would appear that the opposite
may be true for the latter (Preston 1991). Some insight into the problem might be gained by
looking at subgroups of an irradiated population. For example, lung cancer rates in Japanese
males are several times higher than in Japanese females, presumably due in part to the higher
smoking rate in males. Nevertheless, the excess absolute risk for lung cancer attributable to
radiation does not differ significantly between the male and female bomb survivors. This
would suggest that, for lung cancer, absolute risk may be more transportable than relative
risk.
Conclusions. Information on how to transport risk estimates between populations is
very limited; what information there is suggests that the answer is likely to be cancer site
specific.
Dose Response Function and Dependence on Dose Rate
A major issue in radiation risk assessment is how best to quantify the risks and to
characterize their uncertainties for small incremental doses above natural background. A
comprehensive examination of this question was contained in NCRP Report 64 (NCRP 1980).
Based primarily on laboratory studies of cells, plants and animals, the report advocated a
linear-quadratic dose response for acute doses up to about 2.5-4 Gy, above which the dose
response begins to turn over due to cell killing effects. At low doses, the quadratic term is
negligible in comparison to the linear term. The NCRP committee defined the low dose region
as 0-0.20 Gy, since significant deviations from linearity are found in Tradescantia
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experiments and in life shortening in mice above this range. Evidence was also cited to the
effect that the D2 term in the dose response function vanishes when the radiation is delivered
at low dose rates, even for total doses above 0.2 Gy.
A theoretical framework for the linear-quadratic dose response model has been
developed by Kellerer and Rossi (1972), utilizing concepts originally put forth by Lea (1962).
In this theory of "dual radiation action," events leading to "lesions" (i.e., permanent changes)
in cellular DNA require the formation of interacting pairs of "sublesions." The interacting
pairs can be produced by a single traversing particle, or track, or by two tracks, giving rise,
respectively, to a linear and a quadratic term in the dose response relationship. According to
the theory, a sublesion may be repaired before it can interact to form a lesion, the probability
of such repair increasing with time. Consequently, as the dose rate is reduced, the formation
of lesions from sublesions caused by separate tracks becomes less important, and the
magnitude of the D2 term decreases. Hence, the theory predicts that at sufficiently low doses
or dose rates, the response should be linear and, in either limit, should have the same slope.
Results of animal tumorigenesis studies are, in general, qualitatively consistent with
the theory: low-LET radiation seems to have reduced effectiveness per unit dose at low dose
rates (NCRP 1980). However, it is usually not possible from the data to verify that the dose
response curve has the linear-quadratic form. Another success of the dual action theory has
been in explaining observed differences between the effects of low- and high-LET radiations.
In this view, the densely ionizing nature of the latter results in a much greater production of
interacting pairs of sublesions by single tracks, leading to a higher biological effectiveness at
low doses and a linear dose response relationship (except for deviations at high doses
attributable to cell-killing effects).
The dual action theory has nevertheless been challenged on experimental grounds, and
observed variations in response with dose, dose rate, and LET can also be explained by other
mechanisms, e.g., a theory involving only single lesions and a "saturable" repair mechanism
that decreases in effectiveness at high dose rates on the microscopic scale (Goodhead 1982).
One property of such a theory is that, in principle, the effectiveness of repair - and therefore
the shape of the dose response curve - can vary widely with cell type and species. Hence,
results obtained on laboratory animals might not be entirely applicable to humans.
According to either the dual action theory or the saturable repair theory, the dose
response should be linear at low doses or low dose rates, and with equal slopes. At higher
doses and dose rates, multiple track events become important, and the dose response should
bend upward. As a result, the response per unit dose at low doses and dose rates will be
overestimated if one extrapolates linearly from observations made at high doses, acutely
delivered (NCRP 1980). The degree of overestimation is commonly expressed in terms of a
dose and dose rate effectiveness factor (DDREF): e.g., a DDREF of 3 means the risk per unit
dose observed at high acute doses should be divided by 3 before being applied to low dose
(dose rate) conditions.
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Current mechanistic explanations for a DDREF involve DNA repair. The linearity of
the dose response at low doses suggests that DNA repair is maximal and independent of dose
rate for doses below about 0.2 Gy. Repair of radiation-induced DNA damage is found to be
largely complete within a few hours of an acute exposure (Wheeler and Wierowski 1983,
Ullrich et al. 1987). Consequently, protracting the dose beyond this time span should have
little or no effect on the risk of cancer induction. It is expected, therefore, that repair will be
maximal so long as no doses above 0.2 Gy are delivered within a few hours.
When the BEIR III Committee attempted to fit the ABSS data to a linear-quadratic
model, the results were not very satisfactory (NAS 1980). Depending on whether one
analyzed solid tumors or leukemia, and depending on which city the data were drawn from,
the shape of the fitted dose response changed markedly; in some cases no reasonable fit could
be obtained. Some of the discrepancy was resolved by attributing a substantial fraction of the
excess cancers in Hiroshima to neutrons, but serious problems remained, and the ultimate
choice of dose response function seemed to be strongly influenced by supporting laboratory
data.
With the revised "DS86" dosimetry, these curve-fitting problems are largely removed
(Shimizu et al. 1990, NAS 1990). The data from the two cities are now in reasonable
agreement. The combined leukemia data can be fit by a linear-quadratic dose response
function; the slope of the function at low doses is about half that obtained by a linear fit to the
data. A statistical analysis of the solid tumor data, on the other hand, indicates no departure
from linearity in the dose response over the entire range from 10 to 400 rad. Using a linear-
quadratic model to fit the data reduces the linear term by, at most, a factor of 2 compared to a
simple linear model. Viewing these results through the paradigm adopted by NCRP 64 would
indicate that: a best estimate of the DDREF is about 2 for leukemia while, for solid tumors, a
DDREF of 2 represents an upper bound, and the best estimate is about 1.
The conclusions in the preceding paragraph, however, appear to require some
modification in light of a subsequent analysis by Pierce and Vaeth (1991). These authors
show that errors in dose estimation will introduce a negative bias in the dose-squared
dependence of the response. Assuming dosimetry errors of 30-40%, this has a relatively
minor effect on the best estimate of the DDREF, but the upper bound is increased to about 3.
Also pertinent to the issue of what DDREF is applicable to human cancer induction are
clinical studies of radiation-induced breast and thyroid cancer, which have shown little or no
reduction in risk with dose fractionation (Shore et al. 1984, Davis et al. 1989, Howe 1992).
This again suggests a DDREF of about 1 (ICRP 1991). On the other hand, while studies of
tuberculosis patients, who had undergone repeated fluoroscopic examinations, clearly show
an elevated risk of breast cancer from fractionated doses of x-rays, they show no indication of
an excess lung cancer risk (Davis et al. 1989, Howe 1992). When compared with observed
lung cancer risks in the atomic bomb survivors, the results of these studies suggest that the
DDREF may be quite large for lung cancer induction, although the possibility of confounding
by the underlying disease process cannot be ruled out.
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The results on human solid tumors appear to differ from those obtained through
laboratory studies, including studies of radiation-induced tumorigenesis in mice and rats. For
the most part, the laboratory studies suggest a DDREF of about 2 or 3, and sometimes higher,
depending on end point; on the other hand, the preponderance of the evidence on humans
suggests a lower DDREF, possibly about 1 for most sites. One can resolve this apparent
conflict in different ways, with significantly different implications for radiation risk estimation
at low doses and dose rates.
If one retains the linear-quadratic model in NCRP 64 and the connection it implies
between the shape of the dose response and the effect of dose rate on the response, the
Japanese data would seem to dictate an average DDREF no higher than 1 to 3 for radiation-
induced carcinogenesis in humans. It could then be argued that, in light of the extensive
laboratory data suggesting a DDREF of at least 2, a DDREF of 2-3 should be applied in
estimating risks to humans. On the other hand, it could be argued that animal data are an
unreliable guide to the response in humans and that a DDREF of 1, an approximate best
estimate from the human data, should be used in estimating the risk of solid tumors at low
doses and dose rates.
There are experimental data suggesting a difference in DDREF between humans and
rodents. Grosovsky and Little (1985) measured x-ray induced mutations in human
lymphoblast cells and found a linear dose response over the range 0.05-2 Gy, which was
independent of dose rate. Similar experiments performed on rodent cells have shown a
curvilinear dose response and a decrease in the response with decreasing dose rate.
Alternatively, one might reconcile the human and laboratory data by abandoning the
linear-quadratic model of radiation-induced carcinogenesis and its implied connection
between the shape of the dose response for acute doses and the effect of protracting the dose
over time. For example, one could envision having a linear response over the dose range
accessible to epidemiological observation (above about 0.1 Gy) but a substantial reduction in
risk at lower doses, or if these doses are fractionated or delivered chronically.
Studies indicate that repair of radiation-induced DNA damage is completed within a
few hours after it is incurred (Wheeler and Wierowski 1983, Ullrich et al. 1987). Hence, for
multitrack events to be biologically important, it would appear that at least two tracks would
have to pass through a cell nucleus within this time period. For low-LET doses of about 1
mGy, only one track, on average, traverses each cell nucleus. From these considerations, it is
expected that the same amount of unrepaired DNA damage per unit dose should occur so long
as the dose delivered over a few hours is below about 1 mGy. Such conditions define a
region in which the response is expected to be linear with dose and independent of any further
fractionation or reduction in dose rate.
Conclusions. Taken together, current scientific data are generally indicative of a
DDREF between 1 and 3 for human cancer induction. However, there is an indication that a
higher DDREF may apply to the lung.
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C. Risk from Alpha Particles
Radiobiological data indicate that high-LET alpha radiation has a larger biological
effect than an equal absorbed dose of low-LET radiation. The subject has recently been
reviewed in: the BEIR IV Report (NAS 1988); NCRP Report No. 104 (NCRP 1990); and
ICRP Publication 60 (ICRP 1991). The radiobiological results, including those for tumor
induction, are generally suggestive of a linear nonthreshold dose response for high-LET
radiation, except for a possible fall-off in effectiveness at high doses. In contrast to low-LET
radiation, the effects of high-LET radiation often increase with fractionation or with a
decrease in dose rate.
A number of cohorts exposed occupationally or medically to internally deposited alpha
emitters have shown an excess of cancer at heavily irradiated sites. Most important is the
observed induction of: (1) lung cancer in miners inhaling radon progeny; (2) bone sarcomas
in patients injected with Ra-224; (3) bone sarcomas and head carcinomas in dial painters
ingesting mixtures of Ra-226 and Ra-228; and (4) liver cancers in patients injected with
Thorotrast, an x-ray contrast medium containing isotopes of Th. Although other organs of the
body received doses of alpha radiation in these populations, excess cancers were generally not
observed at sites other than those mentioned. As a result, only upper bounds to the risk for
these other organs can be estimated from studies of humans exposed to alpha irradiation.
Site specific cancer risk estimates for high-LET radiation (neutrons or alpha particles)
are often calculated utilizing human epidemiological data on low-LET radiation (e.g., from
the ABSS) and laboratory data on the relative biological effectiveness (RBE) of the high-LET
radiation compared to a reference low-LET radiation (NCRP 1990). Since the dose response
relationship obtained for low-LET radiation is typically linear or concave upward while that
for high-LET radiation is linear or concave downward, the RBE is dose dependent. EPA is
primarily concerned with risks at low doses and dose rates, where the acute high dose risk for
low-LET radiation is reduced by the DDREF. Under these conditions, the dose responses for
both low and high LET radiations are thought to be linear, and the RBE takes on a constant
(maximum) value: RBEM.
Ranges of estimated values for neutron and alpha particle RBEM are wide, depending
on both the biological system and the observed end-point; the uncertainty in the RBEM
estimate from an individual study is also usually large, primarily due to the uncertainty in
extrapolation of low-LET data to low doses. The effectiveness of alpha emitters has been
found to be 15 to 50 times that of beta emitters for the induction of bone sarcomas, liver
chromosome aberrations, and lung cancers (NCRP 1990). Since the LET of secondary
protons produced by fission neutrons in living tissue is comparable to that for alpha particles,
data on the RBEs of fission neutrons provides ancillary information relevant to the estimation
of alpha particle RBE. Where the dose response data on carcinogenic end-points are adequate
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to derive an estimate, fission neutrons have been found to have an RBEM between 6 and 60
times that of low dose gamma rays (NCRP 1990).
III. Comparison of Alternative Risk Models
A. Model Descriptions
This section provides a qualitative description of 6 sets of risk models, all based
largely on ABSS data collected through 1985 and incorporating DS86 dosimetry.
RERF. A detailed description of the RERF's data on the atomic bomb survivors is
contained in two publications by Shimizu, Kato, and Schull (1988, 1990). The data on solid
tumors were analyzed using constant absolute and relative risk models, where the risk
coefficients were, however, allowed to vary with the age ATB. From this analysis, the
authors concluded that the relative, but not the absolute, risk model is consistent with the
observed temporal dependence of excess mortality due to solid tumors.
Most of the major qualitative conclusions that can be drawn from the analysis have
been discussed above. These include: (1) a statistically significant increase in cancer at
various sites, positively associated with radiation dose; (2) for solid tumors, an increase in risk
with age ATD, roughly in proportion to the increase in baseline cancer mortality with age; (3)
a substantially higher observed relative risk in those below age 20 ATB; (4) essentially a
linear dose response for solid tumors, but with evidence of a relatively small quadratic
contribution in the dose response for leukemia.
Age-specific risk coefficients are given for these sites: leukemia, stomach, breast, lung,
colon, and nonleukemia. In the Life Span Report, these are tabulated both for an assumed
neutron RBE of 1 and 10 (Shimizu et al. 1988).
UNSCEAR 88. The lifetime risks in UNSCEAR (1988) were calculated (for the
Japanese population) using coefficients from the RERF Life Span Study Report 11 (Shimizu
et al. 1990). Estimates for leukemia and all other malignancies are derived for age-specific,
absolute and relative risk projection models. The UNSCEAR report also provides risk
estimates for an expanded set of cancer sites, calculated using an "age-averaged" relative risk
model. In this model, the observed differences in relative risk with age ATB are ignored, and
a single, average risk coefficient is adopted for each site. This approach generally yields
somewhat lower estimates of the risk for constant lifetime exposures. While we would reject
the age-averaged model, as being less reflective of the epidemiological data collected so far, if
the high relative risks observed in the younger exposure groups decrease appreciably over
time, the age-averaged model may turn out to provide a better numerical estimate of the
lifetime risk than the age-specific model derived from these data.
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NRPB The NRPB report (Stather et al. 1988) represents a further elaboration of the
information contained in Life Span Study Report 11 and in UNSCEAR 88. Although other
model estimates are developed, the favored approach for solid tumors seems to the age-
specific, constant relative risk projection model, while an absolute risk model with a 2-40 y
expression period is adopted for leukemia.
The NRPB model incorporates some modifications from the model originally derived
from the Japanese data. First, it was noted that the data indicate a much higher risk
coefficient for childhood irradiation of the colon compared to that for adults, but that the data
on childhood exposures are, in this case, sketchy. To avoid the problem this poses (a
relatively large contribution from colon cancer with very little observational support), the
authors arbitrarily assigned the coefficient obtained for ages 20-29 ATB to the age cohort 0-
19. Second, risk estimates were given for several cancer sites (breast, liver, thyroid, and
bone) derived from epidemiological data collected on populations other than the bomb
survivors.
In the case of breast cancer, the authors argued that data on North American women
would be more relevant for the population of interest to them (women of the U.K.).
Accordingly, they adopted a risk model published in the Nuclear Regulatory Commission's
(NRC) Health Effects Model Document (Evans et al. 1985). This breast cancer model was
largely based on studies of women from the U.S. and Canada who received diagnostic or
therapeutic doses of x-rays. For thyroid cancer, the NRPB adopted a model contained in the
same NRC report, as well as in an NCRP report on thyroid cancer risks (NCRP 1985). For
liver and bone cancer, no actual age-specific models are given, but lifetime risk estimates are
developed on the basis of Thorotrast and radium exposed populations, respectively, assuming
an RBE of 20 for alpha particles.
No model is presented for calculating the risk at sites other than those listed. A risk
estimate for the "remainder" sites is calculated by taking the difference between the estimate
for total solid tumors and the estimated sum for listed solid tumors. This procedure only
makes sense in the context of uniform, whole-body irradiation.
ICRP As support for its recommendations in Publication 60 (ICRP 1991), the ICRP
has made use of risk calculations performed by Land and Sinclair (1991). For the most part,
these calculations make direct use of the age- and sex-specific relative risk coefficients listed
in Table 5A of RERF Report 11, Part 2 (neutron RBE=10) (Shimizu et al. 1988). The age at
exposure groups are 0-9, 10-19, 20-29, 30-39, and 40+ years. Land and Sinclair also use the
information in the RERF report to incorporate three additional sites into their model:
esophagus, ovary, and bladder. Age-specific risk coefficients for "residual" cancers are
obtained by subtraction of specified cancers from the total for the period of follow-up.
The risks are calculated for 5 reference populations: Japan, U.S., Puerto Rico, U.K.,
and China. Three methods are used to transport risk estimates from the study population of
bomb survivors to each of the 5 reference populations. The first (additive) involves a direct
-------
transport of age- and sex-specific absolute risk coefficients. The second (multiplicative)
involves a direct transport of relative risk coefficients. The third (NIH) is a hybrid of the
additive and multiplicative methods. For solid tumors, the total excess risk after the minimal
latency period is projected for the period of epidemiological follow-up (i.e., 10-40 y for the
RERF data) using the absolute risk coefficients of the additive model. However, it is
considered to be distributed over time after exposure as a multiple of the baseline rate. The
NIH model relative risk coefficient yields the same risk over the follow-up period as the
absolute risk model.This coefficient is then used to project lifetime risk in the same way as for
the multiplicative model. With the NIH method, the excess risk varies with age, in proportion
to the baseline rates in the population of interest, but only weakly reflects differences between
these baseline rates and those in Japan.
A peculiarity of the NIH projection model is that it can artificially introduce age-
dependent variability where none can be discerned from the data. For example, in view of the
very limited data on lung and colon cancer mortality among the atomic bomb survivors
exposed as children, authors have assigned equal risk coefficients for these cancers to the 0-9
y and the 10-19 y age groups, for both the additive and multiplicative models (Shimizu et al.
1990, Land and Sinclair 1991). However, if these age groupings are maintained, the derived
NIH projection model will contain significantly higher risk coefficients for the 0-9 group, and
a likely inflation of the risk estimates associated with childhood exposures. To avoid this
problem, the NIH risk coefficients for lung and colon are calculated on the basis of treating
the 0-19 y age group as a single group. The result is a decrease in the estimated risk for these
sites compared to previous calculations (ORP 1992).
In discussing the appropriateness of the three models, the authors note that the
multiplicative but not the additive model provides a reasonable approximation to the
epidemiological data. On the other hand, they also point out that little information is available
pertaining to the transfer of risk across populations. Hence, in developing organ-weighting
factors, they advocate an average of the multiplicative and NIH model projections.
BEIR V. The National Academy of Sciences BEIR V Committee conducted an
independent analysis of the ABSS data, supplemented by data on breast cancer induced by
medical irradiation (NAS 1990). The Committee developed several age- and sex-specific
relative risk models for calculating excess mortality due to these types of radiogenic cancers:
leukemia, respiratory, digestive, breast, and other; breast cancer incidence was also modeled
separately from breast cancer mortality. In each case, a preferred model was designated.
