United States
Environmental Protection
Agency
Health Effects Research
Laboratory
Research Triangle Park NC 27711
EPA-600/1-80-009
January 1980
Research and Development
Pilot  Study
Ambient Air
Pollution  and
Survival from  Cancer

-------
                RESEARCH REPORTING SERIES

Research reports of the Office of Research and Development, U.S. Environmental
Protection Agency, have been grouped into nine series. These nine broad cate-
gories were established to facilitate further development and application of en-
vironmental technology.  Elimination  of traditional grouping was  consciously
planned to foster technology transfer and a maximum interface in related fields.
The nine series are:

      1.   Environmental  Health Effects Research
      2.   Environmental  Protection Technology
      3.   Ecological Research
      4.   Environmental  Monitoring
      5.   Socioeconomic Environmental Studies
      6.   Scientific  and Technical Assessment Reports (STAR)
      7.   Interagency  Energy-Environment Research and Development
      8.   "Special"  Reports
      9.   Miscellaneous Reports
This report has been assigned to the ENVIRONMENTAL HEALTH EFFECTS RE-
SEARCH series. This series describes projects and studies relating to the toler-
ances of man for unhealthful substances or conditions. This work is generally
assessed from a medical viewpoint, including physiological or psychological
studies. In addition to toxicology and other medical specialities, study areas in-
clude biomedical instrumentation and health research techniques utilizing ani-
mals  but always  with  intended application to human health measures.
This document is available to the public through the National Technical Informa-
tion Service, Springfield, Virginia 22161.

-------
                                                  EPA-600/1-80-009
                                                  January  1980
    PILOT STUDY OF AMBIENT AIR POLLUTION
          AND SURVIVAL FROM CANCER
             Gregg S. Wilkinson
         Population Studies Division
     Health Effects Research Laboratory
    U.S.  Environmental Protection Agency
Research Triangle Park, North Carolina  27711
                     and
               Peter A.  Reese
               Roger L.  Priore
               Computer Center
       Roswell Park Memorial Institute
     New York State Department of Health
               666 Elm Street
          Buffalo, New York  14263
     Health Effects Research Laboratory
     Office of Research and Development
    U.S. Environmental Protection Agency
Research Triangle Park, North Carolina  27711

-------
                               DISCLAIMER
     This report has been reviewed by the Health Effects Research Labora-
tory, U.S. Environmental Protection Agency, and approved for publication.
Mention of trade names or commercial products does not constitute endorse-
ment or recommendation for use.
                                    11

-------
                                FOREWORD


     The many benefits of our modern, developing, industrial  society are
accompanied by certain hazards.   Careful assessment of the relative risk of
existing and new man-made environmental  hazards is necessary for the estab-
lishment of sound regulatory policy.  These regulations serve to enhance the
quality of our environment in order to promote the public health and welfare
and the productive capacity of our Nation's population.

     The Health Effects Research Laboratory, Research Triangle Park, conducts
a coordinated environmental health research program in toxicology, epidemio-
logy, and clinical studies using human volunteer subjects.  These studies
address problems in air pollution, non-ionizing radiation, environmental
carcinogenesis and the toxicology of pesticides as well as other chemical
pollutants.  The Laboratory participates in the development and revision
of air quality criteria documents on pollutants for which national ambient
air quality standards exist or are proposed, provides the data for registra-
tion of new pesticides or proposed suspension of those already in use,
conducts research on hazardous and toxic materials, and is primarily respon-
sible for providing the health basis for non-ionizing radiation standards.
Direct support to the regulatory function of the Agency is provided in the
form of expert testimony and preparation of affidavits as well as expert
advice to the Administrator to assure the adequacy of health care and
surveillance of persons having suffered imminent and substantial endanger-
ment of their health.
     This report presents the results of a pilot study concerned with
investigating the possible association between the length of survival of
diagnosed cancer patients and ambient levels of particulates and sulfur
dioxide characterizing their area of residence.  Previous studies have
shown increased mortality among elderly and chronically ill populations
during air pollution disasters.  There has also been increasing evidence
of a possible influence exerted by air pollution upon cancer incidence
and mortality.  However, the influence that exposure to air pollutants may
have upon the survival time of a severely stressed and especially suscep-
tible population, such as diagnosed cancer patients, has yet to be
evaluated.  The results of this preliminary study suggest that high levels
of ambient air pollution may adversely affect the health of certain types
of cancer patients.  Additional research of this nature is clearly
warranted.

