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Occupational Asbestos Exposure and Risk of Pleural Mesothelioma, Lung Cancer, and Laryngeal Cancer in the Prospective Netherlands Cohort Study Nadine S.M. Offermans, MSc, Dr. Roel Vermeulen, Prof. Alex Burdorf, Dr. R. Alexandra Goldbohm, Dr. Timo Kauppinen, Prof. Hans Kromhout, and Prof. Piet A. van den Brandt
Objective: To study the association between occupational asbestos exposure and pleural mesothelioma, lung cancer, and laryngeal cancer, specifically addressing risk associated with the lower end of the exposure distribution, risk of cancer subtypes, and the interaction between asbestos and smoking. Methods: Using the Netherlands Cohort Study (n = 58,279 men, aged 55 to 69 years), asbestos exposure was estimated by linkage to job-exposure matrices. After 17.3 years of follow-up, 132 pleural mesothelioma, 2324 lung cancer, and 166 laryngeal cancer cases were available. Results: The multivariable-adjusted model showed overall positive associations between all levels of asbestos exposure and mesothelioma, lung cancer, and laryngeal cancer. Lung adenocarcinoma and glottis cancer showed only a positive association after prolonged higher asbestos exposure (hazard ratio per 10 years increment, 1.43 [95% confidence interval, 1.06 to 1.93] and 1.95 [95% confidence interval, 1.36 to 2.80], respectively). There was no statistically significant interaction between asbestos and smoking. Conclusions: Asbestos levels encountered at the lower end of the exposure distribution may be associated with an increased risk of pleural mesothelioma, lung cancer, and laryngeal cancer.
I
n 2006, globally, an estimated 125 million people were still occupationally exposed to asbestos1 with its use even increasing in parts of Asia, South America, and the former Soviet Union.2 In the Netherlands, despite being banned in 1993, asbestos is still a public health concern with respect to asbestos removal and site cleaning in the general environment.3 Asbestos research has been ongoing for decades and evidence has been accumulated that, regardless of fiber type, asbestos causes mesothelioma and lung, laryngeal, and ovarian cancer.4,5 Nevertheless, there remain questions around asbestos carcinogenicity that pertain to risk at the lower end of the exposure distribution,5–7 the possibility of uncontrolled confounding due to smoking and drinking for especially laryngeal cancer,8 From the Department of Epidemiology (Ms Offermans and Mr van den Brandt), GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, the Netherlands; Institute for Risk Assessment Sciences (Dr Vermeulen and Mr Kromhout), Environmental Epidemiology Division, Utrecht University, Utrecht, the Netherlands; Julius Center for Health Sciences and Primary Care (Dr Vermeulen), University Medical Center, Utrecht, the Netherlands; Department of Public Health (Mr Burdorf), Erasmus MC, Rotterdam, the Netherlands; TNO (Dr Goldbohm), Leiden, the Netherlands; and Finnish Institute of Occupational Health (Dr Kauppinen), Helsinki, Finland. This study was supported by a grant (50-50-500-98-6153) from ZonMw. The sponsor had no role in the study design; collection, analysis, and interpretation of data; writing process; or decision where to submit the paper for publication. Authors Offermans, Vermeulen, Burdorf, Goldbohm, Kauppinen, Kromhout, and van den Brandt have no relationships/conditions/circumstances that present potential conflict of interest. The JOEM editorial board and planners have no financial interest related to this research. Address correspondence to: Piet A. van den Brandt, Department of Epidemiology, GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre, PO Box 616, 6200 MD Maastricht, the Netherlands ([email protected]). C 2013 by American College of Occupational and Environmental Copyright Medicine DOI: 10.1097/JOM.0000000000000060
6
Learning Objectives
r Become familiar with previous studies on occupational asr
r
bestos exposure and risk of pleural mesothelioma, lung, and laryngeal cancer, with special attention to data gaps. Summarize the new findings on asbestos-related risks of pleural mesothelioma, lung, and laryngeal cancer specifically addressing risk associated with the lower end of the exposure distribution, risk of cancer subtypes, and the interaction between asbestos and smoking. Discuss the study implications, including job-exposure matrix-based exposure assessment and implications for calculating population-attributable fractions.