Unlike all the other reports discussed here, BEIR V incorporated time-since-exposure
dependence into its modeling. In transporting risk estimates from Japan to the U.S., BEIR V
assumes a multiplicative model: i.e., it assumes that the same risk models and coefficients
derived from a statistical fit to the atomic bomb survivor data can be applied to the U.S.
population with its own baseline cancer rates.
10
-------
For acute doses of 0.1 Gy or more, BEIR V derives a linear-quadratic model for
leukemia but a linear model for all other cancers. This finding is consistent with earlier
conclusions by the RERF group (Shimizu et al. 1988, 1990).
A number of problems can be identified pertaining to the preferred models and
estimates in BEIR V:
First, the definition of "excess" risk adopted in the report excludes radiogenic cancers
in individuals projected to die of cancer in the absence of the irradiation - this not only
understates the predicted health impact of the radiation, it creates disturbing anomalies such
as organ-specific risks that are negative or dependent on doses to other organs (C. Nelson,
unpublished results).
Second, in projecting radiogenic leukemia risk from the ABSS to the U.S. population,
chronic lymphocytic leukemias were erroneously included in the U.S. baseline rate although
this type of leukemia does not appear to be radiogenic (Gilbert 1991). This results in an
inflation of the leukemia risk estimate for the U.S.
Third, the BEIR V committee employed a multiplicative projection of breast cancer
risk from the Japanese to the U.S. Given the higher breast cancer rates in the latter, this
implies a higher radiogenic risk also. In fact, epidemiological data indicate the radiogenic
risks are similar in the two populations (Preston 1991).
Fourth, a sharp fall-off in risk with time after exposure is incorporated into the
respiratory cancer model. Although the model was developed from a statistical fit to the
ABSS data, the existence of such a fall-off is not strongly supported by the ABSS data
collected so far (NAS 1990). The main evidence for a temporal fall-off comes from the
ankylosing spondylitis study (Darby et al. 1987) for which good dosimetry is lacking and for
which there is a question of potential confounding by the disease. A striking consequence of
the model's fall-off is that the projected risk of irradiating the respiratory tract of children is
very low compared to adults. It is noteworthy that the irradiated spondylitic patients were all
at least 15 y old.
Fifth, BEIR V models digestive cancers from the ABSS as a single category. An
obvious disadvantage of this approach is that no guidance is provided on how to partition the
risk among the digestive organs - most importantly, between stomach and colon. By
combining the ABSS data in this way, BEIR V was able to obtain a more accurate and robust
statistical modeling of sex, age, and time dependencies. To some degree, the gain may be
illusory, however, since there is no guarantee that the various digestive organ risks should
vary in the same way with these model parameters. Additional error may be introduced in
transporting digestive cancer risks from Japan, where stomach cancer rates are high and colon
cancer rates are relatively low, to the U.S., where the reverse is true.
11
-------
Sixth, BEIR V fails to deal effectively with the issue of projecting risk estimates into
the domain of low doses and dose rates. On the one hand, a linear dose response for solid
tumors is advocated. On the other, it is suggested that at low dose rates risk estimates should
be reduced "by a factor of two to ten." Taken together, these two recommendations appear to
be at odds with basic radiobiological principles, which would seem to imply no dose rate
dependence at low doses (see Section II).
NUREG/CR-4214. Recently, the Nuclear Regulatory Commission has published a
revision to NUREG/CR-4214 (Abrahamson et al. 1991), that updates its health effects models
and their scientific bases. The estimation of radiogenic cancers due to low-LET radiation is
discussed in a chapter by Dr. Ethel Gilbert (1991).
While adhering to the general framework laid out in the previous report (Abrahamson
et al. 1989), revised models are developed in light of subsequent information, including the
new Japanese data and the analyses performed by the BEIR V, IMSCEAR 88, and ICRP 60
committees. Risk models are given for application to the general population for these cancer
sites: breast, lung, GI, thyroid, bone, skin, and other. In addition, models are given for in
utero cancer induction and benign thyroid tumor risks. Guidance is also included as to how to
partition the GI cancer risk among organs and how to separately calculate organ specific risks
for males and females.
Age-specific, constant relative risk models are recommended for all sites except
leukemia, bone, thyroid, and skin, for which additive risk models are proposed. The risk
coefficients do not generally represent statistical "best estimates" obtained from an analysis of
the epidemiological data. Compared to the other models discussed here, the
NUREG/CR-4214 models more explicitly incorporate expert judgment. Broadly speaking,
the models are designed to be as simple as possible, but to yield estimates of the risk on an
age and organ specific basis, which are reasonably central in view of the scientific
uncertainties outlined in Section II.
B. Comparison of Risk Projections
Three sets of models described above are quite similar: RERF, UNSCEAR 88, and the
ICRP (multiplicative model). For simplicity, we will eliminate the first two of these from
consideration.
Table 1 compares the site-specific projections of lifetime risks for a stationary U.S.
population, calculated using these five alternative sets of models: NRPB, BEIR V,
NUREG/CR-4214, ICRP (multiplicative), and ICRP (NIH). For purposes of this comparison,
the DDREF in each case is 1. (The choice of a DDREF will be discussed below.) The values
in the table are risk of cancer attributable to radiation, not just the "excess" risk calculated in
the BEIR V report. The cancer risks have been calculated for each model using 1980
decennial U.S. life table and force of mortality data. Hence,the model comparisons are not
12
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confounded by the effects of different sets of vital statistics or of using the specific age
distribution for a population in a particular year. As a consequence, the calculated risks differ
slightly from those in the referenced reports.
Leukemia. The numerical estimates of lifetime risk are quite similar, except for
BEIR V, which is about a factor of 2 higher. In part, this is due to the fact that BEIR V fails
to exclude chronic lymphocytic leukemias, which have not been shown to be radiogenic.
The NRC and NRPB recommend simple absolute risk models, which distribute the
risk evenly over a 25 or 38 y time period, respectively. In contrast, both ICRP's NIH model
and the BEIR V model for leukemia represent statistical fits to the temporal dependence in the
Japanese data. The NIH model, for example, predicts a lognormal temporal response, with a
shape dependent on age at exposure. The ICRP multiplicative model is least satisfactory in
Table 1. Low-LET U.S. population fatal cancer risk (deaths per 104 person-Gy)
for five models.
Cancer
Site
Nonleukemia1
Digestive
Esophagus
Stomach
Colon
Liver
Respiratory
Lung
Bone
Skin
Breast
Ovary
Bladder
Thyroid11
Leukemia
Remainder
NRPB BEIR V
966
1792 263
on T,
1 °f)
305 305
1 S"7
265
106 141
? n
78.0 33.5
6.3 22.5
81.7 16412
424U 329
NUREG/
CR-4214
297
14. 94
74. 34
1494
29. 74
149
8.1
1.8
46.2
32.210
49.610
6.4
89.9
248
ICRP
Mult.
966
45 73
6.2
29.3
381
305
265
9. 3s
2.09
116
47.5
64.0
7.5
110
374
NIH
773
434*
21.3
274
109
305
78.7
9.3s
2.09
32.7
25.0
38.9
7.5
97.9
276
13
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Totals:
Solid tumors14
All sites15
Nonleukemia +
leukemia16
812 754 1293
977 845 1403
1048 1076
855
953
871
Notes for Table 1.
General: All risks are calculated for a stationary population using 1980 decennial U.S. vital
(see Appendix A.) The DDREF is one. Risks not in italics are calculated directly
from the models given in the references. Those in italics are sums of sites or make use
of supplementary information.
Notes for Table 1. (Cont.)
1. NRPB and ICRP provide explicit models for all solid tumor (nonleukemia) mortality
risk. These nonleukemia models presume a uniform dose to all tissues.
2. Sum of stomach, colon, and liver risks.
3. Sum of esophagus, stomach, colon, and liver risks.
4. NUREG/CR-4214 esophagus, stomach, colon, and liver risks are 0.05, 0.25, 0.50, and
0.10 times the digestive risk, respectively.
5. NRPB, BEIR V, and ICRP liver risks are the corresponding alpha dose risks divided
by anRBEof 10.
6. NRPB alpha dose bone risk divided by an RBE of 10.
7. BEIR V incidence value multiplied by a lethality factor of 0.7 for comparability.
8. ICRP alpha dose bone risk divided by an RBE of 10.
9. ICRP also recommends this value for the low-dose, low-dose-rate region.
10. NUREG/CR-4214 ovary and bladder risks are 0.13 and 0.20 times the remainder risk,
respectively.
11. Except for BEIR V, all thyroid risks are based on NCRP Report 80 (NCRP 1985).
12. The linear coefficient of the BEIR V linear-quadratic model for leukemia has been
doubled for comparability with the other model estimates.
14
-------
13. NRPB remainder risk is calculated as the nonleukemia risk less the sum of the
stomach, colon, liver, lung, bone, breast, and thyroid values.
14. Sum of site specific risks for each model as follows:
BEIR V: Digestive, respiratory, breast, and remainder.
NUREG/CR-4214: Digestive, lung, bone, breast, thyroid, and remainder.
ICRP: Esophagus, stomach, colon, lung, breast, ovary, bladder, and remainder.
15. Sum of all solid tumor and leukemia risks (BEIR V, NUREG/CR-4214, and ICRP,
only).
16. Sum of nonleukemia and leukemia risks (NRPB and ICRP, only).
15
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describing the temporal response, concentrating the excess risk at the end of the expression
period, opposite to what is actually observed.
Breast. A major issue with respect to breast cancer is in the transport of risk from Japan
to the U.S., where the baseline rates are much higher. For example, the ICRP multiplicative and
NIH projections of breast cancer risk for the U.S. differ by almost a factor of 4 (Land and Sinclair
1991). The NRPB and NUREG/CR-4214 models do not have this problem since they are based
on North American data. These model projections agree fairly well with ICRP's NIH projection
but are substantially lower than the projection made with ICRP's multiplicative model.
Lung. Lung cancer risks are highly uncertain due to uncertainties in age and temporal
dependencies, and in transporting risk from Japan to the U.S., where the baseline lung cancer
rates are considerably higher. The NRPB relative risk and ICRP multiplicative models are
identical and project the highest risks; these models both presume that the age-specific constant
relative risk coefficients derived from the Japanese data apply to other populations. The BEIR V
respiratory model yields a lower estimate because of its temporal fall-off. ICRP's NIH projection
is lower because of the difference between Japanese and U.S. lung cancer rates. The
NUREG/CR-4214 model produces a higher estimate of risk for childhood exposures but a
lifetime risk projection similar to that from BEIR V or an average of the two ICRP model
projections.
Digestive. All of the stomach and colon cancer risk models are constant relative risk
models derived from the ABSS data, each incorporating a substantially higher coefficient for the
younger age-at-exposure groups. Nevertheless there are important differences among them. For
example, as shown below from a comparison of Land and Sinclair's multiplicative and NIH
projections (1991), the results for stomach and colon are very sensitive to how one transports the
risk from Japan to the U.S.
Table la. Low-LET U.S. population risks (deaths per 10 4 person-Gy) of stomach and
colon cancer for two ICRP Publication 60 projection models.
Cancer type
Stomach
Colon
Multiplicative
Male Female
32
223
45
602
Transport model
Male
221
178
NIH
Female
333
143
These results highlight the large colon cancer contribution in the multiplicative model -
especially for females. As noted previously, the NRPB reduced its colon cancer risk estimate by
decreasing the risk coefficient for childhood exposures. It is also instructive to compare
estimates of total digestive cancers made with the BEIR V model and the ICRP multiplicative
model. (See Table 1.) Although both are age-specific constant relative risk models, which
16
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transport relative risk coefficients directly from the bomb survivors to the U.S. population, the
former projects only about 65% of the digestive cancer risk. This seems to be largely a
consequence of BEIR V's modeling digestive cancers as a single group, coupled with the
differences in baseline stomach and colon cancer rates between Japan and the U.S. The same
concern would probably apply to Gilbert's estimate of digestive cancer risk.
Other/Remainder. Since the sites for which risk estimates are developed differ, the sites
included in the remainder category differ among the sets of models considered here. The NRPB
does not develop a risk model for this category; instead the projection is obtained as a difference
between the model projection for total (nonleukemia) cancers and for modeled (nonleukemia)
sites. This approach yields a higher estimate for the remainder sites than obtained by modeling
the risk for these sites directly. The lack of an explicit model and the assignment of about 40% of
the total risk to this category might be regarded as weaknesses of the NRPB approach.
Miscellaneous Specific Organs. Each of the reports cites high-LET Thorotrast data as the
basis for its liver cancer risk estimate. Assuming an RBE of 10, for the purpose of this
comparison, all the models yield a liver cancer risk estimate of 30 per 104 Gy. The reports
recommend bone cancer risk estimates derived from Ra-224 studies. Based again on an assumed
RBE of 10 and a bone cancer lethality of 0.7, the estimates are in reasonably good agreement
with one another.
ICRP 60 recommends a risk estimate for skin cancer incidence of 980 per 104 Gy; 0.2% of
these cancers are assumed to be fatal. The NRC bases its skin cancer model on ICRP 60 and,
therefore, projects essentially the same risk. (The two reports differ on the risk at low dose rates;
the ICRP makes no adjustment in extrapolating from high dose rates, whereas the NRC applies a
DDREF of 2.) The NRPB employs an older ICRP model, which projects about 30% of the
incidence but 150% of the mortality as ICRP 60.
The NRC, NRPB, and ICRP 60 all calculate thyroid cancer using the absolute risk model
recommended in NCRP 80 (NCRP 1985). From the Israeli Tinea Capitis data (Ron and Modan
1984), BEIR V develops its own (relative risk) model, which projects about 3 times higher risk
than the NCRP model.
The ICRP estimates risk for the bladder and ovary, using the age-average relative risk
coefficients derived from the ABSS data. None of the reports provides an estimate for kidney,
which receives a relatively high dose from certain radionuclides, especially uranium. The ABSS
shows a non-statistically-significant elevation in kidney cancer associated with radiation. The
existence of a radiogenic risk for this site seems to be confirmed by the cervical cancer study
(NAS 1990). The estimate of kidney cancer risk here is based on the ABSS kidney data. An
alternative would be to calculate the risk using a model developed for remainder sites. A
preliminary examination indicates this approach would yield roughly similar results.
C. Extrapolation to Low Doses and Dose Rates
17
-------
As discussed in Section IB, it is widely assumed that the risks of low-LET radiation are
reduced by a DDREF at low doses and dose rates. For leukemia, BEIR V advocates a linear-
quadratic model, consistent with a DDREF of 2. For other sites, the report recommends no
reduction in risk for low, acute doses but suggests that a reduction by a factor of 2 or more may
be appropriate at low dose rates. ICRP 60 contains a fairly detailed discussion of the issue [ICRP
1991: pp. 108-112] and recommends that a DDREF of 2 be used for radiation protection purposes
at this time. The NRC concurs with the ICRP recommendation, except in the case of breast or
thyroid, for which a DDREF of 1 is adopted. The NRPB recommends a DDREF of 1, 2, and 3,
respectively, for thyroid, breast, and all other sites.
D. High-LET Risk Estimates (RBE)
The ICRP (1991) assumes that alpha radiation produces 20 times the risk, per unit
absorbed dose (Gy or rad), as low-LET radiation. This relationship is meant to hold in the limit
of low doses and dose rates. Thus, it already takes into account the assumed DDREF of 2 for
low-LET radiation; at high acute doses, the RBE would be 10. This must be kept in mind both
when calculating alpha particle risks using models derived from low-LET epidemiological data
and when estimating low-LET risks (for bone and liver) based on high-LET studies. The NRC
and NRPB reports also assume that at low doses the risk per Gy from alpha particles is 20 times
that from gamma rays.
IV. Methodology for Estimating Radiogenic Cancer Risks
A. Selection of Risk Models
In our opinion, the models developed by Gilbert for the NRC, and by Land and Sinclair
for the ICRP, are preferable for EPA's needs to the others considered here. BEIR V reveals novel
features of the Japanese data, but for reasons outlined above, was not deemed to provide a good
basis for EPA's nominal "best estimates" of radiogenic cancer risk. The NRPB models are very
similar to the ICRP multiplicative models, but the NRPB makes a somewhat arbitrary adjustment
to its colon cancer model for childhood exposures and appears deficient in its handling of the
"remainder" category. It could also be argued that, in view of the uncertainties, weight should be
given to an "additive transport" of risk estimates, where the radiogenic risk is assumed to be
insensitive to differences in baseline cancer rates between populations. An additive type of
transport (such as that provided by ICRP's NIH projection) leads to somewhat lower estimates of
risk for most radionuclides, especially for those retained in the lung. (See Table 1.)
To a large extent, the ICRP approach reflects a well defined, predetermined procedure in
which the excess cancer mortality observed in the A-bomb survivors, by site, age, and sex, are
used to calculate risk in the U.S. population. However, Land and Sinclair express no preference
between the multiplicative and NIH methods of projecting risk from one population to another,
and the ICRP ended up adopting an arithmetic average of the two methods for each site. The
NRC approach, on the other hand, rests to a degree on judgments, reached after an examination of
18
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all the epidemiological data and a consideration of alternative modeling approaches, on a site
specific basis.
Land and Sinclair's models involve more detailed age and site specific information. For
example, Gilbert does not provide age and sex-specific risk coefficients for individual types of
digestive cancers. Instead she develops a model for uniform irradiation of the digestive organs
and then indicates what fraction of the total risk should be assigned to each. Since the age and
sex dependencies differ among the various digestive organs, considerable manipulation is
required to obtain organ-specific relative risk coefficients that will result in calculated lifetime
risks partitioned as Gilbert describes. Some might prefer Gilbert's approach, however, since it
points up the sketchiness of the organ-specific epidemiological data. The BEIR V Committee,
for this reason, also chose to model digestive cancers together as a single class.
Similar considerations apply with respect to the dependence of risk on age at exposure,
where the ICRP incorporates a more detailed breakdown. Due probably in large part to sampling
errors, the ICRP models display some anomalous variations in risk with age at exposure. Such
variations are smoothed out in the NUREG/CR-4214 models, but significant real features of the
age dependence may be lost in the process.
Gilbert's breast cancer model has the advantage of being derived from North American
data; however, Land and Sinclair's NIH projection of lifetime risk for breast cancer is comparable
to Gilbert's and, qualitatively, exhibits the same sharp decrease in risk with age at exposure.
Conclusions. Having reviewed the scientific information and models outlined here, we
have chosen to base the risk estimates for most organs on Land and Sinclair's models. (A notable
exception is breast cancer where Gilbert's model is adopted.) In view of the uncertainty over the
transport of risk estimates from Japan to the U.S., we have adopted a methodology, described
below, which yields risk estimates intermediate between the multiplicative and NIH projections
of Land and Sinclair. This methodology has been reviewed and judged acceptable by EPA's
Radiation Advisory Committee (Loehr and Nygaard 1992).
B. Transport of Risk Estimates from Japan
Land and Sinclair present two models for calculating risk in a population, differing in
how risk estimates are to be transported from the Japanese atomic bomb survivor study (ABSS)
population. Both models assume a constant excess relative risk coefficient beginning 10 years
after an exposure and continuing throughout the rest of life for each cancer site (except for
leukemia). One model (multiplicative) assumes that the relative risk coefficient is the same
across populations. The other (NIH) assumes that the relative risk coefficients for the target
population should yield the same risks as those calculated with the additive risk coefficients from
the original population over the period of epidemiological follow-up (excluding the minimal
latency period.) These excess relative risk coefficients are then used to project the risk over the
remaining years of life. Projections made for the U.S. using the NIH model are much less
sensitive to differences in site specific baseline rates between Japan and the U.S. than are those
using the multiplicative model.