                                    F. G. Hueter, Ph.D.
                                    Di rector
                                    Health Effects Research Laboratory

                                   iii

-------
                                ABSTRACT
     This study was concerned with investigating the potential influence
exerted by ambient concentrations of particulate and sulfur dioxide air
pollutants upon the length of survival  for diagnosed cancer patients.
Monitoring data from the National Aerometric Data Bank for particulates
and sulfur dioxide were examined in conjunction with survival data from
the Lakes Area Regional Tumor Service Registry.   Length of survival for
respiratory cancer patients was found to be inversely related to maximum
particulate levels.  Survival times for patients who resided in areas
                                                  3
where maximum particulate levels exceeded 240 |jg/m  were significantly
shorter than for similar patients who resided in areas with lower particu-
late levels.  Colorectal cancer patients demonstrated a similar trend
that was not statistically significant.   No association was found between
survival of leukemia patients and particulate or SOp levels, nor was S02
related to survival of respiratory tract or colorectal cancer patients.
These findings suggest that highly polluted air in residential areas may
have a deleterious effect on the survival time of patients with certain
types of neoplastic disease.  Additional research is called for of the
relationship between cancer survival and exposure to ambient air pollution,
especially particulates.

-------
                            TABLE OF CONTENTS
                                                                 Page
Disclaimer	       ii
Foreword	      iii
Abstract 	        v
List of Tables and Figures	      vii
Acknowledgment 	     viii
Section 1.  Introduction 	       1
Section 2.  Conclusions	       4
Section 3.  Recommendations	       5
Section 4.  Materials and Methods	       7
Section 5.  Results and Discussion  	      10
Section 6.  References 	 22
                                   VI

-------
                           TABLES AND FIGURES

                                                                 Page

Table 1:  Cases Available for Analysis ...........       9

Table 2:  Annual Averages of Mean and Maximum Particulates
          by Zip Code ....................       ]1
Table 3:  Annual Averages of Mean and Maximum Sulfur Dioxide
          Levels by Zip Code ................      12

Table 4:  Regression Model for Survival by Cancer Site, Mean
          and Maximum Levels of Particulates and Sulfur
          Dioxide ......................      13

Table 5:  Differences in Median Survival by Cancer Site,
          Mean and Maximum Particulate Levels ........      15

Figure 1: Survival from Respiratory Cancer by Maximum
          Particulate Levels ................      14

Figure 2: Survival from Respiratory Cancer by Mean
          Particulate Levels ................      17

Figure 3: Survival from Leukemia by Mean Particulate
          Levels ......................      18

Figure 4: Survival from Leukemia by Maximum Particulate
          Levels ......................      19

Figure 5: Survival from Colorectal Cancer by Mean
          Particulate Levels ................      20

Figure 6: Survival from Colorectal Cancer by Maximum
          Particulate Levels ................      21
                                    vn

-------
                             ACKNOWLEDGMENT
     This investigation was a cooperative effort jointly conducted by
the Epidemiology Branch, Health Effects Research Laboratory, U.S. Environ-
mental Protection Agency, and the Computer Center, Roswell Park Memorial
Institute, New York State Department of Health.  The computer analyses
were funded by USEPA Purchase Contract No. DA-8-6122J, Gregg S. Wilkinson,
Project Officer.
     Gerald Nehls, Statistics and Data Management Office, Health Effects
Research  Laboratory, U.S. Environmental Protection Agency, contributed
greatly to the study effort by obtaining and providing air quality data
from the  SAROAD system.  Deborah Lorshbough aided in data entry activities
involving both the Lakes Area Regional Tumor Service Registry and the
SAROAD information.
                                   vi ii

-------
                        SECTION 1.   INTRODUCTION
     It has been recognized for many years that air pollution may have
untoward consequences for human health.   This concern has been reinforced
by the health effects that have been observed pursuant to the occurrences
of several major air pollution disasters.   For instance, in 1930, a
large number of residents in the Meuse Valley, Belgium, became severly
ill after the Valley was blanketed for three days by a combination of
industrial smoke and fog.  Approximately sixty deaths from heart failure,
mostly among the elderly and chronically ill, were attributed to this
episode.  Sulfur oxides and fluorine may have been the major culprits
(1).   More recent episodes that are thought to have had serious health
consequences have occurred in Donora, Pennsylvania (2), London (3), Los
Angeles and Piscataway, New Jersey (4).
     During the past decade, considerable attention has been directed
toward potential environmental precursors of malignant neoplasms.
Evidence of an environmental effect has come from several sources.
Studies of migrants have shown their rates for several types of cancer
to vary from those of their former homeland to those of their adopted
country, and among succeeding generations (5,6,7).  Several reports have
demonstrated considerable variation in cancer incidence or mortality
rates between industrialized and less developed countries (8,9).  Within
the United States, differences in county cancer mortality rates have
also been shown (10).  In addition, several studies have shown a tendency
of rates for many types  of cancers in urban areas to exceed rates in
rural areas (11).

