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Analysis of the Exposure-Response Relationship for Mesothelioma among Asbestos-Cement Factory Workers MURRAY M. FINKELSTEIN Ontario Ministry of Labour 400 University Avenue Toronto, Ontario Canada M7A IT7
INTRODUCTION In 1976, Newhouse and Berry suggested that the temporal pattern ofmesothelioma rates among asbestos factory workers might be modelled mathematically using a function that was a power of time since first exposure.’ In 1982. Peto, Seidman, and Selikoff showed that mesothelioma death rates among insulation workers, as well as among a number of other asbestos cohorts including Australian crocidolite miners and amosite factory workers, were proportional to the third or fourth power of time from first exposure.* Among the insulators, the rates were independent of age at first exposure. Subsequently, Doll and Pet0 formulated the “cubic residence-time model,” which predicts that mesothelioma incidence is increased, by each brief period of exposure, by an amount proportional to the intensity and duration of that exposure and to the cube of time since it o c c ~ r r e d The . ~ model appeared to fit quite well the incidence of 10 cases of mesothelioma among asbestos textile worker^.^ In 1989, de Klerk and colleagues tested the cubic residence-time model in a study of 31 mesothelioma deaths among Australian crocidolite miners, and found a good fit t o their data.5 The aim of the present investigation was to replicate the assessment of the cubic residence-time model using as study subjects 45 victims of mesothelioma among a cohort of Ontario asbestos-cement workers.
THE FACTORY A description of the factory and processes has been given elsewhere.h In brief, the factory opened in 1948 for the production of asbestos-cement pipe and rock wool insulation materials. Raw materials in the pipe process included silica and chrysotile and crocidolite asbestos. Production of asbestos-cement board, using only the chrysotile variety of asbestos, began in 1955. In 1960, the manufacture of amosite asbestos insulation materials was introduced. The use of asbestos in the factory was discontinued in 1980.
THE STUDY DESIGN AND ANALYSIS The Ontario Ministry of Labour is following a cohort of some 4,900 individuals who were employed at the factory. Vital status is determined periodically by 85
86
ANNALS NEW YORK ACADEMY OF SCIENCES
matching the study roll against the Canadian Mortality Data Base. Fifty cases of mesothelioma have been identified in the cohort from review of death certificates, review of Workers’ Compensation files, and examination of pathology and autopsy reports. The present analysis is limited to the 45 cases of mesothelioma, 31 pleural and 14 peritoneal, occurring among men who had not been employed as maintenance workers. The design of this study is a nested case-control analysis. The cases are the 45 men who developed mesothelioma. Each man was matched with 5 controls who were born in the same year as the case and who survived the case. FIGURE 1 shows the distribution of the ages at death of the men with mesothelioma. The distribution is notable for the youth of the mesothelioma victims. There was a wide distribution of intervals between first exposure and death, with the earliest death occurring 13 years after first exposure and the most recent 41 years after hire. The cubic residence-time model predicts that the incidence, I, of mesothelioma T years after first exposure will be
f ( T ) = c F(T4 - ( T
-
D)4)
where D is the duration of exposure, F is the intensity of exposure, and c is a constant which will depend upon the process. De Klerk and colleagues cleverly showedSthat this equation could be rewritten as: log f ( T ) = lOg(C)
+ log(F) + lOg(D) + 3 log(T) -
1.5(D/T).
The predictions of this model were tested using a conditional logistic regression a n a l y ~ i s . ~
LL
0
AGES AT DEATH
FIGURE 1. Distribution of ages at death for the men with mesothelioma.