19
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Data on North American women irradiated for medical purposes indicate a similar
attributable risk for breast cancer induction as the ABSS study data, despite the substantially
higher breast cancer rates found in the U.S. or Canada, compared to Japan. For breast cancer,
therefore, the NIH model projection agrees with observation better than the multiplicative model
projection. Comparative data on other radiation-induced cancers, however, are generally lacking
or are too weak to draw any conclusions regarding the transportation of risk estimates from the
ABSS population to the U.S.
Both transportation models have a degree of biological plausibility. For example, the
multiplicative model is consistent with the hypothesis that radiation acts as an initiator while the
factors responsible for differences in baseline rates act as promoters. Alternatively, if both
radiation and these factors act independently, but at the same stage in the carcinogenesis process,
their effects should be additive, and radiation risks should be similar between populations despite
differences in baseline rates. In actuality, the situation is likely to be more complex than either of
these alternatives, leading to an interaction that is intermediate between multiplicative and
additive. In this case, the radiation risk for the U.S. population may lie between the
multiplicative and NIH projections from the ABSS.
Given the uncertainty in the transportation of risk across populations, we adopt here a
model in which most age and site specific risk coefficients are taken to be geometric means of the
corresponding coefficients from the multiplicative and NIH models of Land and Sinclair. Our
choice of a geometric mean coefficient (GMC) model reflects a judgment regarding the
distribution of uncertainty associated with the transportation of risk. We believe this approach
provides a reasonable central estimate of the risk, by organ and by age at irradiation. While
giving weight to both the multiplicative and NIH approaches, it tends to deemphasize extreme
values (e.g., the multiplicative projection for colon cancer) which may reflect large extrapolations
based on a few excess cancers observed among those exposed as children. (Note: since the risk
coefficients for the respective models are age and sex specific, the average lifetime risks
calculated with the GMC model are, in general, not the same as the geometric means of the
average lifetime risks calculated with the multiplicative and NIH models.)
Risk estimates for esophagus, stomach, colon, lung, ovary, bladder, leukemia, and
residual, derived using the multiplicative, NIH, and geometric mean projection models are given
in Table 2. Shown for comparison are the estimates derived using Gilbert's models for these
same organs. Gilbert's models were, as discussed previously, developed primarily from the same
epidemiological data, but incorporate the author's judgment as to what constitutes a reasonable
central estimate of the risk in light of all available information and uncertainties. As can be seen
from Table 2, the GMC model yields lifetime risks that agree well with those calculated using
Gilbert's models.
20
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Table 2. Comparison of fatal cancer risks (deaths per 10 4 person-Gy) for the
geometric mean coefficient (GMC) projection model with Land & Sinclair
(ICRP) and NUREG/CR-4214 models.
Cancer
type
Esophagus
Stomach
Colon
Lung
Breast
Ovary
Bladder
Leukemia
Residual
Total
Land &
Mult
16.2
29.3
381
265
116
47.5
64.0
110
374
1403
£ Sinclair
NIH
21.3
274
109
78.7
32.7
25.0
38.9
97.9
276
953
GMC
18.1
88.7
196
143
60.8
33.2
49.7
99.1
297
986
NUREG/
CR-4214
14.9
74.3
149
149
46.2
32.2
49.6
89.9
238
844
Notes for Table 2.
Model risks are calculated with 1980 U.S. vital statistics for a DDREF of one.
Values in roman type are calculated directly from the models given in the references.
Those in italic type are sums of sites or make use of supplementary information.
The sex and age at exposure specific risk model coefficients for the GMC model are
the geometric means of the corresponding coefficients for the Land and Sinclair (1991)
multiplicative and NIH risk transportation models (see text). Note that since the risk model
coefficients are age and sex specific, the average lifetime risks for the GMC model are not
simply equal to the geometric mean of the risks for the corresponding multiplicative and NIH
models.
The residual risk shown for the NUREG/CR-4214 model (Gilbert 1991) includes the
balance of the digestive site risk.
21
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Table 3. Residual site mortality risk coefficients for the additive and
multiplicative projections of Land and Sinclair (1991).
Age group
(y)
0-9
10-19
20-29
30-39
40+
Additive
(10-4perGy-y)
Male Female
0.096
2.28
5.42
4.18
2.09
1.73
1.60
4.98
4.16
2.96
Multiplicative
(per Gy)
Male Female
0.091
0.762
0.682
0.246
0.052
2.370
0.876
0.969
0.403
0.151
C. Adjustments to Models
For all sites except leukemia, the same temporal response was employed by Land and
Sinclair in both the multiplicative and NIH models; i.e., a constant relative risk with a 10 y
minimal latency period. For leukemia, the temporal dependencies are different. The
multiplicative model presumes a constant relative risk over an expression period extending
from 2 y to 40 y after exposure; the NIH model, on the other hand, presumes a lognormal
variation in relative risk with a width dependent on the age at exposure (National Institutes of
Health 1985). Averaging the risk coefficients corresponding to these two different temporal
models is nonsensical. Before taking the geometric mean of the model coefficients, therefore,
we first adjusted the multiplicative model so that it would exhibit the same form of temporal
response as the NIH model, holding constant the lifetime risk for a given age at exposure.
The NIH temporal response was chosen over that of the multiplicative model because it
conforms better to the epidemiological data. [The BEIR V Committee preferred a model
incorporating two steps, with the temporal width of the steps dependent on age at irradiation
(NAS 1990)].
In view of the statistical limitations in the data, analysts have assumed a constant ratio
of male to female risk coefficients across ages for all specific cancer sites (Shimizu et al.
1988, Land and Sinclair 1991). Land and Sinclair did not, however, constrain their models
for "residual" cancers in this way. As shown in Table 3, this leads to apparent anomalies in
the risk coefficients for the 0-9 y age group. Due probably to large sampling errors in this
group, the estimated risk coefficient appears to be low for males but high for females.
Accordingly, we have replaced the 0-9 y values given by Land and Sinclair with those given
for the age group 10-19 y. The overall effect of this change on U.S. population risk estimates
is very slight: about 10% for the residual organ risk and about 2% for the uniform whole body
risk.
22
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D. Other Cancer Sites
For all the sites listed in Table 2, a statistically significant excess of cancer mortality
(at the 95% confidence level) has been observed in the ABSS (Shimizu et al. 1988). The
excess for breast cancer is also statistically significant, but it seems preferable to base the risk
estimate on the available North American data, bypassing the question of transporting risk
estimates across populations. For kidney, the ABSS data are suggestive of a risk but narrowly
miss statistical significance. The existence of a radiogenic kidney cancer risk is, however,
borne out by the cervical cancer study (NAS 1990; Boice et al. 1988). Given the importance
of the kidney as a possible target organ for uranium and some other radionuclides, we have
developed a risk estimate for this site based on the ABSS data. We also present risk estimates
for liver, bone, and thyroid.
Breast. Using the multiplicative model projection from the Japanese data, a breast
cancer (mortality) risk of 116x 10"4 Gy"1 is calculated. The NIH projection is 32.7x 10"4 Gy"1.
Gilbert's model, based on the North American data, yields a lifetime risk of 46.2xlO"4 Gy"1,
much closer to the NIH projection. The geometric mean model projection (60.2x 10"4 Gy"1)
also agrees reasonably well with Gilbert's model estimate.
Kidney. The age- and sex-averaged excess relative risk (ERR) coefficient for kidney
cancer mortality from the ABSS is 0.5829 Gy"1, with a 90% confidence interval of (-0.09,
1.94). The corresponding absolute risk (AR) coefficient from Table 2B of Shimizu et al.
(1988) is 9x 10"6 (Gy y)"1. However, these values are based on shielded kerma rather than on
organ-absorbed dose as needed for the risk model. Risk coefficients based on kidney-
absorbed dose were calculated assuming that the ratio of the organ-absorbed dose ERR
coefficients to the shielded kerma values is the same as for the bladder. The bladder-absorbed
dose ERR from Table 1 of Land and Sinclair (1991) is 1.3395 Gy"1 and the corresponding
shielded kerma value from Table 2-27 of Shimizu et al. (1988) is 1.1343 Gy"1. Accordingly,
the kidney-absorbed dose ERR and AR coefficients for kidney cancer are calculated to be
0.6883 Gy"1 and 1.06xlO"5 (Gy y)"1, respectively. Using this AR coefficient, the NIH model
ERR coefficient is calculated to be 0.2663 Gy"1. The geometric mean model ERR projection
(see Table 4) is 10.9 kidney cancer deaths per 104 Gy, about 20% of bladder cancer mortality.
Liver. Based on Thorotrast data, BEIR III and BEIRIV estimate the risk of fatal liver
cancer induction by alpha particle radiation to be 300x 10"4 Gy"1 (NAS 1980, 1988).
Assuming an RBE of 10 for alpha particles (see below), a low-LET risk of 30x 10"4 Gy"1 is
derived. For purposes of calculation, we have adopted a constant relative risk model
independent of age-at-exposure and sex.
Bone. As a basis for estimating radiation-induced bone sarcomas, we adopt BEIR IV's
estimate of 2x 10"2 Gy"1 for alpha irradiation by 224Ra (NAS 1988), derived from the work of
Mays and Speiss (1984). This estimate, however, refers to average skeletal dose rather than
endosteal cell dose (NAS 1980, 1988; Mays and Speiss 1984). Taking the endosteal dose to
be 7.5 times that of the whole skeleton, the alpha risk estimate is 2.7x 10"3 cases per Gy; for
23
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low-LET, the risk is again assumed to be 10 times lower (2.7x 10"4 Gy"1). About 70% of bone
sarcomas are fatal (ICRP 1991); hence, for mortality, the low-LET risk estimate is 1.9xlO"4
Gy"1. The ICRP 60 estimate of bone cancer risk is higher because it confuses endosteal and
average skeletal doses (ICRP 1991, Puskin et al. 1992); unfortunately, the NRC erroneously
adopted the ICRP estimate (Gilbert 1991). In a subsequent report (Gilbert 1993), the NRC
has addressed this error. Following BEIR III (NAS 1980), a constant absolute risk model was
selected for projecting risk, with an expression period extending from 2 to 27 years after
exposure.
Thyroid. Thyroid risk estimates are based on NCRP Report 80 (NCRP 1985). Both
the NRC and the ICRP have also adopted this approach (Gilbert 1991, ICRP 1991). The
estimated fatality risk is calculated to be 6.4* 10"4 Gy"1, 1/10 the incidence risk. The estimated
incidence and mortality risks are each reduced by a factor of 3 in the case of exposures to
iodine-125, -129, and -131. [This reduction includes the effect of lowered dose rate on the
risk, as well as possible other factors; hence, the DDREF of 2 applied to organ specific risk
estimates (see below) should not be applied in the case of these radioiodine exposures.]
In addition to thyroid cancers, radiation has been found to induce benign thyroid
nodules. Maxon et al. (1985) has estimated that: for external X or gamma rays, the risk of a
radiogenic thyroid nodule is about 3.7 times that of a radiogenic thyroid cancer; for iodine-
131, the nodule risk is about 2.1 times the cancer risk.
Skin. Estimates of skin cancer risks are highly uncertain, but the mortality risk is
known to be relatively low. For acute exposures, we have adopted the mortality risk estimate
in ICRP 60, 2x 10"4 Gy"1; however, in contrast to ICRP, we have applied a DDREF of 2 in
estimating the skin cancer risk at low doses and dose rates (see below).
Radiation induced skin cancers are of two types: basal cell and squamous cell
carcinomas. The former are nearly all curable, perhaps about 99.99%, but about 1% of the
latter may be fatal (ICRP 1991, 1992). As an upper bound, the ICRP estimates that one of six
radiogenic skin cancers would be squamous cell. Based on these considerations, the ICRP
estimates that only 0.2% of all radiation-induced skin cancers are fatal (ICRP 1991, 1992).
The great majority of radiation induced skin cancers should be easily curable and
result in little trauma for the patient (ICRP 1992). However, left unattended, some of these
cancers, though still not fatal, may require more intensive medical treatment or be disfiguring.
In the absence of data on the fraction of radiogenic skin cancer cases that might be regarded
as serious, we have excluded nonfatal radiogenic skin cancers from the estimates of risk.
24
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E. Summary of Site Specific Cancer Mortality Risk Estimates
Table 4 summarizes an extended set of organ risk estimates calculated using the
revised EPA set of models described above, and using the NUREG/CR-4214 and ICRP
models (Gilbert 1991, Land and Sinclair 1991, ICRP 1991). A detailed listing of age- and
site-specific risk coefficients for the EPA revised models is given in the Appendix. For most
sites, the ICRP estimates reflect the multiplicative and NIH projections of the ABSS estimates
to the U.S.; the basis for ICRP estimates of risk for liver, bone, thyroid, and skin are described
separately in ICRP 60 (ICRP 1991). For comparison purposes, a DDREF of 1 is again
assumed for all sites. The resulting whole body risk calculated using the revised EPA set of
models is 9.72xlO"2 fatal cancers per person-Gy.
F. Incidence Risk Estimates
To obtain estimates of radiation-induced cancer incidence, each site specific mortality
risk estimate is divided by its respective lethality fraction, i.e., the fraction of radiogenic
cancers at that site which are fatal. Aside from thyroid cancer, the lethality fraction is
generally assumed to be the same for radiogenic cancers as for the totality of other cancers at
that site. [An exception is sometimes made for thyroid cancer because the radiogenic cases
are confined to specific types, which have a somewhat lower than average lethality (NCRP
1985)].
Table 5 reproduces a list of lethality fractions recommended by ICRP 60. Two
limitations with respect to this list should be noted. First, the values reflect only cancers
appearing in adults. It appears that leukemia is now often curable in children. However, most
radiogenic leukemias in the atomic bomb survivors occurred before successful treatment
became available. Hence, the leukemia mortality risks derived from the Japanese may more
properly reflect incidence rather than mortality for children. Second, the values listed in
Table 5 are, in part, judgments, since there is no completely reliable way to determine long
term survival based on current (or future) treatment modalities. As in the case of childhood
leukemia, however, improved survival would imply an overestimation of mortality risks
rather than an underestimation of incidence.
Recognizing these limitations, we calculate site specific incidence using the ICRP 60
lethality fractions, except for skin, which is projected by this method to contribute most of the
nonfatal cancers induced by uniform whole body irradiation. At least 83% are basal cell
carcinomas (» 0.01% lethality) and the remainder squamous cell carcinomas (» 1% lethality).
The incidence estimate employed here reflects only fatal cases and omits the much larger
number of nonfatal cases, most of which are easily treated (see Section D).
25
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Table 4. Site specific mortality risk estimates (deaths per 104 person-Gy) for proposed
EPA model compared with those for ICRP and NUREG/CR-4214 models (male and
female combined, DDREF=1).
Cancer
site
Esophagus
Stomach
Colon
Liver
Lung
Bone
Skin
Breast
Ovary
Bladder
Kidney
Thyroid
Leukemia
Residual
Total
ICRP
Mult
16.2
29.3
381
30
265
9.3
2.0
116
47.5
64.0
7.5
110
325
1403
NIH
21.3
274
109
30
78.7
9.3
2.0
32.7
25.0
38.9
7.5
97.9
227
953
EPA
18.1
88.7
196.4
30.0
143.2
1.9
2.0
46.2
33.2
49.7
10.9
6.4
99.1
246.2
972.0
NUREG/
CR-4214
14.9
74.3
149
29.7
149
8.1
1.8
46.2
32.2
49.6
6.4
89.9
193
844
Notes for Table 4
The ICRP risk estimates for liver, bone, skin, and thyroid are general (rather than sex-
specific) estimates from ICRP Publication 60 (ICRP 1991).
For those sites above (other than breast) that are also shown in Table 1, the proposed EPA
risk model coefficients are the same as those for the geometric mean coefficient (GMC)
model. If the GMC model for the female breast had been used, the breast cancer risk would
be 118.5 and 60.2 per 104 Gy for the female and combined male and female populations,
respectively. The total risk estimates would change accordingly.
The residual risk estimate is different from that in Table 1 because it does not include risks
for sites (viz., liver, bone, skin, kidney, and thyroid) that are specifically estimated.
26
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Table 5. Lethality data for adult cancers by site.
Cancer site
Esophagus
Stomach
Colon
Liver
Lung
Bone
Skin
Breast
Ovary
Bladder
Kidney
Thyroid
Leukemia (acute)
Residual
Lethality
fraction k
0.95
0.90
0.55
0.95
0.95
0.70
0.002
0.50
0.70
0.50
0.65
0.10
0.99
0.71
Notes for Table 5.
Lethality fractions (mortality :morbidity ratios) except for residual are from Table B-19
of ICRP Publication 60 (ICRP 1991). Residual lethality fraction is calculated from the
corresponding value of (2-k) in Table B-20 of the same document.
G. Dose and Dose Rate Effectiveness Factor (DDREF)
The issue of DDREF was discussed in Section II.B. After reviewing the information
and arguments pertinent to the choice of a DDREF, we concluded that a value of 2.0 provides
a reasonable "best estimate." The Agency's Radiation Advisory Committee agreed "that this
choice is reasonable and ... consistent with current scientific judgment" (Loehr and Nygaard
1992). A DDREF of 2 has recently been adopted by the ICRP (1991), as well as by other
organizations (Gilbert 1991, CIRRPC 1992), and is expected to be widely applied for
purposes of risk assessment and radiation protection worldwide. The uncertainty in the
DDREF will be factored into EPA's assessments of uncertainty in radiation risk, however.
27
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The DDREF will be applied to all organ-specific risks except for the breast. There is
epidemiological evidence that dose fractionation has little or no effect on risk to the breast
(NAS 1988); moreover, the risk model we have adopted is based mainly on fluoroscopy
studies in which the doses were in fact delivered as multiple small fractions (NAS 1990,
Gilbert 1991). Hence, we have adopted a DDREF of 1 for breast cancer. This choice
assumes that the risk (per unit dose) of highly fractionated exposures approximates the risk at
low doses and dose rates.
The conditions under which the DDREF should be applied remain to be defined.
Although the biological mechanisms are not yet elucidated, according to current thinking: at
low doses, repair is maximal, and the unrepaired DNA damage reflects single track events; at
higher (acute) doses, repair decreases due to damage caused by multiple tracks passing
through the cell nucleus in close temporal proximity. It would appear that repair efficiency is
maximal for all doses below about 0.2 Gy (NCRP 1980). It also appears that DNA repair is
essentially completed within a few hours after radiation-induced damage (Wheeler and
Wierowski 1983, Ullrich et al. 1987). Consequently, maximum repair efficiency should occur
so long as the dose does not exceed 0.2 Gy over a few hours. In view of these considerations,
we have adopted UNSCEAR's recommendation that the DDREF should be applied whenever
the total dose is below 0.2 Gy or the dose rate is below 0.1 mGy/min (UNSCEAR 1993).
H. Alpha Particle RBE
With the exception of radiation-induced breast cancer and leukemia, we have followed
the ICRP recommendation (ICRP 1991) and assumed that the RBE for alpha particles is 20, in
comparison to low-LET radiation at low doses and dose rates. Where the comparison is made
against acute high doses of low-LET radiation, however, a value of 10 will be assumed for the
alpha particle RBE. Thus the low-LET radiation DDREF of 2 we have used for these cancers
is implicitly incorporated into the RBE value for alpha radiation.