-------
     The contribution of exposure to air pollutants in the ambient air
to the etiology of most cancers has yet to be demonstrated for most
cancer sites.  The effects of occupational exposures to such substances
as asbestos, dust in uranium mines, vinyl chloride, and beta naphthylmine
are well known.  The urban excess for lung cancers as well as the results
of several studies showing excess rates among residents of heavily
polluted urban neighborhoods suggests that air pollution may exert a
significant etiologic effect (12).
     Most considerations of a potential air pollution effect for neoplasms
are concerned with an etiological influence.  However, if we review the
findings of studies concerned with the health consequences of air pollution
disasters, we find that major effects occur mainly among the elderly and
those suffering from a chronic illness.  This suggests that rather than
concentrating only upon the etiologic significance of air pollutants, it
may be worthwhile to investigate  health effects among those individuals
who are already severely stressed (13).
     No investigations have yet been conducted of the possible influence
of ambient air pollution levels upon the survival time of individuals
who have been diagnosed and undergone treatment for cancer.  Based upon
the previously mentioned findings, it would appear that such individuals
would comprise a population highly susceptible to contaminants in the
ambient air.  Approximately one-third of those who contract cancer
survive for five years or more after being diagnosed.  Furthermore, the
treatments employed often carry such side effects as depressed immunity
and decreased resistance to infection.  These factors suggest that many

-------
cancer patients residing in heavily polluted areas may be more highly
susceptible to systemic infections, respiratory problems and other
complications than are similar patients who reside in less polluted
regions.   If true, this would result in decreased survival times for
patients from highly polluted areas, especially those with respiratory
involvement such as lung cancer patients,  or those with depressed immunity
as a result of treatment such as leukemia  patients.

-------
                         SECTION 2.  CONCLUSION
     The analyses performed in this pilot study revealed a significant
association between length of survival from diagnosis for respiratory
cancer patients and high maximum particulate levels characterizing area
of residence.  No significant effects for levels of particulates or
sulfur dioxide upon survival were found for leukemia or colorectal
cancer patients.  However, the relationship of maximum particulate
levels to the survival of these patients, although not statistically
significant, was in the same direction as that of survival among respira-
tory cancer patients.
     Since the methods employed in this pilot study to measure exposure
to air pollution were crude, it is not surprising that more significant
results were not found.  Many assumptions were required and knowledge of
the ambient pollutant levels under which cancer patients live is, at
best, approximate.  The results that were obtained indicate that more
precise measurements may yield clear-cut detrimental influences of air
pollution upon cancer survival after diagnosis and treatment.
     These findings imply that exposure to very high levels of particu-
lates may prove harmful to patients with respiratory cancer as indicated
by decreased survival times.  The  same may hold true for similar patients
who are exposed to very high levels of sulfur dioxide and for colorectal
patients exposed to high levels of these same pollutants.  However,
because of the crude manner in which exposure was measured in this pilot
study, we may only conclude that such a possibility may exist and that
additional research is clearly warranted.

-------
                       SECTION 3.   RECOMMENDATIONS
     Since this pilot study was a limited effort and primarily an assess-
ment of feasibility, recommendations will be constrained to suggestions
for future research.
     A large number of assumptions were necessary in order to obtain
estimates of effluent levels representative of the environment in which
a cancer patient resided.   For example, it must be assumed that mean
values of ambient pollution levels in the zip code area that included
both the monitoring station and the patient's residence were representative
of the exposures experienced by the patient after diagnosis and treatment
of his condition.  Fortunately, the precision of these estimates can be
improved in several ways.   First, annual  isopleth maps for particulates
and sulfur dioxide, as well as other pollutants, should be used to
provide a more precise measure of mean and maximum levels in the immediate
area of a given residence.   Second, the residence of each cancer patient
needs to be more accurately located than is possible by zip code alone.
Paper records of patient residence addresses are available from the
Lakes Area Regional Tumor Service Registry and will be used in conjunction
with a follow-up effort.  Third, variables that may affect survival such
as stage of disease, tumor grade, type of treatment as well as socioeco-
nomic status should be included in future analyses.  In the present
study, a lack of reliable information on some of these factors as well
as further erosion of the amount of cases available for analysis precluded
their inclusion.

-------
     Improved accuracy in evaluating the correlation of pollution to
survival can be obtained by plotting patient residences on an accurate
contaminant isopleth map.  In addition, since no cases would be eliminated
for lack of a pollutant reading in the zip code area where the patient
resided on the year of diagnosis, more Registry cases would be available
for analysis.  If the above recommendations were adopted, the patient
sample sizes would double.
     Although the findings of this pilot study do not allow definitive
conclusions or recommendations regarding the association between pollutant
levels and survival to be made, they do suggest that further examination
of this problem is desirable.  The additional expense and effort that is
necessary to achieve an acceptable degree of accuracy does seem warranted
on the basis of these preliminary findings.  Thus, the primary recommenda-
tion is to conduct additional investigations of this potential problem.