the association with subtypes of lung9 and laryngeal cancer,8 and the interaction between asbestos and smoking in relation to lung10 and laryngeal cancer.8 Population-based studies are well suited to address these questions given their overall wide range in exposure levels, including those at the lower end of the exposure distribution (ie, exposure levels in jobs outside asbestos mining, insulation, cement and textile manufacturing, and other more highly exposed jobs), the possibility to control for potential confounders, and large size. The prospective Netherlands Cohort Study (NLCS) started in 1986 among 120,852 men and women of the general population.11,12 Besides questions on occupational history, the NLCS contains extensive information on dietary habits and lifestyle factors. Given the large study size and long follow-up, many cases of asbestos-related cancer have emerged in the NLCS. Therefore, the primary objectives of this study were to assess the following: 1. The overall association between occupational asbestos exposure and the risk of pleural mesothelioma, lung cancer, and laryngeal cancer, with special attention to risk associated with the lower end of the exposure distribution and to potential confounding 2. The association between occupational asbestos exposure and subtypes of lung and laryngeal cancer 3. The possible additive or multiplicative interaction between smoking and asbestos in relation to pleural mesothelioma, lung cancer, and laryngeal cancer Because the proportion of long-term employed women was rather low, this study was conducted only among men. We previously evaluated several methodologies for retrospective occupational exposure assessment within the NLCS. The jobexposure matrices (JEMs) DOMJEM and FINJEM showed rather similar agreement with case-by-case expert assessment and showed moderate agreement among each other.13 To provide insight into the methodological uncertainty associated with the choice of JEM, we present the main risk analyses using both DOMJEM and FINJEM. JOEM r Volume 56, Number 1, January 2014
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JOEM r Volume 56, Number 1, January 2014
MATERIAL AND METHODS Study Population and Cancer Follow-Up The study design and data collection strategies for the NLCS have been described in detail previously.11 In brief, the NLCS started in September 1986 when 58,279 men and 62,573 women aged 55 to 69 years, originating from 204 municipalities in the Netherlands with computerized population registries, were enrolled in the cohort. At baseline, participants completed a self-administered questionnaire on dietary habits and lifestyle, occupational history, and other potential risk factors for cancer.11 For reasons of efficiency in questionnaire processing and follow-up, the case–cohort approach was used.14 Incident cases were enumerated from the entire cohort, whereas the accumulated person-years at risk in the entire cohort were estimated from a random subcohort of 5000 subjects (2411 men and 2589 women), selected immediately after baseline. This subcohort is being followed up for vital status information, while the entire cohort is being monitored for incident cancer by annual record linkage to the Netherlands Cancer Registry and the Dutch Pathology Registry (PALGA).15,16 For these analyses, a total of 17.3 years of follow-up (baseline to December 2003) was available. Completeness of incident cancer coverage was estimated to be almost 100%.17 The NLCS was approved by the institutional review boards of the Netherlands Organisation for Applied Scientific Research TNO (Zeist) and Maastricht University (Maastricht). All prevalent cases at baseline other than skin cancer were excluded, leaving 2336 male subcohort members, 160 pleural mesothelioma cases (International Classification of Diseases for Oncology, Third Edition [ICD-O-3] code C384), 2932 lung cancer cases (ICDO-3 code C34), and 216 laryngeal cancer cases (ICD-O-3 codes C32.0 and C32.1, which refer to cancer of the glottis and supraglottis, respectively). The reason for considering only pleural mesothelioma and cancer of the glottis and supraglottis is the very low number of cases for peritoneal mesothelioma (n = 10) and cancer of the subglottis (n = 4). Subjects without any, or only uncodable, information on occupational history or who never worked professionally were omitted from the analyses. As a result, 2107 male subcohort members, 145 pleural mesothelioma cases, 2592 lung cancer cases, and 184 laryngeal cancer cases were available for analyses after 17.3 years of follow-up.
Occupational Exposure Assessment Information on lifetime occupational history until 1986 was obtained from the questionnaire completed at study enrolment. Questions concerned the job title, name and type of the company, products made in the department, and period of employment. On the basis of these questions, occupations were coded according to the Standard Occupational Classification of 1984 of the Dutch Central Bureau of Statistics, supplemented by a three-digit code assigned within the NLCS based on the job title. Subjects could enter a maximum of five occupations, which was generally sufficient to cover the lifetime occupational history for the large majority of the cohort, because cohort subjects held on average 1.9 job codes during their working life up to 1986. For all subjects, the job code was assessed for each of the maximally five occupations held between starting work and 1986.
Job-Exposure Matrices We applied two JEMs, the DOMJEM from the Netherlands and the Finnish FINJEM, as described previously.13 Briefly, DOMJEM is a generic JEM developed by occupational exposure experts in the Netherlands for application in general population studies. It contains a combined measure of the probability × intensity of exposure, which is semiquantitative (no, low, or high exposure) with a weighting of 0, 1, and 4, respectively.18 FINJEM was constructed
Occupational Asbestos Exposure and Respiratory Tract Tumors
for exposure assessment in large register-based studies, is based on both expert assessment and exposure measurements, and contains a time axis.19 Although FINJEM was constructed for Finland, exposure estimates were not adapted to Dutch occupational circumstances before applying it in the NLCS.