For breast cancer induction, a DDREF of 1 has been adopted (see above). Therefore,
the RBE will be independent of dose and dose rate. Since there is no DDREF correction of
the low-LET breast cancer risk estimates at low doses and dose rates, it is assumed that the
acute high dose RBE of 10 is also applicable to breast cancer at low doses and dose rates.
There is evidence that alpha particle leukemia risks estimated on the basis of an RBE
of 20 are too high (EPA 1991). For this reason, an alpha particle leukemia risk estimate of
S.QxlO"3 Gy"1 is employed, consistent with the available high-LET epidemiological data (NAS
1988, EPA 1991). Quantitatively, this would correspond to an RBE of 1 for this site (relative
to low dose, low-LET radiation). This is not to imply that alpha radiation is no more
carcinogenic than low-LET radiation in inducing leukemia. At least in part, the lower than
expected leukemia risk produced by alpha emitters may result from a nonuniform distribution
of dose within the bone marrow (i.e., average doses to sensitive target cells may be
substantially lower than calculated average marrow doses). Thus the RBE of 1 should be
28
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regarded as an "effective RBE," that reflects factors other than just the relative biological
sensitivity to high- and low-LET radiations. Finally, we recognize that since the spatial
distribution of the dose within the marrow will differ among alpha emitters, depending on the
distribution of the radionuclide within bone and the energies of the emitted alpha particles, the
effective RBE may be radionuclide dependent. However, this issue cannot be resolved with
current data.
Our radon decay product risk estimates will continue to be based directly on radon
epidemiological data. Currently, EPA's radon risk estimate is 2.2x 10"4 fatal lung cancers per
working level month (EPA 1992, Puskin 1992).
I. Summary of Revisions to EPA Low Dose Risk Estimates
Table 6 lists the revised EPA site specific cancer risk estimates (incidence and
mortality), applicable at low doses and dose rates. For comparison, the corresponding
estimates from EPA's 1989 Background Information Document for the Radionuclides
NESHAPS are shown (EPA 1989). These revised EPA site specific mortality risk estimates
are generally quite close to those in NUREG/CR-4214 (Gilbert 1991).
For low-LET radiation at low doses or dose rates, the lifetime fatal cancer risk estimate
associated with uniform, whole-body irradiation of the U.S. population has increased by 24%,
from 392 to 509 per 104 person-Gy. This value is similar to those determined by NRPB,
ICRP, and NRC, and BEIR V, assuming a DDREF of 2. It is estimated that about 70% of all
cancers induced by whole-body irradiation are fatal (nonfatal skin cancers excluded),
corresponding to an incidence risk estimate of 7.61><10"2 Gy"1. These increases occur despite
the change from a DDREF of 1 in NESHAPS to a value of 2 here; without this change, the
risk estimates would have more than doubled.
It should be emphasized that EPA's previously published lifetime risk estimates for
chronic radionuclide exposures (EPA 1989) cannot be simply scaled by the ratio of whole-
body risk estimates to arrive at risk estimates based on the revised models. In general, such
exposures produce a non-uniform dose distribution within the body, which may also be time
varying. As a result, estimation of revised radionuclide specific risks requires more detailed
calculations.
29
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Table 6. EPA low dose, low dose rate cancer risks (10 per Gy).
Cancer
site
Esophagus
Stomach
Colon
Liver
Lung
Bone
Skin
Breast
Ovary
Bladder
Kidney
Thyroid
Leukemia
Remainder
TOTAL
Mortality
NESHAPs Revised
9.1
46.0
22.9
49.6
70.1
2.5
55.4
11.8
5.9
6.4
44.8
67.8
392.1
9.0
44.4
98.2
15.0
71.6
0.9
1.0
46.2
16.6
24.9
5.5
3.2
49.6
123.1
509.1
Morbidity
NESHAPs Revised
9.1
60.1
42.9
49.6
74.5
2.5
142.0
21.4
21.4
64.3
44.8
90.5
623.0
9.5
49.3
178.5
15.8
75.4
1.3
1.0
92.5
23.7
49.7
8.4
32.1
50.1
173.4
760.6
Notes for Table 6.
The Dose and Dose Rate Effectiveness Factor (DDREF) is 1 for breast and 2 for all
other sites. These risk coefficients are applicable to all doses less than 200 mGy and for total
doses greater than 200 mGy from dose rates less than 0.1 mGy/min. The revised model
morbidity estimate for skin shown is for fatalities only. The entire morbidity risk for skin
would be about 500 times greater. The thyroid morbidity risk includes only malignant
neoplasms and does not include benign tumors or nodules. For most cancer sites, high-LET
(alpha particle) risk estimates have increased by more than the corresponding low-LET
estimates, reflecting the change in RBE from 8 to 20, which comes from adopting a DDREF
correction at low doses of low-LET radiation (EPA 1989, NCRP 1990, ICRP 1991).
For occupational exposures, the mortality and incidence risk estimates are 3.94xlO"2
Gy"1 and 5.67><10"2 Gy"1, respectively. (Occupational risks were calculated assuming a
constant exposure rate for both sexes between the ages of 18 and 65.)
30
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31
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References
S. Abrahamson, M. Bender, S. Book, C. Buncher, C. Denniston, E. Gilbert, F. Hahn, V.
Hertzberg, H. Maxon, B. Scott, W. Schull, S. Thomas. Health Effects Model for Nuclear
Power Plant Accident Consequence Analysis. Low LET Radiation, Part II: Scientific Bases
for Health Effects Models. NUREG/CR-4214, SAND 85-7185, Rev. 1, Part II, U.S. Nuclear
Regulatory Commission, Washington, DC, May 1989.
S. Abrahamson, M.A. Bender, B.B. Boecker, E.S. Gilbert, B.R. Scott. Health Effects Models
for Nuclear Power Plant Accident Consequence Analysis. Modifications of Models Resulting
from Recent Reports on Health Effects of Ionizing Radiation, Low LET Radiation, Part II:
Scientific Bases for Health Effects Models. NUREG/CR-4214, Rev. 1, Part II, Addendum 1,
LMF-132, August 1991.
J.D. Boice, Jr., G. Engholm, R.A. Kleinerman, M. Blettner, M. Stovall, H. Lisco, W.C.
Moloney, D.F. Austin, A. Bosch, D.L. Cookfair, E.T. Krementz, H.B. Latourette, J.A. Merrill,
LJ. Peters, M.D. Schulz, H.H. Storm, E. Bjorkholm, F. Pettersson, C.M.J. Bell, M.P.
Coleman, P. Fraser, F.E. Neal, P. Prior, N.W. Choi, T.G. Hislop, M. Koch, N. Kreiger, D.
Robb, D. Tobson, D.H. Thomson, H. Lochmuller, D.V. Fournier, R. Frischkorn, K.E.
Kjorstad, A. Rimpela, M.H. Pejovic, V.P. Kirn, H. Stankusova, F. Berrino, K. Soigurdsson,
G.B. Hutchison, and B. MacMahon. Radiation dose and second cancer risk in patients treated
for cancer of the cervix. Radial. Res. 116, 3-55, 1988.
CIRRPC. Use ofBEIR V and UNSCEAR 1988 in Radiation Risk Assessment. 1992.
Committee on Interagency Radiation Research and Policy Coordination; Office of Science
and Technology Policy. Available as ORAU 92/F-64 through NTIS, Springfield, VA 22161.
S.C. Darby, R. Doll, S.K. Gill and P.G. Smith. Long-term mortality after a single treatment
course with X-rays in patients treated for ankylosing spondylitis. Br. J. Cancer 55, 179-190,
1987.
F.G. Davis, J.D. Boice, Jr., Z. Hrubek and R.R. Monson. Cancer mortality in a radiation-
exposed cohort of Massachusetts tuberculosis patients. Cancer Res. 49, 6130-6136, 1989.
Environmental Protection Agency. Radionuclides: Background Information Document for
Final Rules. Volume I. EPA 520/1-84-022-1, 1984.
Environmental Protection Agency. Risk Assessment Methodology. Environmental Impact
Statement. NESHAPS for Radionuclides. Background Information Document— Volume 1.
EPA/520/1-89-005, 1989.
Environmental Protection Agency. Final Draft for the Drinking Water Criteria Document on
Radium. Prepared by Life Systems, Inc., NTIS: PB 91225631, EPA, 1991.
32
-------
Environmental Protection Agency. Technical Support Document for the 1992 Citizen's Guide
to Radon. EPA 400-R-92-011, 1992.
J.S. Evans, D.W. Moeller and D.W. Cooper. Health Effects Model for Nuclear Power Plant
Accident Consequence Analysis, NUREG/CR-4214, SAND 85-7185, U.S. Nuclear Regulatory
Commission, Washington, DC, 1985.
E.S. Gilbert. "Chapter 3: Late somatic effects." In: S. Abrahamson, M.A. Bender, B.B.
Boecker, E.S. Gilbert, B.R. Scott. Health Effects Models for Nuclear Power Plant Accident
Consequence Analysis. Modifications of Models Resulting from Recent Reports on Health
Effects of Ionizing Radiation, Low LET Radiation, Part II: Scientific Bases for Health Effects
Models. NUREG/CR-4214, Rev. 1, Part II, Addendum 1, LMF-132, August 1991.
E.S. Gilbert. "Chapter 3: Late somatic effects." In: S. Abrahamson, M.A. Bender, B.B.
Boecker, E.S. Gilbert, B.R. Scott. Health Effects Models for Nuclear Power Plant Accident
Consequence Analysis. Modification of Models Resulting from Addition of Effects of Exposure
to Alpha-Emitting Radionuclides, Part II: Scientific Bases for Health Effects Models.
NUREG/CR-4214, Rev. 1, Part II, Addendum 2, LMF-136, May 1993.
D.T. Goodhead. An assessment of the role of microdosimetry in radiobiology. Radial. Res.
91,45-76, 1982.
AJ. Grosovsky and J.B. Little. Evidence for linear response for the induction of mutations in
human cells by x-ray exposures below 10 rads. Proc. Natl. Acad. Sci. USA 82, 2092-2095,
1985.
G.R. Howe. Effects of dose, dose-rate and fractionation on radiation-induced breast and lung
cancers: the Canadian fluoroscopy study. In: International Conference on Radiation Effects
and Protection, pp. 108-113. Japan Atomic Energy Research Institute, Tokyo, 1992.
ICRP. ICRP Publication 60. 1990 Recommendations of the International Commission on
Radiological Protection. Annals of the ICRP 21, No. 1-3, 1991.
ICRP. ICRP Publication 59. The Biological Basis for Dose Limitation in the Skin. Annals of
the ICRP 22, No. 2, 1992.
A.M. Kellerer and H.M. Rossi. The theory of dual radiation action. Curr. Topics Radiat. Res.
Quart. 8, 85-158, 1972.
C.E. Land and W.K. Sinclair. The relative contributions of different organ sites to the total
cancer mortality associated with low-dose radiation exposure. In: Risks Associated with
Ionising Radiations, Annals of the ICRP 22, No. 1, 1991.
D.E. Lea. Actions of Radiations on Living Cells, Cambridge University Press, 1962.
33
-------
M.P. Little and M.W. Charles. Time variations in radiation-induced relative risk and
implications for population cancer risks. J. Radiol. Prot. 11, 91-110, 1991.
M.P. Little, M.M. Hawkins, R.E. Shore, M.W. Charles and N.G. Hildreth. Time variations in
the risk of cancer following irradiation in childhood. Radial. Res. 126, 304-316, 1991.
R.C. Loehr and O.E. Nygaard. Evaluation of EPA's proposed methodology for estimating
radiogenic cancer risks. Letter to William K. Reilly, EPA Administrator, Dec. 9, 1992.
H. Maxon, S. Thomas, C. Buncher, S. Book and V. Hertzberg. Thyroid effects. In: Health
Effects Model for Nuclear Power Plant Accident Consequence Analysis. Part II: Scientific
Basis for Health Effects Models, pp. 181-226 (J.S. Evans, D.W. Moeller and D.W. Cooper,
eds.)NUREG/CR-4214, U.S. Nuclear Regulatory Commission, Washington, D.C., 1985.
C.W. Mays and H. Speiss. Bone sarcomas in patients given radium-224. In: Radiation
Carcinogenesis. Epidemiology and Biological Significance., pp. 241-252 (J.D. Boice and J.F.
Fraumeni, eds.) New York: Raven, 1984.
National Academy of Sciences. The Effects on Populations of Exposure to Low Levels of
Ionizing Radiation (BEIRIII). National Academy Press, Washington, D.C., 1980.
National Academy of Sciences. Health Risks of Radon and Other Internally Deposited Alpha-
Emitters (BEIRIV). National Academy Press, Washington, D.C., 1988.
National Academy of Sciences. Health Effects of Exposure to Low Levels of Ionizing
Radiation (BEIR V). National Academy Press, Washington, D.C., 1990.
National Institutes of Health, Report of the National Institutes of Health Ad Hoc Working
Group to Develop Radioepidemiological Tables, NIH Publication 85-2748, Superintendent of
Documents, U.S. Government Printing Office, Washington, DC, 1985.
NCRP. Influence of Dose and Its Distribution in Time on Dose-Response Relationships for
Low-LET Radiations. NCRP Report 64. National Council on Radiation Protection and
Measurements, Bethesda, MD, 1980.
NCRP. Induction of Thyroid Cancer by Ionizing Radiation. NCRP Report 80. National
Council on Radiation Protection and Measurements, Bethesda, MD, 1985.
NCRP. The Relative Biological Effectiveness of Radiations of Different Quality. NCRP Report
No. 104. National Council on Radiation Protection and Measurements, Bethesda, MD, 1990.
Office of Radiation Programs. Reevaluation of EPA's Methodology for Estimating
Radiogenic Cancer Risks. Transmittal from M. Oge to D.G. Barnes, Jan. 10, 1992.
34
-------
D.A. Pierce and M. Vaeth. The shape of the cancer mortality dose-response curve for the A-
bomb survivors. Radial. Res. 126, 36-42, 1991.
D.L. Preston. Breast cancer: Discussion. In: The Future of Human Radiation Research, BIR
Report 22, p. 56 (G.B. Gerber, D.M. Taylor, E. Cardis and J.W. Theissen, eds.) British
Institute of Radiology, London, 1991.
J.S. Puskin. An analysis of the uncertainties in estimates of radon-induced lung cancer. Risk
Analysis 12, 277-285, 1992.
J.S. Puskin, N.S. Nelson and C.B. Nelson. Bone cancer risk estimates. Health Phys. 63, 579-
580, 1992.
E. Ron and B. Modan. Thyroid and other neoplasms following childhood scalp irradiation. In:
Radiation Carcinogenesis: Epidemiology and Biological Significance, pp. 139-151 (J.D.
Boice Jr. and J.F. Fraumeni, Jr., eds.) Raven Press, N.Y., 1984.
Y. Shimizu, H. Kato and W.J. Schull. Life Span Study Report 11. Part 2. Cancer Mortality in
the Years 1950-85 Based on the Recently Revised Doses (DS86). RERF TR 5-88. 1988.
Y. Shimizu, H. Kato and W.J. Schull. Studies of the mortality of A-bomb survivors: 9.
Mortality, 1950-1985: Part 2. Cancer mortality based on the revised doses (DS86). Radial.
Res. 121, 120-141, 1990.
R.E. Shore, E.D. Woodward and L.H. Hempelman. Radiation induced thyroid cancer. In:
Radiation Car cinogenesis: Epidemiology and Biological Significance., pp. 131-138 (J.D.
Boice, Jr. and J.F. Fraumeni, Jr., eds.) Raven Press, N.Y., 1984.
J.W. Stather, C.R. Muirhead, A.A. Edwards, J.D. Harrison, D.C. Lloyd and N.R. Wood.
Health Effects Models Developed from the 1988 UNSCEAR Report. NRPB-R226. 1988.
R.L. Ullrich, M.C. Jernigan, L.C. Satterfield andN.D. Bowles. Radiation Carcinogenesis:
Time-dose relationships. Radial. Res. Ill, 179-184, 1987.
UNSCEAR. Sources, Effects and Risks of Ionizing Radiation. United Nations, N.Y., 1988.
UNSCEAR. Sources and Effects of Ionizing Radiation. United Nations, N.Y., 1993.
K.T. Wheeler and J.D. Wierowski. DNA repair kinetics in irradiated undifferentiated and
terminally differentiated cells. Radial. Environ. Biophys. 22, 3-19, 1983.
35
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Appendix A: Calculational Methods
A. Introduction
A radiogenic cancer risk model defines the relationship between radiation dose and the
subsequent force of mortality (or morbidity) attributable to that dose. As such, the model
provides the basis for calculating a time (or age) varying rate coefficient in a death or disease
process model. [General methods for structuring and solving the differential equations
representing such stochastic processes can be found in Chiang (1980).] Thus, to calculate
risks, the radiogenic risk model and other relevant quantities must be incorporated into a
suitable calculational procedure.
The risk calculations in this appendix are for attributable risk. Attributable risk can be
defined as the likelihood of death from (or development of) cancer that, according to the risk
model, is caused by a radiation exposure. By way of comparison, the excess risk calculated in
BEIR V (National Research Council 1990, Vaeth and Pierce 1989) excludes the fraction of
the attributable risk that represents deaths or cases among persons who would be expected to
die from (or to develop) cancer at a later age even if they had not been exposed.
The use of the attributable risk-per-unit-dose coefficients calculated here is limited to
the asymptotic case, i.e., these coefficients can only be used for applications where the
survival function is not significantly affected by the doses being assessed. When this is not
the case, risks must be calculated explicitly for the specific doses under consideration.
Male and female survival data (up to an age of 110 y) are from the U.S. Decennial life
Tables for 1979-1981 (National Center for Health Statistics 1985). These data were used to
calculate a combined life table for a male:female live birth ratio of 1.051. U.S. mortality data
were extracted from 1979-1981 Vital Statistics Mortality Data, Detail Tapes (National Center
for Health Statistics 1982, 1983, 1984). Deaths in these data files are classified according to
the 9th edition of the International Classification of Disease (ICD) codes (Public Health
Service 1980).
Radiogenic risk calculations require integrating functions of the risk model and vital
statistics. The vital statistics are discrete data, typically tabulated at one or five year intervals.
Radiogenic risk models are usually defined for several different age intervals and are
inherently discontinuous. Previously, such risk model calculations were implemented by
adapting actuarial methods developed for life table calculations, e.g., the CAIRO program
(Cook et al. 1978). The method used here is to fit a cubic spline to discrete data and then to
calculate interpolated values, derivatives, and integrals directly from the spline coefficients
(de Boor 1978, Fritsch and Butland 1982). This method admits almost any form of risk
model and eliminates most of the ad hoc approaches that were necessary with CAIRO.
36
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B. Risk Model Formulation
There are two basic types of radiogenic cancer risk projection models: absolute risk
and relative risk. An absolute risk model presumes that the age-specific excess force of
mortality (or morbidity) due to a radiation dose is independent of cancer mortality or
morbidity rates in the population. It can be written as
e( Y v\ •=. rt( Y\ I* (t Y\ V (Y\ /1 \
vA)Ae' ttVAe/lsVl'Ae/Y W (1)
where e(x,xe) is the excess force of mortality (or morbidity) (y"1 Gy"1) at age x due to a dose at
age xe (x > xg),
, the absolute risk coefficient (y"1 Gy"1), is a function of age at exposure, xe,
\xj, the time since exposure (t = x-xe) response function, can also be a function
and y(x) is the age at expression response function,
The radiogenic risk models for bone, skin, and thyroid cancer in the Revised Methodology are
all absolute risk models.