-------
                    SECTION 4.   MATERIALS AND METHODS
     The purpose of this pilot study was to assess the influence that
air pollution may exert upon the survival of diagnosed cancer patients.
It was hypothesized that length of survival would be inversely associated
with levels of air .pollutants.   Survival among respiratory cancer patients
would be affected because of involvement of the respiratory system.
Leukemia patients were selected because of the depressed immunity they
experience as a result of treatment.   Colorectal  patients were chosen as
a comparison group.  Such patients do not have the direct involvement of
the respiratory tract as do lung cancer patients, and they do not experience
depressed immunity from therapeutic procedures to the same extent as do
leukemia patients.
Data Preparation
     Data from the Lakes Area Regional Tumor Service Registry were
combined with pollution levels from the National  Aerometric Data Bank to
produce information sets for various cancer sites.  Site by site analyses
were then performed to determine the relationship between ambient pollutant
levels and survival from date of diagnosis.
     The Lakes Area Regional Tumor Service Registry contains data on
approximately 26,000 cancer patients who were treated at hospitals
located in western New York and northern Pennsylvania.  The Registry
master file contains various elements of demographic data as well as
treatment summary and follow-up information.  For this study, residence
zip code, diagnosis date, site of histology (ACS Red Book codes), date
of last follow-up and patient status were the main parameters extracted
from the master file.

-------
     The National Aerometric Data Bank contains mean and maximum readings
for various sampler sites scattered about the catchment area of the
Lakes Area Registry.  The pollutants sampled and the years in which
sampling was conducted varies widely between sampler locations.  While
particulates were generally sampled, the years in which sampling actually
took place were somewhat variable.  A visual inspection indicates that
sulfur dioxide was the only other pollutant recorded consistently enough
to allow meaningful determination of its affect on survival.
     The first step of the analysis was to determine the zip code zone
in which the various samplers are located.  It was then possible to
construct data files containing records of sampler site, zip code, and
mean and maximum pollutant levels for the years 1970 through 1976.  The
files were then sorted by zip code, and average values for maximum and
mean ambient concentrations were computed by year within each zip code.
This process was repeated for particulates and sulfur dioxide.
     Next a computer program was written to collate the pertinent informa-
tion on each patient in the Lakes Area Registry with the average pollutant
level in the residence zip area during the year of diagnosis.  Cases
were eliminated who were diagnosed before 1970, had a residence zip code
outside of western New York, had no pollutant sample values in their zip
code area for the year of diagnosis, or contained an obvious data error.
The total number of cases and the number available for analysis by
pollutant are given for the initial sites of interest in Table 1.
                                   8

-------
       TABLE 1.   CASES AVAILABLE FOR ANALYSIS BY TYPE OF POLLUTANT
                                                        Cases Available
                                                         for Analysis
                                                      Particulate
              Site                    Total  Cases       Matter        Sp_2
Leukemia (ACS Red Book Histology)         577             315         154
           Code 9800-9949
Respiratory (ACS Red Book Site)          2622            1463         774
           Code 1600-1639
Colorectal (ACS Red Book Site)           3163            1687         865
           Code 1530-1539
The reduced number of evaluable cases under sulfur dioxide is due to the
smaller number of sampler recordings for that pollutant.
Cox Modeling
     A series of Cox Modeling analyses were then performed on the various
data sets.  Cox Modeling is a multivariate nonlinear regression technique
designed to accommodate censored data in the analysis of survival.  The
technique allows the assessment of the effect of multiple covariates on
hazard function and, thus, survival under the assumption of exponential
failures (14).
Life Tables
    Life table analyses were conducted using mean and maximum particulate
levels to form exposure groups.  Breslow tests were completed in order
to determine the significance of the difference in survival distributions
between the two groups (15).

-------
                   SECTION 5.   RESULTS AND DISCUSSION
     Average mean and maximum levels of particulate matter for the years
1970 thru 1976 were categorized for the zip codes corresponding to the
sampler locations.  Tables 2 and 3 present these data.
     Several observations are worth discussion.   First, it is obvious
that considerably more data regarding particulates are available than
for sulfur dioxide.  This has a direct bearing on the types of analyses
that may be conducted.  Also, the range of variation tends to be much
greater for maximum particulate levels than for mean levels by both
sampler location and year of measurement.
     A problem that immediately surfaces concerns depletion of the
number of patients available for analysis due to a lack of or inconsist-
ency of monitoring data.  Regarding particulate matter, this problem is
especially observable for data collected during the early seventies.   On
the other hand, the number of stations measuring sulfur dioxide levels
was much less than the number measuring particulate matter.
     Initially, a series of univariate regression analyses were conducted
to determine the relationship between pollutant level and risk of death.
As demonstrated by Table 4, the risk of death among leukemia and colorectal
patients is not significantly associated with either mean or maximum
particulate levels, nor mean or maximum levels of sulfur dioxide.
However, for respiratory cancer patients, the risk is significantly
associated with maximum particulate levels.
                                  10