FINKELSTEIN: EXPOSURE-RESPONSE IN MESOTHELIOMA
87
2I
RESULTS TABLE1 compares the predictions of the cubic residence-time model with the observations among the Australian crocidolite miners and the Ontario asbestos cement workers. There is excellent agreement with the predictions for the behavior of latency and duration of exposure. In each study, an average fiber level was computed by dividing an estimate of each subject’s cumulative exposure by the duration of exposure. In each study, the estimated relationship between exposure level and mesothelioma risk is less than linear. For the Ontario study, the result presented is a preliminary estimate, because the exposures of some of the study subjects must be investigated further. Several men who were employed outside of the asbestos production areas developed mesothelioma. These men were nominally assigned exposure levels of zero, and this will influence the estimates of risk according to level of exposure. Further analyses, using subgroups in which exposure level is more reliably defined, will be undertaken. FIGURE2 illustrates the exposure-response relationship, adjusted for latency, for the asbestos-cement workers. Two additional deductions from this cohort relate to the influence of age at first exposure and the effect of cigarette smoking on mesothelioma risk. Men were placed into one of two categories with respect to age at first exposure: less than 26 years of age and 26 years or more. There was no effect of age on mesothelioma risk. Histories of cigarette smoking were available for half of the men in the casecontrol analysis. Cigarette habit was coded as “ever smoker,” “never smoker,” or “unknown.” Within the limitations of the available data, there was no association between smoking habit and mesothelioma risk.
a
=
[0.25-0.831 0.2 [-0.2-0.61
0.4d
1 log(F )
+ 1.3 [OS-2.01 1.1 [0.4-1.81
1 log@)
+
From de Klerk et The coefficients predicted by the cubic residence-time model are underscored. The 95% confidence limits for the logistic-regression coefficients are presented in brackets. Preliminary estimate.
Australian crocidolite miners:
Model Predictions:b Observed Coeficients': Asbestos-cement factory:
log I
3.5 [0.7-6.21 2.8 [0.8-4.81
1 log( T )
-
-7.7 [-15-(-0.
l)]
[ -7.5-( -0.3)]
-3.9
1.5 ( D I T )
Comparison of the Predictions of the Cubic Residence-time Model for Mesothelioma with Observations of Mesothelioma Risk among Ontario Asbestos-Cement Workers and Australian Crocidolite Miners"
TABLE 1.
0 5a 7:
-e
c
in
FINKELSTEIN: EXPOSURE-RESPONSE IN MESOTHELIOMA
89
CONCLUSIONS The cubic residence-time model provides a good fit to the mesothelioma pattern of three industrial cohorts and should thus provide a reasonable basis for risk prediction. Under this model, mesothelioma risk is proportional to the level and duration of exposure. Estimates of exposure and duration levels in nonindustrial settings may thus be used in conjunction with estimates of historical exposure levels in industrial settings to provide “order of magnitude” assessments of mesothelioma risk in these nonindustrial settings. REFERENCES 1.
2. 3. 4.
5.
6.
7.
NEWHOUSE, M. L. & G. BERRY.1976. Predictions of mortality from mesothelial tumows in asbestos factory workers. Br. J. Ind. Med. 33: 147-151. & I . J. SELIKOFF.1982. Mesothelioma mortality in asbestos PETO,J., H. SEIDMAN workers: Implications for models of carcinogenesis and risk assessment. Br. J . Cancer 45: 124-135. DOLL,R. & J. PETO. 1985. Effects on Health of Exposure to Asbestos. A Report to the Health and Safety Commission. Her Majesty’s Stationery Office. London. W. BINNS,R. CLAYTON & T. GOFFE.1985. RelationPETO,J., R. DOLL,C. HERMON, ship of mortality to measures of environmental asbestos pollution in an asbestos textile factory. Ann. Occup. Hyg. 29: 305-355. DE KLERK,N . H., B. K. ARMSTRONG, A. W. MUSK, & M. S. HOBBS.1989. Cancer mortality in relation to measures of occupational exposure to crocidolite at Wittenoom Gorge in Western Australia. Br. J . Ind. Med. 4 6 529-536. FINKELSTEIN, M. M. 1982. Asbestosis in long-term employees of an Ontario asbestos cement factory. Am. Rev. Resp. Dis. 125: 496-501. EGRETSTATISTICAL SOFTWARE. 1989. Statistics and Epidemiology Research Corporation. Seattle. WA.