A relative risk model presumes that the age-specific excess force of mortality (or
morbidity) due to a radiation dose is the product of an exposure-age-specific relative risk
coefficient and baseline cancer mortality or morbidity rates in the population. The model can
be written as
(2)
where Jjfx^J is the relative risk (Gy"1) at age x due to a dose at age xe (x > xe),
P(xJ, the relative risk coefficient (Gy"1), is a function of age at exposure, xe,
C(t,xJ, the time since exposure (t=x-xe~) response function, may also be a function of xe,
and y(x) is the age at expression response function.
C. Revised Methodology Risk Models
Risk model coefficients
Risk coefficients for the Revised Methodology mortality risk models are shown in
Table A.I. Absolute risk models are used for bone, skin, and thyroid cancers. Relative risk
models are used for all other cancers.
37
-------
Table A.I Coefficients for the Revised Methodology mortality risk model (male and
female by age group).
Cancer
type
Male:
Esophagus
Stomach
Colon
Liver
Lung
Bone
Skin
Breast
Ovary
Bladder
Kidney
Thyroid
Leukemia
Residual
Female:
Esophagus
Stomach
Colon
Liver
Lung
Bone
Skin
Breast
Ovary
Bladder
Kidney
Thyroid
Leukemia
Residual
Risk
model
type*
R
R
R
R
R
A
A
R
R
R
R
A
R
R
R
R
R
R
R
A
A
R
R
R
R
A
R
R
0-9
0.2239
1.2337
2.1565
1.3449
0.4060
0.0927
0.0672
0.0
0.0
1.2191
0.3911
0.1667
672.16
0.7115
1.0418
3.4469
2.9680
1.3449
1.3753
0.0927
0.0672
0.7000
1.3163
1.0115
0.3911
0.3333
761.07
0.7119
10-19
0.2312
1.9165
2.1565
1.3449
0.4060
0.0927
0.0672
0.0
0.0
1.1609
0.3911
0.1667
244.07
0.7140
1.0896
4.2721
2.9680
1.2449
1.3753
0.0927
0.0672
0.7000
1.0382
0.9296
0.3911
0.3333
225.81
0.7174
Age group
20-29
0.2517
1.9051
0.2809
1.3449
0.0453
0.0927
0.0672
0.0
0.0
1.0736
0.3911
0.0833
323.47
0.1735
1.2492
4.0533
0.5755
1.3449
0.1921
0.0927
0.0672
0.3000
0.8829
1.0124
0.3911
0.1667
281.76
0.2932
30-39
0.2892
0.2881
0.4275
1.3449
0.1342
0.0927
0.0672
0.0
0.0
1.0544
0.3911
0.0833
228.86
0.1754
1.5831
0.5797
0.8186
1.3449
0.5440
0.0927
0.0672
0.3000
0.7678
1.1032
0.3911
0.1667
153.12
0.2963
40+
0.3258
0.2524
0.0899
1.3449
0.1794
0.0927
0.0672
0.0
0.0
0.9639
0.3911
0.0833
142.51
0.1847
2.0211
0.4887
0.1870
1.3449
0.8048
0.0927
0.0672
0.1000
0.6367
0.9792
0.3911
0.1667
154.28
0.3031
*Notes:
Risk model type
Absolute (A)
Relative (R)
Coefficient units
38
-------
Time since exposure response function
The time since exposure (TSE) response function for all cancers except bone, thyroid, and
leukemia has a 10 y minimal latency period and a lifetime plateau, i.e.,
= 1, 10 (a»L) • (8)
Since this TSE function has a maximum value that is much less than 1, the risk model
coefficients for leukemia in Table A.I are much larger than those for other sites.
Age at expression function
The age at expression function, y(x), is equal to one for all models in the Revised
Methodology.
39
-------
D. Risk Calculations
Basic quantities
S(x), the survival function, is the fraction of live born individuals expected to survive
to age x. S(0)=\, and decreases monotonically for increasing values of x. S(x) is obtained by
fitting a cubic spline to the decennial life table values to provide a continuous function of x.
8(x) is the expected lifetime (years) remaining for an individual who has attained age
x. It is given by
fi(x) is the force of mortality or hazard rate (y"1) at age x. Without a subscript, it is
usually the total rate from all causes. A subscript is used (unless it is clear by context) to
indicate a specific cause, i.e.,
- no)
alii v '
S(x) is directly dependent on ju(x) since
S(x) = exp(- 1 x\i(u) du) . HI)
When the baseline force of mortality ju0(x) is incremented by ///xj, S(x) becomes
S(x) = exp(-P(ii0(u) + |i/u))du)
•J 0
(12)
= S0(x) S/A) ,
where
S0(x) = exp(- I X\i0(u) du) , H3)
and
S/A) = exp
For sufficiently small values ofju/x), St(x) approaches a value of 1 for all values of x, i.e.,
S0(x) and S(x) are essentially the same. For most environmental radiation risk assessment
cases of practical interest, the increment of risk due to radiation satisfies this condition.
40
-------
Attributable lifetime risk coefficient
The age-specific attributable lifetime risk (ALR) coefficient, r(x), is the risk per unit
dose of a subsequent cancer death (Gy"1) due to radiation received at age x. For an absolute
risk model, the asymptotic ALR coefficient is
Similarly, for a relative risk model,
These age-specific coefficients are principally used to calculate age-averaged coefficients and
risks from radionuclide intakes or exposures.
Attributable lifetime loss coefficient
The attributable lifetime loss (ALL) coefficient e(x), at age x, is the expected lifetime
loss per unit dose (y Gy"1) for a radiation dose a age x. For an absolute risk model, the
asymptotic ALL coefficient is
For a relative risk model,
7T f "^ V^ ^ W
xJx
Ae-averaed coefficients
du •
08)
^ '
The lifetime age-averaged risk and life loss coefficients are
r(x)S(x)dx
(19)
f°°r(x\ ^(x\ dx
I 1 \AJ i_MAJ UA
Jo
§
and
41
-------
(20)
f
Jo
respectively. Since the age distribution of a stationary population is proportional to S(x), the
stationary-population weighted average values are identical to the lifetime age-averaged ones.
When the coefficients are averaged over a specific age interval, e.g., for assessing childhood
or occupational exposures, the limits of integration in both the numerators and the
denominators of these expressions are changed accordingly.
Sex-averaged coefficients
Since radiogenic cancer risk models are generally sex-specific, the resulting risk
coefficients must be averaged for use in assessing risk to a combined population. This is
accomplished by presuming a male:female sex ratio for live births of 1.051. Since S(x) is sex-
specific, the sex ratio is a function of age. The combined (sex-averaged) survival function is
1.051 S.W+S.W
2.051 ^ ;
where the subscripts m,f, and c refer to the male, female, and combined values respectively.
Similarly, the expected combined lifetime is
1.051 § + §f
(22}
' ( }
2.051 '
The combined age-specific force of mortality must reflect the age-specific contribution of
each sex. Hence,
1.051 5a+5
< i.o5i saoa
Combined age-specific ALR and ALL coefficients are
1.051 5)r)+5*)r*)
and
42
-------
1.051 5»e»+
respectively. Combined age averaged ALR and ALL values must reflect the expected lifetime
over the age interval. The lifetime average combined ALR and ALL coefficients are
r<= i.o5i e.+ g, • <26>
and
1.051
_
1.051 g+ § ' (27)
Continuity considerations
While the integration of a smoothly varying function using a spline is straightforward,
the radiogenic cancer models are inherently discontinuous. For example, the time since
exposure function for most solid cancers typically has a value of zero for times since exposure
that are less than the 10 y minimal latency and a value of one for times equal to or greater
than the minimal latency. Suppose that the function to be integrated (the integrand) is fitted at
one year increments. For the Revised Methodology models, the function will change abruptly
from a value of zero for times since exposure less than 10 y to a generally smoothly varying
function of time for times equal to or greater than 10 years. However fitting a spline to the
integrand provides a continuous transition from the value at 9 y to the value at 10 y. If the
integral is evaluated on the basis of these spline coefficients, it will include an unintended
contribution from this interval.
One way to solve the problem is to integrate functions in piece-wise continuous
intervals. This method is exact and would work well for the simple example considered
above. In general, however, the value of the integrand at each discontinuity depends on the
interval of integration; the method becomes unwieldy for situations with many discontinuities.
An alternative method for situations where the function is reasonably smooth on either side of
a discontinuity is to replace the value of the function at the discontinuity with the average of
the values immediately above and below it. For the case above, the value of the time since
exposure response function at 10 y is changed from 1 to (0+1)72=0.5. The reduced excess in
the integral between 9 and 10 y is then compensated for by a comparable reduction in the 10
to 1 1 year interval. This discontinuity smoothing method was used to calculate the risks and
lifetime losses for this report.
Cancer tvoe and dose location associations
43
-------
The dose locations associated with each cancer type are shown in Table A.2. When
more than one dose location is shown in the table, risks are calculated for a weighted mean of
the doses at these locations using the weights shown in the table. The residual cancer
category represents a composite of primary and secondary cancers that are not otherwise
considered in the model. The dose location associated with these cancers, the pancreas, was
chosen to be generally representative of soft tissues; the pancreas is not considered the origin
of all these neoplasms.
Table A.2 Dose regions associated with cancer types in the Revised Methodology risk
models
Cancer type
Esophagus
Stomach
Colon
Liver
Lung
Bone
Skin
Breast
Ovary
Bladder
Kidney
Thyroid
Leukemia
Residual
Dose region
Esophagus
Stomach wall
Upper Large Intestine wall
Lower Large Intestine wall
Liver
Tracheo-bronchial region
Pulmonary region
Bone surface
Dermis
Female breast
Ovary
Urinary bladder wall
Kidney
Thyroid
Red bone marrow
Pancreas
Weighting
factor
1.0
1.0
0.5
0.5
1.0
0.8
0.2
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
44
-------
Cancer morbidity calculations
While the calculational methodology outlined above could be used with incidence
models and force of morbidity data, the method used for the Revised Methodology is to
divide the mortality risk coefficient by a corresponding lethality factor, k, (see Section IV.F).
An exception is made for skin; only mortality is considered for calculating skin cancer
morbidity, i.e., k is considered to be 1. The lifetime loss coefficient is not recalculated for
morbidity.
E. Baseline Force of Mortality Calculations
Age-specific mortality rates (force of mortality) were calculated at one year intervals
using U.S. death data for the period 1979-1981 (National Center for Health Statistics 1982,
1983, 1984). These calculations assume that the fraction of the recorded deaths in each age
group due to a given cause, e.g., a specific ICD code, is the same as the probability of death in
that age interval for a birth cohort with the corresponding age-specific death rate. In
summary,
let nt be the number of deaths due to all causes between ages xt_} and xt,
ntj be the number of deaths due to causey between ages xt_} and xt,
mt be the probability in a birth cohort of dying from all causes between ages xt_} and xt,
and mtj be the probability in a birth cohort of dying from causey between ages xt_} and xt.
Then, given the age-specific forces of mortality, ju(x) and ju/x), and the survival function,
S(x),
ffl. = [x'\i(x)S(x)dx = S(xn)- S(x) ,
Jxt-i
and
m = fx'\i(x)S(x)dx
Jxi-i
(29)
= [S(xn)~ S(x)]
(For /=0, xt, nt, nip m^ and mtj are all equal to 0 as well.) LetM/xJ be the probability in a birth
cohort of dying from causey by age xt, i.e.,
45
-------
M(x) = fx']i(x)S(x)dx
J 0
(30)
= !>*, •
kO
Differentiating the expression forMj(x) with respect to x,
dM.(x)
(31)
Solving for the force of mortality,
1 dM.(x)
11 (y\ = J f^r)\
^ j S(x) dx • (32)
Hence, point estimates of ju/x) can be calculated by fitting a spline to M/x), calculating its
derivative with respect to x from the spline coefficients, and dividing the derivative by the
value of the survival function at*.
The ICD-9-CM codes for malignant neoplasms used to define each cancer type in the
model are listed in Table A.3. Even though baseline mortality rates are not necessary for
absolute risk model calculations, these definitions serve to clarify which ICD codes are
considered to comprise each cancer type.
F. Radionuclide Risk Coefficients
Age-specific radionuclide risk calculations
The age-specific cancer risk attributable to a unit intake of a radionuclide (Bq"1) is
calculated from the absorbed dose rate due to a unit intake of activity and the age-specific risk
per unit dose coefficient. The calculation is specific for each cancer and associated absorbed
dose site in the risk model. The complete calculation may involve the sum of contributions
from more than one tissue (see Table A.2) and from both low- and high-LET absorbed doses.
Except for leukemia, the Revised Methodology radiogenic cancer risk relative biological
effectiveness (RBE) for a high-LET absorbed dose from alpha radiation is 20 times that for a
low dose, low dose rate low-LET absorbed dose. For leukemia, the effective alpha dose RBE
is 1, as discussed in the main text. Each risk contribution is calculated as follows:
i
J- /" ™ I/ \ / \ r>/ \ t
dx ' (33)
where ra(xj is the cancer risk coefficient (Bq"1) for a unit intake of activity at age xt,
46
-------
d(x) is the absorbed dose rate (Gy y"1) at the site at age x due to a unit intake of activity
at age xia,
r(x) is the cancer risk due to a unit absorbed dose (Gy"1) at the site at age x,
and S(x) is the survival function at age x.
Sex-averaged risk coefficient
Age-specific male and female risk coefficients are combined by calculating a weighted
mean:
1.051 rtS+r
where ra(x) is the combined cancer risk coefficient (Bq"1) for a unit intake of activity at age xt,
1.051 is the presumed sex ratio at birth (male:female),
rma(x) is the male risk per unit activity at age xt,
rfa(x) is the female risk per unit activity at age xt,
Sm(x) is the male survival function at age xt,
and S/xJ is the female survival function at age xt.
This formulation weights each sex-specific risk coefficient by the proportion of that sex in a
stationary combined population at the desired age of intake.
Average lifetime risk coefficient
The average lifetime risk coefficient (Bq"1) for a unit intake of a radionuclide is
calculated from the age-specific value, ra(x), by the equation:
rra(x)S(x)dx
J 0
f = 12-1 (35)
a a '
where ra (Bq"1) is the average lifetime risk per unit intake of activity
and § is the expected lifetime at age 0.
47
-------
Table A.3 ICD codes used to define cancer types.
Cancer type
ICD-9-CM codes
Esophagus
Stomach
Colon
Liver
Lung
Bone
Skin
Breast
Ovary
Bladder
Kidney
Thyroid
Leukemia
EPA residual
150.0-150.9
151.0-151.9
153.0-153.9
155.0-155.2
162.0-162.9
170.0-170.9
173.0-173.9
except 172.0-172.9 (melanoma)
174.0-174.9 (female)
and 175.0-175.9 (male)
183.0
188.0-188.9
189.0-189.1
193.0-193.9
204.0-208.9
except 204.1 (chronic lymphoid)
140-208
except 181 (placenta), and all codes included
in the above definitions.
Equation (35) also provides the lifetime risk per unit intake for a lifetime intake at a constant
intake rate. For a stationary population, the expected incidence or mortality per unit activity
intake (cases per Bq or deaths per Bq) is also given by equation (35).
The sex-weighted average is given by
f §
1.051
§f
(36)
Radionuclide risk coefficients for external exposures
Lifetime risks for external radionuclide exposures are calculated in a similar manner to
those for radionuclide intakes. Since the organ and tissue doses occur at the same time as the
exposure and are not considered to be age dependent, the calculations are simpler. Given the
age specific cancer risk per unit dose, r(x), from equation (15) or (16) and the corresponding
48
-------
dose per unit exposure coefficient, de (e.g., Gy per Bq y/m2 to the thyroid from ground surface
exposure to 60Co), the lifetime risk is simply
re(x) = der(x) (37)
for an exposure at age x. The average lifetime risk, re is just
fe = der . (38)
Equation (38) can also be used in the same manner as equation (35) to calculate lifetime risk
from lifetime exposure at a constant exposure rate or population risk from an external
exposure.
Radionuclide Risk Coefficient Tables
Average lifetime mortality and morbidity (incidence) risk coefficients for the 321
radionuclides in Tables A.4a and A.4b, respectively, were calculated with CRDARTAB
(Sjoreen 1994) using RADRISK dose rates and Revised Methodology risk coefficients. The
coefficients correspond to the sums of risks for all cancers using equations (35) or (38) for
intakes and external exposures, respectively. The default clearance class for inhalation and
the digestive tract to blood transfer factor, fl5 for each element (or radionuclide when
necessary) are shown in Table A.5. These clearance class and fx defaults were chosen
conservatively, i.e., among the standard values that might be appropriate for environmental
exposures, they yield the greatest risks.
49
-------
Table A.4a Revised Methodology radionuclide mortality risk coefficients.