-------
             TABLE 2.  AVERAGES* OF MEAN AND MAXIMUM 'ARTICULATE COUNTS Bv HP CODE
Zip
Code
14006
14011
14020
14031
14043
14048
14063
14070
14072
14080
14086
14092
14094
14101
14105
14120
14131
14132
14136
1*150
1*174
14203
14206
14207
14210
14211
1*212
14213
14214
14215
14216
14217
14213
14219
14220
14221
14224
14225
14225
H301
14302
14303
14304
14305
14482
14569
14701
14706
14719
14733
14760
14772
14802
14895
1970
Mean





58



42

74
59
45
53
117

59

95


134

181
32
97

76



162




ICC


118

215
111

41
75

42

63
40


Max





131



91

188
141
94
140
263

117

199


162

592
156
250

144



425




210


259

512
276

53
195

120

393
89


1971
Mean


67


63



53
50
84
70
48
57
121

57

105

103
134

152
79
93

87

94
92
126
75
86

67
58
72
111
110
107
128
;o7

62
81

50
52
64
45


Max


136


134



386
95
222
197
106
144
254

135

296

222
333

335
137
211

357

323
202
321
150
177

146
304
1*0
213
249
215
307
227

346
201

114
121
117
106


1972
Mean
38
26
58


64



38
51
85
64
45
51
82

53
42
82

95
117
70
137
76
78

72

81
37
117
78
102

76
92
74
108
104
103
109
98

53
78
25
44
42
56
41

27
Max
106
31
122


128



94
117
192
137
131
111
152

109
65
159

237
292
128
363
135
146

139

182
155
275
282
279

254
214
133
226
174
222
230
219

166
197
46
126
88
164
95

66
1973
Mean
39
46
53


57



41
53
31
59
45
56
74

50
57
72

37
112
74
136
79
75

65


73
125
68
104

65
72
70
101
101
71
96
93

48
75
54
30
44
54
29

49
Max
114
114
138


177



124
179
209
235
128
168
159

122
139
142

236
279
120
309
204
145

1*1


134
371
151
351

139
163
160
251
241
95
272
193

113
225
342
70
129
139
63

1J3
1974
Mean
44
31
45
17
58
58


46
34
48
68
57
38
47
54

47
76
81

34
99
72
136
61
70

62
74

69
13*
64
34
70
73
75
69
96
33

35
95

42
66
39
25
35
62
2*
23
34
Max
180
72
110
122
155
134


35
72
ill
167
126
115
96
124

119
718
151

266
259
136
312
108
128

108
157

123
385
174
236
145
201
212
148
224
153

195
293

119
172
121
58
31
164
57
14
'I
1975
Mean
47
40
47
48
58
60


49
45
49
68
59
45
57
63

54
55
113
56
82
74
74
103
60
63

55
79

69
137
71
36
34
66
71
75
99
75

93
39

55
73
36
33
34
18
37
23
40
Max
120
97
98
132
140
132


115
110
128
175
141
109
147
143

1-9
102
286
114
201
189
156
243
122
123

110
202

130
379
153
239
223
142
158
219
196
154

201
174

115
192
92
100
78
9*
82
6"1
103
1976
Mean
40
36
36
44
54
49



36
43
55
50
39
*6
56
*4
45
52
115
49
60
99
68
110
60
61

48
60

56
111
56
91

59
72
=3
75
64

76
63

44
43
38
36
39
49
32
25
29
Max
110
110
65
141
156
143



119
158
139
150
103
132
155
127
121
141
345
148
151
281
157
253
137
172

134
154

127
289
234
414

177
177
155
191
140

172
154

109
141
117
96
106
104
110
39
1-2
'Values are _g.-IT
                                              11

-------
           TABLE 3.  AVERAGES* OF MEAN AND MAXIMUM SULFUR DIOXIDE COUNTS 9Y ZIP CODE
Zip
Code
14006
14011
14020
14031
14043
14048
14063
14070
14072
14080
14086
14092
14094
14101
14105
14120
14131
14132
14136
14150
14174
14203
14206
14207
14210
14211
14212
14213
14214
14215
14216
ua?
1421S
14219
14220
14221
14224
14225
14226
14253
14:01
14302
14303
143C4
14305
14432
14559
14701
14706
14719
14733
1*760
14772
1-202
14895
1970 1971 1972 1973
Mean Max Mean Max Mean Max Mean Max