Analysis of the Exposure-Response Relationship for Mesothelioma among Asbestos-Cement Factory Workers MURRAY M. FINKELSTEIN Ontario Ministry of Labour 400 University Avenue Toronto, Ontario Canada M7A IT7
INTRODUCTION In 1976, Newhouse and Berry suggested that the temporal pattern ofmesothelioma rates among asbestos factory workers might be modelled mathematically using a function that was a power of time since first exposure.’ In 1982. Peto, Seidman, and Selikoff showed that mesothelioma death rates among insulation workers, as well as among a number of other asbestos cohorts including Australian crocidolite miners and amosite factory workers, were proportional to the third or fourth power of time from first exposure.* Among the insulators, the rates were independent of age at first exposure. Subsequently, Doll and Pet0 formulated the “cubic residence-time model,” which predicts that mesothelioma incidence is increased, by each brief period of exposure, by an amount proportional to the intensity and duration of that exposure and to the cube of time since it o c c ~ r r e d The . ~ model appeared to fit quite well the incidence of 10 cases of mesothelioma among asbestos textile worker^.^ In 1989, de Klerk and colleagues tested the cubic residence-time model in a study of 31 mesothelioma deaths among Australian crocidolite miners, and found a good fit t o their data.5 The aim of the present investigation was to replicate the assessment of the cubic residence-time model using as study subjects 45 victims of mesothelioma among a cohort of Ontario asbestos-cement workers.
THE FACTORY A description of the factory and processes has been given elsewhere.h In brief, the factory opened in 1948 for the production of asbestos-cement pipe and rock wool insulation materials. Raw materials in the pipe process included silica and chrysotile and crocidolite asbestos. Production of asbestos-cement board, using only the chrysotile variety of asbestos, began in 1955. In 1960, the manufacture of amosite asbestos insulation materials was introduced. The use of asbestos in the factory was discontinued in 1980.
THE STUDY DESIGN AND ANALYSIS The Ontario Ministry of Labour is following a cohort of some 4,900 individuals who were employed at the factory. Vital status is determined periodically by 85
86
ANNALS NEW YORK ACADEMY OF SCIENCES
matching the study roll against the Canadian Mortality Data Base. Fifty cases of mesothelioma have been identified in the cohort from review of death certificates, review of Workers’ Compensation files, and examination of pathology and autopsy reports. The present analysis is limited to the 45 cases of mesothelioma, 31 pleural and 14 peritoneal, occurring among men who had not been employed as maintenance workers. The design of this study is a nested case-control analysis. The cases are the 45 men who developed mesothelioma. Each man was matched with 5 controls who were born in the same year as the case and who survived the case. FIGURE 1 shows the distribution of the ages at death of the men with mesothelioma. The distribution is notable for the youth of the mesothelioma victims. There was a wide distribution of intervals between first exposure and death, with the earliest death occurring 13 years after first exposure and the most recent 41 years after hire. The cubic residence-time model predicts that the incidence, I, of mesothelioma T years after first exposure will be
f ( T ) = c F(T4 - ( T
-
D)4)
where D is the duration of exposure, F is the intensity of exposure, and c is a constant which will depend upon the process. De Klerk and colleagues cleverly showedSthat this equation could be rewritten as: log f ( T ) = lOg(C)
+ log(F) + lOg(D) + 3 log(T) -
1.5(D/T).
The predictions of this model were tested using a conditional logistic regression a n a l y ~ i s . ~
LL
0
AGES AT DEATH
FIGURE 1. Distribution of ages at death for the men with mesothelioma.