))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) )))))))))))))))
Internal External Internal
External
Ol
o
Nuclide
H-3
Be- 7
C-11
C-14
C-15
N-13
0-15
F-18
Na-22
Na-24
Si-31
P-32
P-33
S-35
CI-36
CI-38
Ar-41
K-40
K-42
Ca-45
Ca-47
Sc-46
Sc-47
Sc-48
V-48
Cr-51
Mn-52
Mn-54
Mn-56
Fe-55
Fe-59
Co-57
Co-58
Co-58m
Co-60
Ni-59
Ni-63
Ni-65
Cu-64
Zn-65
Zn-69
Ingestion
(Bq-1)
1.28E-12
1.38E-12
1.01E-12
1.93E-11
1.58E-14
7.01E-13
2.23E-13
2.34E-12
1.50E-10
2.57E-11
8.42E-12
1.14E-10
1.42E-11
6.92E-12
4.02E-11
4.72E-12
Inhalation
(Bq-1)
Bq
1.73E-12
3.56E-12
8.36E-13
1.31E-13
2.06E-14
6.36E-13
2.45E-13
1.56E-12
8.95E-11
1.52E-11
8.09E-12
6.21E-11
7.91E-12
3.33E-12
2.36E-11
4.06E-12
Submersion Gnd Sur
(per
y/m 3) 1
A ^ A A A A ^
11 11 ) 11
2.83E-09
5.83E-08
2.68E-07
5.83E-08
5.83E-08
5.65E-08
1.29E-07
2.82E-07
5.35E-11
3.27E-16
1.01E-07
1.05E-14 7.74E-08
2.28E-10
2.36E-11
3.84E-11
1.05E-10
8.87E-11
4.44E-11
1.03E-10
1.17E-10
2.16E-12
9.59E-11
3.32E-11
1.46E-11
6.24E-12
9.56E-11
1.65E-11
4.69E-11
1.49E-12
3.36E-10
3.04E-12
8.85E-12
9.51E-12
8.29E-12
1.78E-10
1.29E-12
1.33E-10
1.65E-11
5.77E-11
1.04E-10
2.73E-10
3.83E-11
7.99E-11
1.32E-10
3.59E-12
8.34E-11
7.31E-11
1.26E-11
1.08E-11
1.37E-10
6.47E-11
1.07E-10
1.93E-12
1.46E-09
8.00E-12
2.01E-11
8.80E-12
9.33E-12
1.94E-10
2.67E-12
9.49E-09
1.70E-08
5.92E-19
6.41E-08
1.22E-07
6.10E-09
2.04E-07
1.76E-07
1.77E-09
2.08E-07
5.05E-08
1.09E-07
8.87E-13
7.20E-08
6.65E-09
5.83E-08
1.33E-12
1.51E-07
1.48E-12
3.34E-08
1.09E-08
3.52E-08
3.40E-13
(per
Bqy/m2)
))))))))
5.88E-11
1.20E-09
3.10E-09
1.20E-09
1.20E-09
1.17E-09
2.42E-09
4.20E-09
9.35E-13
3.60E-17
1.57E-09
1.35E-09
1.60E-10
2.83E-10
1.56E-19
1.13E-09
2.26E-09
1.35E-10
3.67E-09
3.21E-09
3.82E-11
3.81E-09
9.73E-10
1.88E-09
1.71E-13
1.28E-09
1.50E-10
1.14E-09
2.75E-13
2.65E-09
3.22E-13
5.78E-10
2.22E-10
6.37E-10
7.16E-15
Nuclide
Ingestion
(Bq-1)
Inhalation
(Bq-1)
Submersion Gnd Surf
(per
Bq y/m 3)
Zn-69m
Ga-67
Ga-72
Ge-71
As-73
As-74
As-76
As-77
Se-75
Br-82
Kr-83m
Kr-85
Kr-85m
Kr-87
Kr-88
Kr-89
Kr-90
Rb-82
Rb-86
Rb-87
Rb-88
Rb-89
Sr-82
Sr-85
Sr-85m
Sr-89
Sr-90
Sr-91
Sr-92
Y-90
Y-91
Y-91m
Y-92
Y-93
Zr-93
Zr-95
Zr-97
Nb-93m
Nb-94
Nb-95
Nb-95m
111)))))
2.36E-11
1.28E-11
7.38E-11
2.03E-13
1.28E-11
6.62E-11
1.01E-10
2.52E-11
1.21E-10
2.54E-11
2.51E-13
1.38E-10
7.27E-11
3.47E-12
1.97E-12
4.06E-10
2.39E-11
3.38E-13
1.63E-10
9.64E-10
4.42E-11
3.14E-11
2.25E-10
2.02E-10
6.76E-13
3.15E-11
8.76E-11
8.55E-12
5.99E-11
1.57E-10
1.00E-11
1.08E-10
3.50E-11
4.60E-11
)))))))
2.57E-11
9.81E-12
4.39E-11
1.45E-12
3.09E-11
9.71E-11
9.16E-11
2.40E-11
9.46E-11
1.45E-11
7.81E-16
6.08E-15
5.93E-15
2.68E-14
4.60E-14
3.68E-14
3.86E-14
3.00E-13
8.28E-11
4.43E-11
3.46E-12
1.73E-12
1.68E-10
2.07E-11
1.51E-13
7.18E-11
1.51E-09
1.46E-11
8.53E-12
1.89E-10
4.05E-10
7.02E-13
3.92E-11
7.55E-11
1.29E-10
1.33E-10
9.39E-11
1.07E-10
1.79E-09
6.27E-11
4.32E-11
i lit}}}}
2.36E-OE
(per
Bqy/m2)
i 4.95E-10
7.97E-09 1.77E-10
1.77E-07
3.52E-12
1.97E-10
4.43E-08
2.55E-08
4.86E-10
2.17E-08
1.58E-07
3.41E-12
1.28E-10
8.83E-09
5.23E-08
1.34E-07
1.19E-07
7.82E-08
6.29E-08
5.75E-09
4.22E-OE
1.33E-07
1.20E-11
2.92E-08
1.21E-08
8.32E-12
4.16E-08
8.09E-08
2.18E-10
3.06E-0!
1.53E-08
5.60E-09
4.39E-08
1.09E-08
4.42E-12
9.47E-0
4.59E-08
3.34E-0'
2.97E-09
9.03E-13
8.14E-12
9.00E-10
4.91E-10
1.04E-11
4.73E-10
3.00E-09
8.26E-13
2.63E-12
1.95E-10
8.65E-10
2.08E-09
1.95E-09
1.39E-09
1.29E-09
1.05E-10
! 6.78E-10
2.23E-09
2.89E-12
6.04E-10
2.64E-10
1.57E-13
7.85E-10
1.39E-09
3.86E-12
} 6.24E-10
2.81E-10
9.90E-11
8.62E-10
2.01E-10
6.78E-13
8 1.84E-09
8.96E-10
} 7.48E-11
-------
Table A.4a Revised Methodology radionuclide mortality risk coefficients, (cont.)
Internal External Internal External
Nuclide
Nb-97
Nb-97m
Mo-99
Tc-95
Tc-95m
Tc-96
Tc-96m
Tc-97
Tc-97m
Tc-99
Tc-99m
Ru-97
Ru-103
Ru-105
Ru-106
Rh-103m
Rh-105
Rh-105m
Rh-106
Pd-100
Pd-101
Pd-103
Pd-107
Pd-109
Ag-105
Ag-108
Ag-108m
Ag-109m
Ag-110
Ag-IIOm
Ag-111
Cd-109
Cd-115
Cd-115m
ln-113m
ln-114
ln-114m
ln-115
ln-115m
Sn-113
Sn-121
Ingestion
(Bq-1)
3.34E-12
6.41E-14
3.88E-11
1.22E-12
2.22E-11
3.95E-11
4.66E-13
2.83E-12
2.10E-11
2.49E-11
8.87E-13
9.18E-12
5.09E-11
1.83E-11
5.28E-10
1.66E-13
2.91E-11
1.98E-14
8.78E-14
5.76E-11
5.89E-12
1.58E-11
3.14E-12
5.05E-11
2.67E-11
1.69E-13
1.03E-10
6.55E-15
5.94E-14
1.43E-10
1.03E-10
1.38E-10
1.10E-10
2.19E-10
1.50E-12
Inhalation
(Bq-1)
Bq
5.38E-12
8.41E-14
8.60E-11
7.59E-13
4.38E-11
3.86E-11
4.83E-13
8.02E-12
4.49E-11
6.75E-11
7.66E-13
7.83E-12
9.66E-11
1.82E-11
2.75E-09
3.26E-13
2.38E-11
2.11E-14
1.18E-13
6.71E-11
4.82E-12
2.23E-11
3.61E-11
4.17E-11
4.75E-11
2.42E-13
1.49E-09
8.87E-15
8.10E-14
6.78E-10
1.01E-10
4.29E-10
9.45E-11
3.64E-10
1.43E-12
Submersion Gnd Surf
(per
y/m 3)
3.92E-OE
4.36E-0!
9.15E-09
4.72E-08
3.91E-08
1.51E-07
(per
Bqy/m2)
! 7.82E-10
3 8.54E-10
1.82E-10
9.21E-10
7.85E-10
2.90E-09
2.50E-09 4.90E-11
3.05E-11
4.33E-11
2.63E-14
4.13E-12
3.71E-12
6.22E-16
7.02E-09 1.56E-10
1.28E-08
2.76E-08
4.62E-08
6.59E-12
4.37E-09
1.51E-09
1.21E-08
6.03E-11
3.94E-11
1.02E-09
9.41E-0!
2.82E-10
5.70E-10
9.24E-10
7.46E-13
9.40E-11
3.66E-11
2.41E-10
6.62E-12
8.11E-13
2.07E-11
] 1.90E-09
2.04E-10 7.24E-12
1.80E-09
1.65E-07
1.48E-09
7.25E-11
1.17E-08
1.33E-09
1.44E-08
1.10E-13 1.49E-13 1.85E-09
3.18E-10
8.14E-10
5.46E-12
5.66E-11
1.84E-11
5.39E-10
5.00E-09
4.09E-12
1.46E-10
1.20E-11
5.15E-09
8.92E-09
3.92E-10
3.59E-11
3.11E-09
3.19E-11
6.22E-12
2.40E-10
2.44E-11
3.07E-10
3.71E-11
1.08E-10
1.93E-10
1.26E-11
Nuclide
Ingestion
(Bq-1)
Inhalation
(Bq-1)
Submersion Gnd Sur
(per
Bq y/m 3)
Sn-121m
Sn-125
Sn-126
Sb-122
Sb-124
Sb-125
Sb-126
Sb-126m
Sb-127
Sb-129
Te-125m
Te-127
Te-127m
Te-129
Te-129m
Te-131
Te-131m
Te-132
-122
-123
-125
-126
-129
-130
-131
-132
-133
-134
-135
Xe-122
Xe-123
Xe-125
Xe-127
Xe-129m
Xe-131m
Xe-133
Xe-133m
Xe-135
Xe-135m
Xe-137
Xe-138
) 1 1 1 1 ) 1 1
3.08E-11
2.51E-10
3.26E-10
1.33E-10
1.65E-10
4.59E-11
1.51E-10
1.60E-12
1.28E-10
2.92E-11
4.08E-11
1.32E-11
1.02E-10
2.90E-12
1.84E-10
2.59E-12
8.77E-11
1.66E-10
5.12E-13
2.24E-12
7.24E-11
1.38E-10
5.06E-10
2.04E-11
1.04E-10
6.30E-12
3.53E-11
3.87E-12
1.12E-11
)))))))
1.63E-10
2.32E-10
9.07E-10
1.04E-10
2.70E-10
1.10E-10
1.62E-10
1.62E-12
1.16E-10
1.95E-11
6.14E-11
9.46E-12
2.99E-10
3.71E-12
2.87E-10
2.67E-12
7.06E-11
1.45E-10
5.69E-13
1.31E-12
4.78E-11
9.01E-11
3.35E-10
1.19E-11
6.72E-11
4.00E-12
2.11E-11
2.62E-12
6.80E-12
5.60E-14
1.39E-14
1.93E-14
7.37E-15
1.09E-14
7.86E-15
7.87E-15
9.81E-15
1.44E-14
3.81E-15
3.17E-14
4.21E-14
lilt}}}}
1.23E-11
1.88E-08
(per
Bqy/m2)
"l1!1!1!1!*!1!^
))))))))
4.38E-13
3.39E-10
2.36E-09 5.89E-11
2.57E-08
1.16E-07
2.43E-08
1.63E-07
9.22E-0
3.88E-08
8.69E-08
3.42E-10
2.74E-10
1.12E-10
3.08E-09
5.21E-10
2.05E-09
5.01E-10
3.24E-09
3 1.85E-09
7.78E-10
1.63E-09
1.48E-11
5.79E-12
4.74E-12
6.38E-11
1.94E-09 4.02E-11
2.44E-08
8.59E-OE
1.19E-08
5.59E-08
8.58E-09
3.86E-10
2.65E-08
2.98E-10
1.26E-07
2.16E-08
1.37E-07
3.52E-08
1.60E-07
9.74E-08
3.23E-09
3.63E-08
1.38E-08
1.44E-08
1.01E-09
3.65E-10
1.64E-09
1.54E-09
1.39E-08
2.45E-08
1.10E-08
7.33E-08
4.91E-10
1.63E-09
2.66E-10
1.14E-09
1.94E-10
1.71E-11
5.38E-10
1.56E-11
2.50E-09
4.55E-10
2.64E-09
7.06E-10
2.99E-09
1.69E-09
7.54E-11
7.08E-10
3.01E-10
3.21E-10
3.78E-11
1.42E-11
4.58E-11
3.99E-11
3.00E-10
5.05E-10
2.16E-10
1.23E-09
-------
Table A.4a Revised Methodology radionuclide mortality risk coefficients, (cont.)
Internal External Internal External
Nuclide
Cs-131
Cs-134
Cs-134m
Cs-135
Cs-136
Cs-137
Cs-138
Ba-131
Ba-133
Ba-133m
Ba-137m
Ba-139
Ba-140
La-140
Ce-141
Ce-143
Ce-144
Pr-142
Pr-143
Pr-144
Pr-144m
Nd-147
Nd-149
Pm-147
Pm-148
Pm-148m
Pm-149
Sm-147
Sm-151
Sm-153
Eu-152
Eu-154
Eu-155
Eu-156
Gd-153
Gd-159
Tb-158
Tb-160
Dy-165
Dy-166
Ho-166
Ingestion
(Bq-1)
3.28E-12
8.49E-10
9.17E-13
8.27E-11
1.38E-10
5.71E-10
3.96E-12
2.64E-11
4.53E-11
4.17E-11
5.35E-14
5.72E-12
1.78E-10
1.44E-10
5.86E-11
8.91E-11
4.42E-10
1.05E-10
9.88E-11
1.91E-12
7.46E-13
8.82E-11
7.60E-12
2.12E-11
2.17E-10
1.52E-10
8.27E-11
5.12E-10
6.99E-12
6.04E-11
9.17E-11
1.47E-10
2.54E-11
1.65E-10
2.01E-11
3.93E-11
6.54E-11
1.16E-10
5.54E-12
1.40E-10
1.14E-10
Inhalation
(Bq-1)
Bq
1.91E-12
5.01E-10
7.09E-13
4.78E-11
8.10E-11
3.34E-10
3.21E-12
8.35E-12
7.90E-11
9.49E-12
3.90E-14
3.59E-12
5.49E-11
9.75E-11
8.99E-11
7.48E-11
2.60E-09
8.44E-11
1.10E-10
3.37E-12
1.44E-12
9.47E-11
9.89E-12
1.84E-10
2.00E-10
6.26E-10
6.83E-11
1.69E-07
1.15E-10
4.17E-11
1.69E-09
2.01E-09
2.23E-10
1.83E-10
7.03E-11
2.48E-11
1.53E-09
2.37E-10
5.54E-12
1.49E-10
7.92E-11
Submersion Gnd Surf
(per
y/m 3)
2.51E-10
9.22E-08
1.04E-09
1.30E-07
1.49E-07
2.56E-08
2.02E-08
3.03E-09
3.52E-OE
1.96E-09
1.07E-08
1.44E-07
4.07E-09
1.46E-08
9.32E-10
3.64E-09
5.33E-16
2.10E-09
2.01E-10
7.23E-09
2.12E-OE
1.91E-13
3.46E-OE
(per
Bqy/m2)
1.39E-11
1.82E-09
2.71E-11
2.47E-09
2.52E-09
5.46E-10
4.52E-10
7.19E-11
i 7.01E-10
4.19E-11
2.23E-10
2.49E-09
9.21E-11
3.14E-10
2.18E-11
6.02E-11
1.04E-17
3.49E-11
7.63E-12
1.59E-10
! 4.53E-10
4.27E-15
i 6.24E-10
1.17E-07 2.33E-09
6.59E-10
3.02E-14
2.45E-09
6.79E-08
7.51E-08
2.81E-09
8.59E-08
4.18E-09
2.04E-09
4.55E-08
6.48E-08
1.34E-09
1.48E-09
1.54E-09
1.40E-11
3.48E-15
6.57E-11
1.28E-09
1.39E-09
6.94E-11
1.46E-09
1.15E-10
4.62E-11
8.62E-10
1.22E-09
2.93E-11
4.04E-11
3.04E-11
Nuclide
Ingestion
(Bq-1)
Inhalation
(Bq-1)
Submersion Gnd Sur
(per
Bq y/m 3)
Er-169
Er-171
Tm-170
Tm-171
Yb-169
Yb-175
Lu-177
Hf-181
Ta-182
W-181
W-185
W-187
Re-183
Re-186
Re-187
Re-188
Os-185
Os-191
Os-191m
Os-193
lr-190
lr-192
lr-194
Pt-191
Pt-193
Pt-193m
Pt-197
Pt-197m
Au-196
Au-198
Hg-197
Hg-203
TI-202
TI-204
TI-207
TI-208
TI-209
Pb-203
Pb-209
Pb-210
Pb-211
111)))))
3.17E-11
2.53E-11
1.12E-10
8.79E-12
5.21E-11
3.60E-11
4.42E-11
8.30E-11
1.07E-10
4.29E-12
3.07E-11
3.77E-11
2.82E-11
4.80E-11
1.63E-13
4.69E-11
2.86E-11
4.58E-11
7.50E-12
6.56E-11
7.68E-11
9.84E-11
1.06E-10
2.30E-11
2.43E-12
3.76E-11
3.21E-11
5.32E-12
2.04E-11
7.99E-11
1.79E-11
4.02E-11
1.83E-11
3.54E-11
2.61E-13
3.95E-13
3.08E-13
1.62E-11
3.45E-12
1.46E-08
7.15E-12
)))))))
2.93E-11
1.65E-11
2.41E-10
4.23E-11
8.31E-11
3.19E-11
4.22E-11
1.26E-10
3.61E-10
1.47E-12
7.29E-12
9.25E-12
5.77E-11
5.47E-11
4.41E-13
4.89E-11
9.57E-11
5.38E-11
6.88E-12
5.26E-11
8.70E-11
2.42E-10
8.49E-11
7.09E-12
1.38E-12
9.62E-12
7.82E-12
2.07E-12
2.00E-11
7.02E-11
1.33E-11
6.10E-11
1.08E-11
2.10E-11
3.16E-13
3.42E-13
2.82E-13
5.66E-12
1.45E-12
3.59E-08
2.61E-10
i lit}}}}
9.54E-14
2.03E-08
2.18E-10
2.33E-11
1.45E-08
2.18E-09
1.87E-09
3.05E-08
7.70E-08
1.47E-09
1.46E-12
2.74E-0!
7.12E-09
1.04E-09
3.31E-09
4.08E-08
3.44E-09
(per
Bqy/m2)
"l1!1!1!1!*!1!1!
))))))))
4.33E-15
4.46E-10
5.82E-12
6.94E-13
3.55E-10
4.71E-11
4.21E-11
6.45E-10
1.41E-09
4.17E-11
3.26E-14
} 5.59E-10
1.76E-10
2.44E-11
6.85E-11
8.25E-10
8.36E-11
1.89E-10 5.45E-12
3.65E-09
7.98E-08
4.64E-08
5.28E-09
1.51E-08
1.70E-12
4.56E-10
1.14E-09
7.95E-11
1.65E-09
9.80E-10
1.07E-10
3.37E-10
4.31E-13
1.22E-11
2.74E-11
4.06E-09 9.42E-11
2.60E-08
2.29E-08
2.99E-09
1.27E-08
2.58E-08
4.84E-11
1.32E-10
2.33E-07
1.28E-07
1.62E-08
5.49E-11
3.00E-09
5.65E-10
4.83E-10
7.60E-11
2.77E-10
5.51E-10
1.23E-12
2.51E-12
3.56E-09
2.27E-09
3.61E-10
2.41E-12
5.99E-11
-------
Table A.4a Revised Methodology radionuclide mortality risk coefficients, (cont.)