1








39 150 29 150 35 196 42
14 36 22 73 41

33
26 78 30 73 42

54

10 10 4 25 22


40 290 33 480 34
10
16 40 8 40 35
22




13 30 2 10
10
24




10 20 1 30 16
24


38 2 1C 21 U3 2' 131 30

41 131 50 244 67
50 50


7 12 15









1








145
112

49
87

105

60


569
10
80
50





10
70




50
50


660

164



84







1974
Mean Max


1


10



8

19
24

22
31

29

12

14
28

26
12
14

13


11
17




14
13


20

34


15
14


7


3



3


39



28

111
120

139
164

172

50

45
279

110
50
40

50


46
42




60
60


220

159


69
87


23


17

1975
Mean Max


1


11



5

11
11

11
13

10

14

16
26

32
11
9

8


9
15

20


12
10


16

19


11
11


4


4



4


87



28

51
42

41
91

37

64

48
234

145
45
30

36


44
55

40


42
35


82

02


40
96


43


42

1976
Mean Max


1


3



6

9
13

9
18

11

13

10
24

37
11
12

11


15
21

19


13
10


12

17


11
13


4


1



10


12



32

56
47

31
80

65

70

38
183

157
60
41

42


79
67

51


42
33


67

74


38
100


35


6

; /a1 js  ars  t,g/ n"
                                                12

-------
    TABLE 4.   REGRESSION TABLE  FOR  CANCER  SITE AND TYPE OF  POLLUTANT
                                           Coefficient of         Significance
Site                   Covariate            Covariate  (pi)           of  Pi
Leukemia            Mean Particulate           .1328E-02                .61
                    Max.  Participate          -.3950E-03                .62
                    Mean S09                 -.9680E-02                .33
                    Max.  SOg                  .1177E-02                .29
Respiratory         Mean Particulate           .6741E-03                .55
                    Max.  Particulate           .6671E-03                .05
                    Mean SO,                 -.2374E-02                .51
                    Max.  SOg                  .2982E-03                .48
Colorectal          Mean Particulate           .1491E-02                .25
                    Max Particulate           .5859E-03                .17
                    Mean S09                  .5893E-02                .88
                    Max.  SO                   .3495E-03                .45
     This finding is further supported by Figure 1 which  presents  an
actuarial survival comparison of respiratory cancer patients  residing in
areas with maximum particulate levels of 240 ug/m  or less  versus  areas
with higher levels.   The difference between these two curves  is  statisti-
cally significant at the a = .05 level.   Individuals residing in areas
                                    o
where maximum levels exceed 240 pg/m  consistently display  poorer  survival
than those residing in less polluted areas.
     Table 5 presents in somewhat greater detail the relationship  between
cancer site, particulate levels and median survival.  The only significant
difference in survival once again occurs for respiratory  tract cancers.
Median survival for patients residing in areas characterized by maximum
                                     o
particulate levels less than 240 ug/m  is 7.0 months compared to 5.2
months in higher pollution areas.
                                  13

-------
                             Figure 1
              SURVIVAL FROM RESPIRATORY CANCER BY.
                  MAXIMUM PARTICULATE LEVELS
                       I         I         I
                          PARTICULATE LEVELS

                                 0-240

                                  >240
cc
3
CO
01
o
cc
HI
       BRESLOW TEST RESULTS: p < .05
                                14

-------
         TABLE 5.   MEDIAN SURVIVAL BY PARTICIPATE LEVELS AND CANCER SITE

                                         Median      Significance of Difference
Site                  Groups            Survival      in Survival Distributions
Leukemia         I - Mean Part.  0-80    15.2 mo.                 NS
                II - Mean Part.  > 80    17.4 mo.
Leukemia         I - Max. Part.  0-240   15.9 mo.                 NS
                II - Max. Part.  > 240   15.1 mo.
Respiratory      I - Mean Part.  0-80     6.7 mo.                 NS
                II - Mean Part.  > 80     6.3 mo.
Respiratory      I - Max. Part.  0-240    7.0 mo.               p < .05
                II - Max. Part.  > 240    5.2 mo.
Colorectal       I - Mean Part.  0-80    24.5 mo.                 NS
                II - Mean Part.  > 80    22.8 mo.
Colorectal       I - Max. Part.  0-240   24.3 mo.                 NS
                II - Max. Part.  > 240   22.6 mo.
    Qualifications
         It is important to understand the assumptions underlying the Cox
    Modeling performed.  It must be assumed that the mean value of the
    ambient concentrations in the zip code area of residence during the year
    of diagnosis is representative of the conditions under which the cancer
    patient lived the remainder of his life.  This is indeed a considerable
    supposition.  A cursory inspection of the time progression of particulate
    and SO2 levels indicates a tendency for the mean reading to decline with
    time.  Also, maximum values demonstrate no consistent trend which may be
    attributed to sampling being conducted on a periodic schedule such as
                                       15