FINKELSTEIN: EXPOSURE-RESPONSE IN MESOTHELIOMA
87
2I
RESULTS TABLE1 compares the predictions of the cubic residence-time model with the observations among the Australian crocidolite miners and the Ontario asbestos cement workers. There is excellent agreement with the predictions for the behavior of latency and duration of exposure. In each study, an average fiber level was computed by dividing an estimate of each subject’s cumulative exposure by the duration of exposure. In each study, the estimated relationship between exposure level and mesothelioma risk is less than linear. For the Ontario study, the result presented is a preliminary estimate, because the exposures of some of the study subjects must be investigated further. Several men who were employed outside of the asbestos production areas developed mesothelioma. These men were nominally assigned exposure levels of zero, and this will influence the estimates of risk according to level of exposure. Further analyses, using subgroups in which exposure level is more reliably defined, will be undertaken. FIGURE2 illustrates the exposure-response relationship, adjusted for latency, for the asbestos-cement workers. Two additional deductions from this cohort relate to the influence of age at first exposure and the effect of cigarette smoking on mesothelioma risk. Men were placed into one of two categories with respect to age at first exposure: less than 26 years of age and 26 years or more. There was no effect of age on mesothelioma risk. Histories of cigarette smoking were available for half of the men in the casecontrol analysis. Cigarette habit was coded as “ever smoker,” “never smoker,” or “unknown.” Within the limitations of the available data, there was no association between smoking habit and mesothelioma risk.
a
=
[0.25-0.831 0.2 [-0.2-0.61
0.4d
1 log(F )
+ 1.3 [OS-2.01 1.1 [0.4-1.81
1 log@)
+
From de Klerk et The coefficients predicted by the cubic residence-time model are underscored. The 95% confidence limits for the logistic-regression coefficients are presented in brackets. Preliminary estimate.
Australian crocidolite miners:
Model Predictions:b Observed Coeficients': Asbestos-cement factory:
log I
3.5 [0.7-6.21 2.8 [0.8-4.81
1 log( T )
-
-7.7 [-15-(-0.
l)]
[ -7.5-( -0.3)]
-3.9
1.5 ( D I T )
Comparison of the Predictions of the Cubic Residence-time Model for Mesothelioma with Observations of Mesothelioma Risk among Ontario Asbestos-Cement Workers and Australian Crocidolite Miners"
TABLE 1.
0 5a 7:
-e
c
in
FINKELSTEIN: EXPOSURE-RESPONSE IN MESOTHELIOMA
89
CONCLUSIONS The cubic residence-time model provides a good fit to the mesothelioma pattern of three industrial cohorts and should thus provide a reasonable basis for risk prediction. Under this model, mesothelioma risk is proportional to the level and duration of exposure. Estimates of exposure and duration levels in nonindustrial settings may thus be used in conjunction with estimates of historical exposure levels in industrial settings to provide “order of magnitude” assessments of mesothelioma risk in these nonindustrial settings. REFERENCES 1.
2. 3. 4.
5.
6.
7.
NEWHOUSE, M. L. & G. BERRY.1976. Predictions of mortality from mesothelial tumows in asbestos factory workers. Br. J. Ind. Med. 33: 147-151. & I . J. SELIKOFF.1982. Mesothelioma mortality in asbestos PETO,J., H. SEIDMAN workers: Implications for models of carcinogenesis and risk assessment. Br. J . Cancer 45: 124-135. DOLL,R. & J. PETO. 1985. Effects on Health of Exposure to Asbestos. A Report to the Health and Safety Commission. Her Majesty’s Stationery Office. London. W. BINNS,R. CLAYTON & T. GOFFE.1985. RelationPETO,J., R. DOLL,C. HERMON, ship of mortality to measures of environmental asbestos pollution in an asbestos textile factory. Ann. Occup. Hyg. 29: 305-355. DE KLERK,N . H., B. K. ARMSTRONG, A. W. MUSK, & M. S. HOBBS.1989. Cancer mortality in relation to measures of occupational exposure to crocidolite at Wittenoom Gorge in Western Australia. Br. J . Ind. Med. 4 6 529-536. FINKELSTEIN, M. M. 1982. Asbestosis in long-term employees of an Ontario asbestos cement factory. Am. Rev. Resp. Dis. 125: 496-501. EGRETSTATISTICAL SOFTWARE. 1989. Statistics and Epidemiology Research Corporation. Seattle. WA.