Internal External Internal External
Ol
CO
Nuclide
Pb-212
Pb-214
Bi-206
Bi-207
Bi-210
Bi-211
Bi-212
Bi-213
Bi-214
Po-210
Po-212
Po-213
Po-214
Po-215
Po-216
Po-218
At-217
Rn-219
Rn-220
Rn-222
Fr-221
Fr-223
Ra-223
Ra-224
Ra-225
Ra-226
Ra-228
Ac-225
Ac-227
Ac-228
Th-227
Th-228
Th-229
Th-230
Th-231
Th-232
Th-234
Pa-231
Pa-233
Pa-234
Ingestion Inhalation Submersion Gnd Surl
(Bq-1) (Bq-1) (per (per
Bqy/m 3) Bqy/m2)
2.99E-10 8.68E-10 7.98E-09 1.77E-10
6.02E-12 1.56E-10 1.39E-08 2.98E-10
1.11E-10 9.61E-11 1.98E-07 3.72E-09
7.82E-11 1.95E-10 9.16E-08 1.74E-09
1.10E-10 1.28E-09
4.42E-13 4.48E-11 2.66E-09 5.69E-11
1.22E-11 9.35E-10 1.11E-08 2.06E-10
8.90E-12 7.92E-10 7.90E-09 1.65E-10
4.45E-12 3.74E-10 9.48E-08 1.64E-09
5.88E-09 5.14E-08 5.13E-13 9.95E-15
1.10E-21 1.52E-19
1.57E-20 2.00E-18 1.83E-12 3.57E-14
5.16E-19 7.12E-17 5.02E-12 9.74E-14
1.13E-17 1.15E-15 8.46E-12 1.77E-13
1.59E-15 7.56E-14 8.75E-13 1.69E-14
1.10E-12 9.44E-11
1.98E-16 1.32E-14 1.39E-11 2.80E-13
1.74E-12 3.22E-09 6.91E-11
4.42E-12 3.01E-11 6.16E-13
3.21E-11 2.22E-11 4.59E-13
3.04E-12 2.05E-10 1.70E-09 3.75E-11
7.91E-12 1.17E-11 2.34E-09 5.85E-11
3.91E-09 9.12E-08 7.18E-09 1.61E-10
2.46E-09 5.70E-08 5.57E-10 1.21E-11
2.88E-09 6.01E-08 2.63E-10 1.16E-11
5.26E-09 6.62E-08 3.71E-10 8.21E-12
4.48E-09 2.22E-08 2.48E-18 5.19E-19
2.19E-09 1.06E-07 7.03E-10 1.68E-11
8.17E-09 1.78E-06 6.41E-12 1.95E-13
2.55E-11 8.33E-10 5.58E-08 1.05E-09
6.11E-10 1.10E-07 5.72E-09 1.28E-10
9.84E-10 2.41E-06 1.01E-10 2.69E-12
9.94E-10 1.91E-06 4.42E-09 1.05E-10
6.39E-10 4.22E-07 1.88E-11 7.72E-13
2.70E-11 2.18E-11 5.60E-10 1.71E-11
5.61E-10 4.73E-07 8.51E-12 5.31E-13
2.88E-10 3.89E-10 3.78E-10 9.65E-12
2.86E-09 5.85E-07 1.65E-09 3.81E-11
7.05E-11 1.01E-10 1.17E-08 2.58E-10
3.37E-11 2.91E-11 1.17E-07 2.25E-09
Nuclide
Pa-234m
U-232
U-233
U-234
U-235
U-236
U-237
U-238
U-240
Np-236
Np-237
Np-238
Np-239
Np-240
Np-240m
Pu-236
Pu-238
Pu-239
Pu-240
Pu-241
Pu-242
Pu-243
Pu-244
Am-241
Am-242
Am-242m
Am-243
Cm-242
Cm-243
Cm-244
Cm-245
Cm-246
Cm-247
Cm-248
Cf-252
Ingestion Inhalation Submersion Gnd Surfa
(Bq-1) (Bq-1) (per (per
Bqy/m 3) Bqy/m2)
1.16E-13 1.61E-13 6.90E-10 1.31E-11
1.40E-09 1.35E-06 1.23E-11 8.11E-13
7.44E-10 3.63E-07 1.21E-11 4.38E-13
7.38E-10 3.58E-07 6.72E-12 6.12E-13
7.53E-10 3.33E-07 8.29E-09 1.84E-10
6.99E-10 3.39E-07 5.12E-12 5.47E-13
6.01E-11 5.99E-11 6.96E-09 1.65E-10
7.31E-10 3.19E-07 4.36E-12 4.81E-13
8.29E-11 6.98E-11 2.79E-11 2.90E-12
1.43E-11 8.96E-11 6.80E-09 1.61E-10
6.65E-09 8.04E-07 1.13E-09 3.05E-11
6.92E-11 9.80E-11 3.36E-08 6.24E-10
6.42E-11 4.61E-11 8.96E-09 2.03E-10
3.42E-12 3.26E-12 6.81E-08 1.34E-09
5.76E-13 7.24E-13 1.94E-08 3.82E-10
1.56E-09 3.39E-07 4.66E-12 7.14E-13
6.64E-09 6.76E-07 3.32E-12 6.11E-13
7.12E-09 6.82E-07 3.83E-12 2.89E-13
7.11E-09 6.81E-07 3.26E-12 5.86E-13
1.19E-10 6.55E-09
6.76E-09 6.47E-07 2.78E-12 4.86E-13
5.80E-12 6.29E-12 1.16E-09 2.83E-11
6.95E-09 6.53E-07 1.94E-12 4.11E-13
7.39E-09 8.96E-07 8.46E-10 2.61E-11
2.25E-11 2.52E-10 7.03E-10 1.78E-11
6.74E-09 8.08E-07 2.01E-11 2.00E-12
7.36E-09 8.89E-07 2.43E-09 6.21E-11
6.60E-10 7.81E-08 3.62E-12 6.51E-13
5.58E-09 6.75E-07 6.82E-09 1.55E-10
4.66E-09 5.70E-07 3.04E-12 5.80E-13
7.54E-09 9.12E-07 3.69E-09 8.68E-11
7.48E-09 9.08E-07 2.49E-12 5.10E-13
6.93E-09 8.34E-07 1.79E-08 3.80E-10
2.90E-08 3.39E-06 2.26E-12 4.11E-13
3.50E-09 6.59E-07 2.79E-12 4.37E-13
-------
Table A.4b Revised Methodology radionuclide incidence risk coefficients.
Internal External Internal
External
Nuclide
Ingestion Inhalation
(Bq-1) (Bq-1)
Submersion Gnd Surl
(per (per
Bqy/m 3) Bqy/m2)
H-3
Be- 7
C-11
C-14
C-15
N-13
0-15
F-18
Na-22
Na-24
Si-31
P-32
P-33
S-35
CI-36
CI-38
Ar-41
K-40
K-42
Ca-45
Ca-47
Sc-46
Sc-47
Sc-48
V-48
Cr-51
Mn-52
Mn-54
Mn-56
Fe-55
Fe-59
Co-57
Co-58
Co-58m
Co-60
Ni-59
Ni-63
Ni-65
Cu-64
Zn-65
Zn-69
I))))))))))))))
1.93E-12 2.59E-12
2.33E-12 4.81E-12
1.21E-12 9.14E-13
2.79E-11 1.89E-13
1.79E-14 2.18E-14
8.25E-13 6.84E-13
2.57E-13 2.60E-13
2.94E-12 1.77E-12
2.17E-10 1.32E-10
3.74E-11 2.03E-11
1.36E-11 8.90E-12
1.65E-10 7.92E-11
2.11E-11 1.07E-11
1.12E-11 5.01E-12
6.04E-11 3.51E-11
5.58E-12 4.41E-12
1.27E-14
3.39E-10 2.02E-10
3.48E-11 2.04E-11
5.46E-11 6.79E-11
1.80E-10 1.41E-10
1.55E-10 3.53E-10
7.97E-11 5.44E-11
1.80E-10 1.13E-10
2.04E-10 1.85E-10
3.74E-12 4.70E-12
1.62E-10 1.19E-10
5.30E-11 9.98E-11
2.32E-11 1.41E-11
9.50E-12 1.51E-11
1.59E-10 1.91E-10
2.62E-11 7.78E-11
7.62E-11 1.40E-10
2.56E-12 2.41E-12
5.11E-10 1.86E-09
5.00E-12 1.08E-11
1.49E-11 2.74E-11
1.52E-11 9.71E-12
1.42E-11 1.13E-11
2.68E-10 2.70E-10
1.67E-12 2.82E-12
til}}}}}}}}}}}}}
4.31E-09 8.94E-11
8.87E-08 1.83E-09
4.05E-07 4.69E-09
8.87E-08 1.83E-09
8.87E-08 1.83E-09
8.59E-08 1.77E-09
1.96E-07 3.68E-09
4.28E-07 6.36E-09
8.13E-11 1.42E-12
6.32E-16 6.95E-17
1.54E-07 2.37E-09
1.17E-07 2.05E-09
1.44E-08 2.43E-10
2.57E-08 4.30E-10
1.13E-18 2.98E-19
9.74E-08 1.71E-09
1.85E-07 3.43E-09
9.42E-09 2.08E-10
3.10E-07 5.58E-09
2.67E-07 4.88E-09
2.71E-09 5.83E-11
3.16E-07 5.79E-09
7.68E-08 1.48E-09
1.65E-07 2.85E-09
1.71E-12 3.30E-13
1.09E-07 1.94E-09
1.03E-08 2.33E-10
8.85E-08 1.73E-09
2.55E-12 5.31E-13
2.30E-07 4.03E-09
2.85E-12 6.21E-13
5.07E-08 8.78E-10
1.65E-08 3.38E-10
5.34E-08 9.68E-10
5.18E-13 1.09E-14
Nuclide
Ingestion
(Bq-1)
Inhalation
(Bq-1)
Submersion Gnd Surf
(per
(per
Bqy/m 3) Bqy/m2)
Zn-69m
Ga-67
Ga-72
Ge-71
As-73
As-74
As-76
As-77
Se-75
Br-82
Kr-83m
Kr-85
Kr-85m
Kr-87
Kr-88
Kr-89
Kr-90
Rb-82
Rb-86
Rb-87
Rb-88
Rb-89
Sr-82
Sr-85
Sr-85m
Sr-89
Sr-90
Sr-91
Sr-92
Y-90
Y-91
Y-91m
Y-92
Y-93
Zr-93
Zr-95
Zr-97
Nb-93m
Nb-94
Nb-95
Nb-95m
111)))))
4.11E-11
2.26E-11
1.29E-10
3.19E-13
2.22E-11
1.14E-10
1.77E-10
4.46E-11
1.77E-10
3.83E-11
2.84E-13
1.92E-10
9.96E-11
3.96E-12
2.34E-12
6.97E-10
3.78E-11
4.87E-13
2.79E-10
1.10E-09
7.62E-11
5.48E-11
4.05E-10
3.64E-10
9.98E-13
5.26E-11
1.55E-10
1.41E-11
1.06E-10
2.80E-10
1.79E-11
1.87E-10
6.09E-11
8.27E-11
))))))),
3.16E-11
1.39E-11
5.87E-11
1.58E-12
3.69E-11
1.25E-10
1.17E-10
3.10E-11
1.33E-10
2.12E-11
9.40E-16
7.75E-15
7.42E-15
3.26E-14
5.96E-14
4.34E-14
4.33E-14
3.17E-13
1.14E-10
6.12E-11
3.69E-12
1.87E-12
2.40E-10
3.08E-11
1.93E-13
9.94E-11
1.61E-09
2.11E-11
1.27E-11
2.68E-10
5.01E-10
8.09E-13
4.36E-11
9.40E-11
1.42E-10
1.75E-10
1.28E-10
1.17E-10
2.22E-09
8.40E-11
6.08E-11
>}}}}}}}
3.59E-08
1.23E-08
2.69E-07
6.79E-12
3.21E-10
6.74E-08
3.87E-08
7.43E-10
3.33E-08
2.41E-07
6.48E-12
1.94E-10
1.36E-08
7.93E-08
2.03E-07
1.81E-07
1.19E-07
9.56E-08
8.74E-09
6.39E-08
2.02E-07
2.29E-11
4.44E-08
1.85E-08
1.26E-11
6.32E-08
1.23E-07
3.32E-10
4.65E-08
2.32E-08
8.51E-09
6.68E-08
1.65E-08
8.30E-12
1.44E-07
6.97E-08
5.12E-OE
lilt}}}}
7.54E-10
2.72E-10
4.51E-09
1.74E-12
1.39E-11
1.37E-09
7.46E-10
1.58E-11
7.26E-10
4.56E-09
1.58E-12
3.99E-12
3.00E-10
1.31E-09
3.15E-09
2.96E-09
2.12E-09
1.95E-09
1.59E-10
1.03E-09
3.38E-09
5.51E-12
9.19E-10
4.04E-10
2.39E-13
1.19E-09
2.12E-09
5.86E-12
9.49E-10
4.27E-10
1.50E-10
1.31E-09
3.05E-10
1.27E-12
2.79E-09
1.36E-09
1 1.15E-10
-------
Table A.4b Revised Methodology radionuclide incidence risk coefficients, (cont.)
Internal External Internal External
Ol
Ol
Nuclide
Nb-97
Nb-97m
Mo-99
Tc-95
Tc-95m
Tc-96
Tc-96m
Tc-97
Tc-97m
Tc-99
Tc-99m
Ru-97
Ru-103
Ru-105
Ru-106
Rh-103m
Rh-105
Rh-105m
Rh-106
Pd-100
Pd-101
Pd-103
Pd-107
Pd-109
Ag-105
Ag-108
Ag-108m
Ag-109m
Ag-110
Ag-IIOm
Ag-111
Cd-109
Cd-115
Cd-115m
ln-113m
ln-114
ln-114m
ln-115
ln-115m
Sn-113
Sn-121
Ingestion
(Bq-1)
4.74E-12
Inhalation
(Bq-1)
Bq
5.75E-12
8.85E-14 9.03E-14
6.13E-11
1.84E-12
3.36E-11
6.17E-11
7.05E-13
4.27E-12
3.24E-11
3.79E-11
1.51E-12
1.59E-11
8.98E-11
3.12E-11
9.32E-10
2.21E-13
5.22E-11
2.92E-14
9.80E-14
1.01E-10
1.01E-11
2.85E-11
5.66E-12
9.00E-11
4.41E-11
1.88E-13
1.64E-10
7.32E-15
6.60E-14
2.28E-10
1.85E-10
2.16E-10
1.97E-10
3.84E-10
2.24E-12
1.23E-13
5.56E-10
9.43E-10
9.24E-12
1.01E-10
3.31E-11
1.21E-10
9.13E-13
5.67E-11
5.25E-11
6.11E-13
9.31E-12
5.30E-11
7.81E-11
9.43E-13
1.10E-11
1.24E-10
2.17E-11
3.11E-09
3.45E-13
3.30E-11
2.50E-14
1.25E-13
9.60E-11
6.18E-12
2.92E-11
3.94E-11
5.37E-11
6.28E-11
2.55E-13
1.90E-09
9.34E-15
8.53E-14
8.69E-10
1.42E-10
5.00E-10
1.33E-10
4.60E-10
1.56E-12
Submersion Gnd Surfa
(per (per
y/m 3) E
5.96E-08
6.62E-0
1.39E-08
7.17E-08
5.95E-08
2.29E-07
3.81E-09
5.69E-11
7.56E-11
4.14E-14
1.09E-08
1.96E-08
4.20E-08
7.02E-08
1.20E-11
6.66E-09
2.34E-09
1.84E-08
1.09E-10
5.98E-11
1.55E-09
1.43E-07
3.31E-10
2.74E-09
!qy/m2)
1.19E-09
8 1.30E-09
2.78E-10
1.40E-09
1.20E-09
4.41E-09
7.53E-11
7.72E-12
6.78E-12
9.78E-16
2.42E-10
4.34E-10
8.67E-10
1.40E-09
1.37E-12
1.43E-10
5.79E-11
3.66E-10
1.21E-11
1.23E-12
3.14E-11
2.89E-09
1.22E-11
5.45E-11
2.50E-07 4.72E-09
2.26E-09
1.31E-10
1.77E-08
4.86E-11
1.13E-11
3.65E-10
2.02E-09 3.71E-11
2.20E-08
4.68E-10
1.57E-13 2.81E-09 5.64E-11
6.83E-10
5.60E-09
4.74E-12
1.79E-10
1.66E-11
7.87E-09
1.36E-08
6.29E-10
1.66E-10
2.96E-10
2.10E-11
Nuclide
Ingestion
(Bq-1)
Inhalation
(Bq-1)
Submersion Gnd Sur
(per
Bq y/m 3)
Sn-121m
Sn-125
Sn-126
Sb-122
Sb-124
Sb-125
Sb-126
Sb-126m
Sb-127
Sb-129
Te-125m
Te-127
Te-127m
Te-129
Te-129m
Te-131
Te-131m
Te-132
-122
-123
-125
-126
-129
-130
-131
-132
-133
-134
-135
Xe-122
Xe-123
Xe-125
Xe-127
Xe-129m
Xe-131m
Xe-133
Xe-133m
Xe-135
Xe-135m
Xe-137
Xe-138
))))))))
5.40E-11
4.53E-10
5.73E-10
2.38E-10
2.91E-10
8.02E-11
2.63E-10
1.97E-12
2.29E-10
5.02E-11
6.78E-11
2.31E-11
1.62E-10
4.00E-12
3.18E-10
1.05E-11
2.38E-10
3.29E-10
5.84E-13
1.47E-11
6.98E-10
1.30E-09
4.98E-09
1.31E-10
9.77E-10
1.79E-11
2.86E-10
6.25E-12
6.14E-11
)))))))
2.02E-10
3.23E-10
1.15E-09
1.47E-10
3.57E-10
1.41E-10
2.27E-10
1.74E-12
1.63E-10
2.32E-11
7.70E-11
1.17E-11
3.53E-10
3.96E-12
3.60E-10
6.71E-12
2.27E-10
2.26E-10
6.05E-13
7.94E-12
4.62E-10
8.52E-10
3.30E-09
7.06E-11
6.31E-10
9.51E-12
1.63E-10
3.74E-12
3.19E-11
8.34E-14
2.41E-14
3.25E-14
1.10E-14
1.55E-14
1.12E-14
1.12E-14
1.38E-14
2.01E-14
5.09E-15
3.76E-14
5.58E-14
lilt}}}}
2.08E-11
2.85E-08
3.74E-09
3.91E-08
1.76E-07
3.69E-08
(per
Bqy/m2)
"l1!1!1!1!*!1!1!
))))))))
7.39E-13
5.14E-10
9.36E-11
7.91E-10
3.12E-09
7.64E-10
2.47E-07 4.92E-09
1.40E-07 2.82E-09
5.89E-OE
1.32E-07
5.94E-10
1.18E-09
2.47E-09
2.57E-11
4.17E-10 8.81E-12
1.94E-10
4.70E-OE
8.24E-12
9.74E-11
2.97E-09 6.18E-11
3.72E-08
1.31E-07
1.83E-08
8.49E-08
1.33E-08
6.63E-10
3.97E-08
5.03E-10
1.91E-07
3.24E-08
2.09E-07
5.35E-08
2.43E-07
1.48E-07
4.99E-09
5.53E-08
2.12E-08
2.22E-08
1.65E-09
5.99E-10
2.62E-09
2.39E-09
2.12E-08
3.72E-08
1.67E-08
1.11E-07
7.49E-10
2.48E-09
4.10E-10
1.73E-09
3.00E-10
2.94E-11
8.06E-10
2.64E-11
3.80E-09
6.82E-10
4.02E-09
1.07E-09
4.54E-09
2.56E-09
1.18E-10
1.08E-09
4.65E-10
4.94E-10
6.31E-11
2.39E-11
7.38E-11
6.32E-11
4.59E-10
7.68E-10
3.29E-10
1.87E-09
-------
Table A.4b Revised Methodology radionuclide incidence risk coefficients, (cont.)