-------
every third day rather than daily.  This indicates that even if a cancer
patient remained at home after being diagnosed, the mean level to which
he or she was exposed probably declined.
     Finally, it should be remembered that this was a pilot study designed
to assess, in a preliminary manner, whether the hypothesis that length
of survival among diagnosed cancer patients was associated with ambient
pollutant levels is worthy of continued investigation.  Although the
only significant relationship found was between survival of respiratory
cancer patients and maximum particulate levels, the same trend was also
observed for both colorectal and  leukemia patients.  Given the crude
measures consisting of available  data that were employed in this investi-
gation, one might argue that any  bias that might exist would be against
obtaining significant findings.   Thus,  it may  be concluded that, although
definitive statements about a possible  association between the length of
survival of cancer patients and ambient concentrations of particulate
matter are not yet warranted, continued investigation of this potential
problem is justified.
                                   16

-------
C9
CC

C/l
H

ui
u
oc
IU
a.
100

 90


 80


 70


 60



 50




 40





 30
    20
    10
                                Figure 2
               SURVIVAL FROM RESPIRATORY CANCER BY

                     MEAN PARTICULATE LEVELS
                                          T         I

                                     PARTICULATE LEVELS


                                             0-80
                                          >80
               10
                     20
  30


MONTHS
40
50
60
       BRESLOW TEST RESULTS: NOT SIGNIFICANT
                                    17

-------
   100

    90

    80


    70


    60


    50

z

E   40

oc

CO
z
LLJ
O
cc
Ul
a.
    30
    20
    10
                             Figure 3
                     SURVIVAL FROM LEUKEMIA BY
                      MEAN PARTICULATE LEVELS
                         I
                   I         I

              PARTICULATE LEVELS
            	  0-80
            	   >80
               10
20
                                  30


                                 MONTHS
40
50
60
       BRESLOW TEST RESULTS: NOT SIGNIFICANT
                                 18

-------
                               Figure 4
                      SURVIVAL FROM LEUKEMIA BY
                     MAXIMUM PARTICULATE LEVELS
>

cc
M
B
oc
1U
                                   PARTICULATE LEVELS
                                           0-240
                                             >240
       BRESLOW TEST RESULTS: NOT SIGNIFICANT
                                  19

-------
                               Figure 5
               SURVIVAL FROM COLORECTAL CANCER BY

                     MEAN PARTICULATE LEVELS
o
cc

V)
I-

III
o
cc
UJ
a.
                                   PARTICULATE LEVELS

                                            0-80
                                  	>80
       BRESLOW TEST RESULTS: NOT SIGNIFICANT
                                  20

-------
                              Figure 6
   100


    90


    80



    70



    60
O   en
Z   50
    40
I
o
K


30
    20
    10
              SURVIVAL FROM COLORECTAL CANCER BY

                   MAXIMUM PARTICULATE LEVELS
                                     T
                   I
                                 PARTICULATE_LEVELS


                                       0-240
                                I
              10
                   20
  30




MONTHS
40
50
60
      BRESLOW TEST RESULTS: NOT SIGNIFICANT
                                  21

-------
                               REFERENCES
1.    Roholm, K.  The Fog Disaster  in the Meuse  Valley:   A  Fluorine
     Intoxication.  J. Ind. Hyg. Toxicol.  19(3):126-137, 1937.
2.    Ciacco, A. and D. J. Thompson.  A  Follow-up of Donora Ten  Years
     After:  Methodology and Findings.  Am.  J.  Pub. Hlth.  51(2):155-164,
     1961.
3.    Wilkins,  E. T.  Air Pollution and  the London Fog of December,  1952.
     J. R. San. Inst. 74(1):1-15,  1954.
4.    Waldbott, G.  Health Effects  of Environmental  Pollutants.   The
     C. V. Mosby Company, St.  Louis, Missouri,  1978.   pp.  6-8.
5.    Haenszel, W.  Cancer Mortality Among  the Foreign-Born in the United
     States.   J. Natl. Cancer  Inst. 26(1):37-132, 1961.
6.    Haenszel, W.  and M. Kurihara.  Studies of Japanese  Migrants.   I.
     Mortality from Cancer  and Other Diseases Among Japanese in the
     United  States.  J. Natl.  Cancer Inst.  40(l):43-68,  1968.
7.    Staszewski, J. and W.  Haenszel.  Cancer Among the Polish-Born in
     the  United States.  J. Natl.  Cancer  Inst.  35(2):291-297, 1965.
8.    Waterhouse, J., C. Muir,  P.  Corres,  and J. Powell.  Cancer Incidence
     in Five Continents, Volume  III.   IARC Scientific Publications No.
     15.   International Agency for Research on Cancer, Lyon, France,
     1976.
9.   Levin,  D.  L., S. S. Devesa,  J. D.  Godwin,  II, and D.  T. Silverman.
     Cancer  Rates  and Risks.   DHEW Pub.  No. (NIH) 75-691.   U.S. Govt.
     Printing Office, Washington,  D.C., 1974.
                                   22

-------
10.   Mason, T. J. and F. W. McKay.  U.S. Cancer Mortality by County:
     1950-1969.  DHEW Pub. No. (NIH) 74-615.  U.S. Govt. Printing  Office,
     Washington, D.C., 1973.
11.   Levin, M. L., W. Haenszel, B. E. Carroll, P. R. Gerhardt, V.  H.  Handy,
     and S. C. Ingraham, II.  Cancer Incidence in Urban and Rural  Areas
     of New York State.  J. Natl. Cancer Inst. 24(6):1243-1257,  1960.
12.   Henderson, B. E., R. J. Gordon, H. Mende, J. Soohoo, S. P.  Martin,
     and M. C. Pike.  Lung Cancer and Air Pollution  in Southcentral  Los
     Angeles County.  Am. J. Epidemiol. 10(16):477-488, 1975.
13.   Goldsmith, J. R. and L. Breslow.   Epidemiological Aspects of  Air
     Pollution.  J. Air Pollution Control Assoc. 9(3):129-132, 1959.
14.   Cox, D. R.  Regression Models and  Life Tables.  J. Roy. Statist.
     Soc. 34:187-220, 1972.
15.   Breslow,  N.  A Generalized Kruskal-Wailace Test for Comparing K
     Samples Subject to Unequal Patterns of Censorship.  Biometrika
     57:579-594, 1970.
                                   23

-------
                                   TECHNICAL REPORT DATA
                            {Please read Instructions on the reverse before completing)
  REPORT NO.
  EPA-600/1-80-009
                                                           3. RECIPIENT'S ACCESSION1 NO.
4. TITLE AND SUBTITLE
 Pilot  Study of Ambient Air Pollution And Survival
 From Cancer
                     5. REPORT DATE
                        January  1980
                     6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
  Gregg  S.  Wilkinson, Peter Reese,  Roger Priore
                     8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
  Health Effects Research Laboratory
  Environmental Protection Agency
  Research Triangle Park, NC  27711
     and
Roswell Park Memoria L
 Institute
666 Elm Street
Buffalo, NY 14263
10. PROGRAM ELEMENT NO.
    1HE775
11. CONTRACT/GRANT NO.

    DA-8-6122J
12. SPONSORING AGENCY NAME AND ADDRESS

      Environmental Protection Agency
      Research Triangle Park,  NC 27711
                     13. TYPE OF REPORT AND PERIOD COVERED
                     14. SPONSORING AGENCY CODE


                        EPA 600/11
15. SUPPLEMENTARY NOTES
16. ABSTRACT
   This study was concerned with  investigating the potential  influence exerted
   by ambient concentrations of particulate and sulfur dioxide  air pollutants
   upon the length of survival for diagnosed cancer patients.   Monitoring data
   from the National Aerometric Data Bank for particulates  and  sulfur dioxide
   were examined in conjunction with survival data from the Lakes Area Regional
   Tumor Service Registry.  Length of survival for respiratory  cancer patients
   was found to be inversely related to maximum particulate levels.  Median sur-
   vival for those patients who resided in areas where maximum  particulate levels
   exceeded 240 yg/m^ was significantly shorter than for  similar patients who
   resided in areas with lower particulate levels.  Colorectal  cancer patients
   demonstrated a similar trend that was not statistically  significant.  No as-
   sociation was found between survival of leukemia patients  and particulate or
   SC>2 levels, nor was SC>2 related to survival of respiratory tract or colorectal
   cancer patients.  These findings suggest that highly polluted air in residential
   areas may have a deleterious effect on the survival time of  patients with neo-
   plastic disease.  Additional research is called for of the relationship between
   cancer survival and exposure to ambient air pollution, especially particulates.
17.
                                KEY WORDS AND DOCUMENT ANALYSIS
a.
                  DESCRIPTORS
        b.lDENTIFIERS/OPEN ENDED TERMS  C. COSATI Field/Group
   Sulfur Dioxide
   Particulates
   Aerometric
   Cancer
                                    06.F.P
13. DISTRIBUTION STATEMENT

          RELEASE TO PUBLIC
        19. SECURITY CLASS (ThisReport)
          UNCLASSIFIED
              21. NO. OF PAGES
                     32
                                              20. SECURITY CLASS (Thispage)
                                                UNCLASSIFIED
                                                                        22. PRICE
EPA Form 2220-1 (9-73)
                                            24

-------