Internal External Internal External
Ol
CT3
Nuclide
Cs-131
Cs-134
Cs-134m
Cs-135
Cs-136
Cs-137
Cs-138
Ba-131
Ba-133
Ba-133m
Ba-137m
Ba-139
Ba-140
La-140
Ce-141
Ce-143
Ce-144
Pr-142
Pr-143
Pr-144
Pr-144m
Nd-147
Nd-149
Pm-147
Pm-148
Pm-148m
Pm-149
Sm-147
Sm-151
Sm-153
Eu-152
Eu-154
Eu-155
Eu-156
Gd-153
Gd-159
Tb-158
Tb-160
Dy-165
Dy-166
Ho-166
Ingestion
(Bq-1)
4.87E-12
1.28E-09
1.23E-12
1.22E-10
2.09E-10
8.54E-10
4.75E-12
4.59E-11
7.29E-11
7.47E-11
6.58E-14
8.23E-12
3.18E-10
2.56E-10
1.06E-10
1.60E-10
7.99E-10
1.89E-10
1.78E-10
2.18E-12
8.72E-13
1.59E-10
1.23E-11
3.82E-11
3.90E-10
Inhalation
(Bq-1)
Bq
2.87E-12
7.80E-10
8.39E-13
7.33E-11
1.26E-10
5.18E-10
3.51E-12
1.30E-11
1.09E-10
1.51E-11
4.24E-14
4.13E-12
8.57E-11
1.38E-10
1.17E-10
1.04E-10
2.91E-09
1.12E-10
1.51E-10
3.55E-12
1.52E-12
1.31E-10
1.14E-11
2.02E-10
2.83E-10
2.68E-10 7.96E-10
1.49E-10
6.78E-10
1.24E-11
1.09E-10
1.55E-10
2.53E-10
4.46E-11
2.95E-10
3.56E-11
7.03E-11
1.14E-10
2.06E-10
8.80E-12
2.55E-10
2.05E-10
9.64E-11
1.87E-07
1.25E-10
5.88E-11
2.14E-09
2.47E-09
2.59E-10
2.50E-10
8.66E-11
3.34E-11
1.90E-09
3.08E-10
6.06E-12
2.11E-10
1.10E-10
Submersion Gnd Surfa
(per
y/m 3) 1
4.35E-10
1.40E-07
1.63E-09
1.98E-07
2.26E-07
3.91E-08
3.09E-08
4.68E-09
5.34E-OE
3.02E-09
1.62E-08
2.18E-07
6.31E-09
2.24E-08
1.46E-09
5.52E-09
8.09E-16
3.18E-09
3.39E-10
1.11E-08
3.24E-08
2.96E-13
5.25E-OE
(per
3qy/m2)
2.42E-11
2.76E-09
4.32E-11
3.76E-09
3.82E-09
8.38E-10
6.96E-10
1.12E-10
! 1.07E-09
6.46E-11
3.41E-10
3.78E-09
1.43E-10
4.81E-10
3.42E-11
9.14E-11
1.59E-17
5.29E-11
1.29E-11
2.45E-10
6.94E-10
6.65E-15
1 9.47E-10
1.78E-07 3.54E-09
1.01E-09
5.54E-14
3.88E-09
1.03E-07
1.14E-07
4.43E-09
1.30E-07
6.67E-09
3.14E-09
6.92E-08
9.85E-OE
2.13E-11
6.42E-15
1.05E-10
1.94E-09
2.12E-09
1.10E-10
2.22E-09
1.85E-10
7.13E-11
1.31E-09
1 1.86E-09
2.06E-09 4.53E-11
2.36E-09
2.38E-09
6.48E-11
4.70E-11
Nuclide
Ingestion
(Bq-1)
Inhalation
(Bq-1)
Submersion Gnd Surl
(per
Bq y/m 3)
Er-169
Er-171
Tm-170
Tm-171
Yb-169
Yb-175
Lu-177
Hf-181
Ta-182
W-181
W-185
W-187
Re-183
Re-186
Re-187
Re-188
Os-185
Os-191
Os-191m
Os-193
lr-190
lr-192
lr-194
Pt-191
Pt-193
Pt-193m
Pt-197
Pt-197m
Au-196
Au-198
Hg-197
Hg-203
TI-202
TI-204
TI-207
TI-208
TI-209
Pb-203
Pb-209
Pb-210
Pb-211
111)))))
5.73E-11
4.41E-11
2.03E-10
1.58E-11
9.27E-11
6.49E-11
7.97E-11
1.48E-10
1.90E-10
7.36E-12
5.50E-11
6.65E-11
4.26E-11
8.12E-11
2.47E-13
8.63E-11
4.87E-11
8.22E-11
1.34E-11
1.18E-10
1.34E-10
1.74E-10
1.89E-10
4.05E-11
4.38E-12
6.77E-11
5.74E-11
8.79E-12
3.52E-11
1.43E-10
3.20E-11
7.15E-11
2.74E-11
5.33E-11
2.90E-13
4.73E-13
3.80E-13
2.79E-11
5.66E-12
1.82E-08
9.13E-12
)))))))
4.08E-11
2.03E-11
2.96E-10
4.97E-11
1.08E-10
4.54E-11
5.94E-11
1.67E-10
4.47E-10
2.17E-12
1.15E-11
1.43E-11
6.94E-11
7.06E-11
5.10E-13
6.25E-11
1.25E-10
7.30E-11
8.97E-12
7.24E-11
1.21E-10
3.04E-10
1.13E-10
1.12E-11
2.13E-12
1.56E-11
1.23E-11
2.72E-12
2.81E-11
9.83E-11
1.88E-11
8.18E-11
1.64E-11
3.12E-11
3.34E-13
3.68E-13
3.04E-13
8.38E-12
1.85E-12
4.51E-08
2.79E-10
lilt}}}}
1.52E-13
3.12E-08
(per
Bqy/m2)
"l1!1!1!1!*!1!1!
))))))))
7.63E-15
6.85E-10
3.47E-10 9.29E-12
3.75E-11
2.27E-08
3.33E-09
2.89E-09
4.65E-08
1.17E-07
2.37E-09
2.27E-12
4.17E-08
1.12E-08
1.63E-09
5.07E-09
6.21E-08
5.41E-09
3.03E-10
5.59E-09
1.22E-07
7.06E-08
8.04E-09
2.32E-08
3.28E-12
7.26E-10
1.79E-09
6.28E-C
3.97E-08
3.49E-08
4.75E-09
1.94E-08
3.94E-08
7.68E-11
2.01E-10
3.54E-07
1.95E-07
2.50E-OJ
9.09E-11
4.56E-09
1.12E-12
5.57E-10
7.21E-11
6.51E-11
9.85E-10
2.14E-09
6.71E-11
5.07E-14
8.52E-10
2.76E-10
3.82E-11
1.05E-10
1.26E-09
1.32E-10
8.84E-12
1.22E-10
2.52E-09
1.49E-09
1.62E-10
5.21E-10
8.32E-13
1.96E-11
4.32E-11
19 1.47E-10
8.65E-10
7.36E-10
1.21E-10
4.24E-10
8.43E-10
1.95E-12
3.81E-12
5.41E-09
3.45E-09
i 5.56E-10
4.16E-12
9.11E-11
-------
Table A.4b Revised Methodology radionuclide incidence risk coefficients, (cont.)
Internal External Internal External
Nuclide
Pb-212
Pb-214
Bi-206
Bi-207
Bi-210
Bi-211
Bi-212
Bi-213
Bi-214
Po-210
Po-212
Po-213
Po-214
Po-215
Po-216
Po-218
At-217
Rn-219
Rn-220
Rn-222
Fr-221
Fr-223
Ra-223
Ra-224
Ra-225
Ra-226
Ra-228
Ac-225
Ac-227
Ac-228
Th-227
Th-228
Th-229
Th-230
Th-231
Th-232
Th-234
Pa-231
Pa-233
Pa-234
Ingestion Inhalation Submersion Gnd Surf;
(Bq-1) (Bq-1) (per (per
Bqy/m 3) Bqy/m2)
4.87E-10 1.04E-09 1.23E-08 2.74E-10
7.94E-12 1.68E-10 2.12E-08 4.56E-10
1.92E-10 1.37E-10 3.01E-07 5.66E-09
1.37E-10 2.54E-10 1.39E-07 2.65E-09
1.97E-10 1.38E-09
4.93E-13 4.71E-11 4.05E-09 8.69E-11
1.68E-11 9.88E-10 1.69E-08 3.13E-10
1.19E-11 8.36E-10 1.20E-08 2.51E-10
5.27E-12 3.94E-10 1.44E-07 2.49E-09
8.80E-09 5.79E-08 7.79E-13 1.51E-14
1.22E-21 1.60E-19
1.81E-20 2.11E-18 2.79E-12 5.42E-14
5.74E-19 7.50E-17 7.63E-12 1.48E-13
1.35E-17 1.21E-15 1.29E-11 2.70E-13
2.38E-15 7.98E-14 1.33E-12 2.57E-14
1.37E-12 9.96E-11
2.43E-16 1.39E-14 2.11E-11 4.26E-13
1.87E-12 4.91E-09 1.05E-10
5.18E-12 4.58E-11 9.35E-13
4.96E-11 3.38E-11 6.97E-13
3.91E-12 2.17E-10 2.61E-09 5.76E-11
1.21E-11 1.60E-11 3.66E-09 9.23E-11
6.33E-09 9.74E-08 1.11E-08 2.50E-10
4.04E-09 6.08E-08 8.54E-10 1.86E-11
4.25E-09 6.44E-08 4.40E-10 1.96E-11
7.98E-09 7.35E-08 5.72E-10 1.27E-11
6.64E-09 2.60E-08 4.77E-18 9.99E-19
3.85E-09 1.12E-07 1.10E-09 2.65E-11
9.52E-09 1.91E-06 1.01E-11 3.24E-13
4.38E-11 8.84E-10 8.49E-08 1.60E-09
1.09E-09 1.16E-07 8.78E-09 1.97E-10
1.70E-09 2.55E-06 1.58E-10 4.34E-12
1.53E-09 2.05E-06 6.90E-09 1.66E-10
1.01E-09 4.66E-07 3.00E-11 1.33E-12
4.85E-11 2.97E-11 8.91E-10 2.83E-11
8.85E-10 5.21E-07 1.39E-11 9.57E-13
5.20E-10 5.15E-10 5.98E-10 1.54E-11
4.02E-09 6.54E-07 2.54E-09 5.92E-11
1.27E-10 1.33E-10 1.80E-08 3.97E-10
5.76E-11 3.51E-11 1.78E-07 3.42E-09
Nuclide
Ingestion
(Bq-1) (
Inhalation
Bq-1)
Submersion Gnd Surfac
(per (per
Bqy/m 3) Bqy/m2)
Pa-234m
U-232
U-233
U-234
U-235
U-236
U-237
U-238
U-240
Np-236
Np-237
Np-238
Np-239
Np-240
Np-240m
Pu-236
Pu-238
Pu-239
Pu-240
Pu-241
Pu-242
Pu-243
Pu-244
Am-241
Am-242
Am-242m
Am-243
Cm-242
Cm-243
Cm-244
Cm-245
Cm-246
Cm-247
Cm-248
Cf-252
1 1 1 1 ) 1 1 ,
1.29E-13
2.19E-09
1.21E-09
1.20E-09
1.22E-09
1.14E-09
1.08E-10
1.15E-09
1.48E-10
2.52E-11
7.98E-09
1.23E-10
1.15E-10
4.79E-12
6.54E-13
2.08E-09
7.98E-09
8.53E-09
8.52E-09
1.40E-10
8.11E-09
9.97E-12
8.46E-09
8.87E-09
3.96E-11
')))))))
1.70E-13
1.43E-06
3.82E-07
3.77E-07
3.51E-07
3.57E-07
8.43E-11
3.36E-07
9.06E-11
1.05E-10
9.33E-07
1.26E-10
6.52E-11
3.55E-12
7.64E-13
3.61E-07
7.42E-07
7.51E-07
7.51E-07
7.59E-09
7.13E-07
7.22E-12
7.20E-07
1.04E-06
2.81E-10
ill}}}}}}}}}}}}},
1.05E-09 1.98E-11
2.01E-11 1.47E-12
1.91E-11 7.46E-13
1.13E-11 1.13E-12
1.28E-08 2.84E-10
8.72E-12 1.02E-12
1.08E-08 2.58E-10
7.46E-12 8.97E-13
4.84E-11 5.36E-12
1.06E-08 2.53E-10
1.79E-09 4.92E-11
5.11E-08 9.48E-10
1.38E-08 3.15E-10
1.04E-07 2.04E-09
2.95E-08 5.80E-10
8.30E-12 1.34E-12
6.05E-12 1.16E-12
6.29E-12 5.28E-13
5.93E-12 1.11E-12
5.04E-12 9.20E-13
1.82E-09 4.46E-11
3.63E-12 7.81E-13
1.36E-09 4.26E-11
1.10E-09 2.84E-11
7.90E-09 9.43E-07 3.42E-11 3.69E-12
8.84E-09
1.03E-09
6.79E-09
5.69E-09
9.05E-09
8.97E-09
8.35E-09
3.54E-08
4.86E-09
1.03E-06
8.54E-08
7.81E-07
6.58E-07
1.06E-06
1.05E-06
9.68E-07
3.95E-06
7.01E-07
3.85E-09 9.92E-11
6.63E-12 1.23E-12
1.05E-08 2.40E-10
5.60E-12 1.10E-12
5.75E-09 1.36E-10
4.65E-12 9.67E-13
2.72E-08 5.78E-10
4.13E-12 7.76E-13
5.04E-12 8.22E-13
-------
Table A.5 Default inhalation clearance class and ingestion f l values by element.
Inhalation Ingestion
Element clearance f,
class
Inhalation Ingestion
Element clearance f,
class
H
Be
N
C"
0
F
Na
Si
P
S
Cl
Ar
K
Ca
Sc
V
Cr
Mn
Fe
Co
Ni
Cu
Zn
Ga
Ge
As
Se
Br
Kr
Rb
Sr
Y
Zr
Nb
Mo
Tc
Ru
Rh
Pd
Cd
In
Sn
Sb
Te
V
Y
D
D
D
D
D
W
D
D
D
D
W
Y
W
Y
W
W
Y
W
Y
Y
W
W
W
W
D
D
D
Y
W
Y
Y
W
Y
Y
Y
Y
Y
W
W
W
W
1.0E+00
5.0E-03
9.5E-01
9.5E-01
9.5E-01
9.5E-01
9.5E-01
1.0E-02
8.0E-01
8.0E-01
9.5E-01
9.5E-01
3.0E-01
1.0E-04
1.0E-02
1.0E-01
1.0E-01
1.0E-01
3.0E-01
5.0E-02
5.0E-01
5.0E-01
1.0E-03
9.5E-01
5.0E-01
8.0E-01
9.5E-01
9.5E-01
3.0E-01
1.0E-04
2.0E-03
1.0E-02
8.0E-01
8.0E-01
5.0E-02
5.0E-02
5.0E-03
5.0E-02
5.0E-02
2.0E-02
2.0E-02
1.0E-01
2.0E-01
Xe
Cs
Ba
La
Ce
Pr
Nd
Pm
Sm
En
Gd
Tb
Dy
Ho
Er
Tm
Yb
Lu
Hf
Ta
W
Re
Os
Ir
Pt
An
Hg
Tl
Pb
Bi
Po
At
Rn
Fr
Ra
Ac
Th
Pa
U
Np
Pu
Am
Cm
Cf
D
D
D
W
Y
Y
Y
Y
W
W
W
W
W
W
W
W
Y
Y
W
Y
D
W
Y
Y
D
Y
W
D
D
W
W
D
D
W
Y
Y
Y
Y
W
Y
W
W
Y
9.5E-01
9.5E-01
1.0E-01
1.0E-03
3.0E-04
3.0E-04
3.0E-04
3.0E-04
3.0E-04
1.0E-03
3.0E-04
3.0E-04
3.0E-04
3.0E-04
3.0E-04
3.0E-04
3.0E-04
3.0E-04
2.0E-03
1.0E-03
3.0E-01
8.0E-01
1.0E-02
1.0E-02
1.0E-02
1.0E-01
2.0E-02
9.5E-01
2.0E-01
5.0E-02
1.0E-01
9.5E-01
9.5E-01
2.0E-01
1.0E-03
2.0E-04
1.0E-03
5.0E-02
1.0E-03
1.0E-03
1.0E-03
1.0E-03
1.0E-03
Tor 14C, clearance class is *, f, is 1.0.
58
-------
References for Appendix A
C.L. Chiang, An Introduction to Stochastic Processes and Their Applications, Robert E.
Krieger Publishing Company, Inc., Huntington, NY, 1980.
J.R. Cook, B.M. Bunger, and M.K. Barrick, A Computer Code for Cohort Analysis of
Increased Risks of Death (CAIRD), EPA 520/4-78-012, U.S. Environmental Protection
Agency, Washington, DC, June 1978.
C. de Boor, A Practical Guide to Splines, Applied Mathematical Sciences Vol. 27, Springer-
Verlag, New York, NY, 1978.
F.N. Fritsch and J. Butland, A Method for Constructing Local Monotone Piecewise Cubic
Interpolants, UCRL-87559, Lawrence Livermore National Laboratory, April 1982.
National Center for Health Statistics, Vital Statistics Mortality Data, Detail, 1979, PB82-
132340, U.S. Department of Health and Human Services, Public Health Service, National
Center for Health Statistics, Hyattsville, MD, 1982.
National Center for Health Statistics, Vital Statistics Mortality Data, Detail, 1980, PB83-
261545, U.S. Department of Health and Human Services, Public Health Service, National
Center for Health Statistics, Hyattsville, MD, 1983.
National Center for Health Statistics, Vital Statistics Mortality Data, Detail, 1981, PB84-
213008, U.S. Department of Health and Human Services, Public Health Service, National
Center for Health Statistics, Hyattsville, MD, 1984.
National Center for Health Statistics, U.S. Decennial life Tables for 1979-1981, Vol. 1, No. 1,
United States Life Tables, (PHS) 85-1150-1, U.S. Department of Health and Human Services,
Public Health Service, National Center for Health Statistics, Hyattsville, MD, August 1985.
National Institutes of Health, Report of the National Institutes of Health Ad Hoc Working
Group to Develop Radioepidemiological Tables, NIH Publication 85-2748, Superintendent of
Documents, U.S. Government Printing Office, Washington, DC, 1985.
National Research Council, Health Effects of Exposure to Low Levels of Ionizing Radiation
(BEIR V), Committee on the Biological Effects of Ionizing Radiations, Board of Radiation
Effects Research, Commission on Life Sciences, National Research Council, National
Academy Press, Washington, DC, 1990.
Public Health Service, The International Classification of Diseases, 9th Revision, Clinical
Modification (ICD-9-CM), Vol. 1 Diseases: Tabular List, DHHS Publication No. (PHS) 80-
1260, U.S. Department of Health and Human Services, Public Health Service—Health Care
59
-------
Financing Administration, Superintendent of Documents, U.S. Government Printing Office,
Washington, DC, 1980.
A.L. Sjoreen, Reconstruction of the RADRISK Database, Oak Ridge National Laboratory,
Oak Ridge, TN, (to be published) 1994.
M. Vaeth and D.A. Pierce, Calculating Excess Lifetime Risk in Relative Risk Models, RERF
CR 3-89, Editorial Office, Radiation Effects Research Foundation, Hiroshima, Japan,
November 1989.
60
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