Asbestos Exposure Variables Several exposure variables were defined: ever versus never exposed to asbestos (yes/no), duration of exposure (years), cumulative exposure (CE; fiber-years/mL [f-y/mL] [FINJEM] or unit-years [DOMJEM], see explanation hereafter), and duration of high exposure (years). The CE is a combined measure of the probability (P), intensity (I), and duration (years) of exposure. Ever versus never exposed is based on the CE, in that subjects were classified as being ever exposed to asbestos when CE > 0. For occupations with P × I > 0, duration of employment was summed to obtain the duration of exposure. For DOMJEM, the CE measure was estimated by summing the product of P × I and duration over the reported occupations. The DOMJEM scores of no, low, and high exposure for P × I were arbitrarily assigned values of 0, 1, and 4, respectively, to mirror the log-normal (multiplicative) nature of occupational exposure levels, hence the expression in unit-years. The weighting was based on reported levels for semiquantitatively scored exposure, thereby ensuring a balanced weighting between intensity and duration in the calculation of CE.20 To arrive at the CE for FINJEM, first the P × I per job code was estimated using the time-specific exposure information in the time axis of this JEM, before summing P × I over the reported occupations. For those workers who started working before 1945, exposure was set to zero, because there was hardly any asbestos industry in the Netherlands in the period before 1945. For the duration of high exposure, first, the P × I per occupation was categorized into no, low, or high exposure on the basis of the distribution in the subcohort. Second, duration of employment was summed for those occupations with a high P × I to obtain the duration of high exposure. Participants were classified into never-exposed subjects and tertiles of those exposed to asbestos on the basis of the distribution among the subcohort for the duration of exposure and CE (reference group is the never exposed) and for the duration of high exposure (reference group is the never highly exposed). Continuous variables were also used. For the duration of (high) exposure, an increment of 10 years was used; while for the CE, an increment of 1 f-y/mL (FINJEM) or unit-year (DOMJEM) was used.
Statistical Analyses Age-adjusted (for lung cancer, also adjusted for family history of lung cancer [yes/no]) and multivariable-adjusted hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) were estimated by using Cox proportional hazards (PH) models. Because age is the natural time scale in studies of disease occurrence, attained age was used as date of entry in the analyses.21 In models with (attained) age as date of entry, baseline age should also be considered a covariate when there is a cohort effect or when the proportional hazards assumption is violated,22 which was the case in our analyses. Because most PH assumptions was no longer violated after adjustment for baseline age, we included baseline age as a covariate in our analyses. The total person-years at risk were estimated from the subcohort,23 and standard errors were estimated by using a robust covariance matrix estimator to account for increased variance due to sampling the subcohort from the entire cohort.24 The covariates included in the multivariate models were either a priori selected risk factors based on the literature or variables that changed the age-adjusted regression coefficients by at least 10% (using a backward stepwise procedure). For mesothelioma, only
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JOEM r Volume 56, Number 1, January 2014
Offermans et al
current smoking (yes/no), the number of cigarettes smoked per day, and years of smoking cigarettes were considered potential confounders. Although we can assume that mesothelioma is solely caused by asbestos, we added these covariates for confirmation purposes only. For lung cancer, the full covariate model consisted of current smoking (yes/no), the number of cigarettes smoked per day, years of smoking cigarettes, and occupational exposure to crystalline silica and polycyclic aromatic hydrocarbons. For laryngeal cancer, alcohol consumption was entered in the model in addition to current smoking (yes/no), the number of cigarettes smoked per day, and years of smoking cigarettes. Risk factors that were added to the model but did not satisfy the 10% rule and were not mentioned earlier were fruits and vegetables for all cancers and nickel, chromium, and welding fumes for lung cancer. All covariates were entered into the models as continuous variables, except for current smoking (yes/no). The number of cigarettes smoked per day and years of smoking cigarettes were added to the model as both centered and noncentered variables because of possible problems with collinearity. As results of both analyses were comparable (not shown), we only presented the noncentered variables. To enable comparison, the age-adjusted (for mesothelioma and laryngeal cancer) and family history of lung cancer–adjusted (for lung cancer) analyses were restricted to subjects included in the multivariable-adjusted analyses (ie, with no missing values on confounding variables), which left 1962 subcohort members and 132 cases for pleural mesothelioma, 1962 subcohort members and 2324 cases for lung cancer, and 1931 subcohort members and 166 cases for laryngeal cancer for analyses. For each analysis, the proportional hazards assumption was tested by using the scaled Schoenfeld residuals.25 Trends for all subjects and only including the exposed were evaluated with the Wald test by assigning subjects the median value for each level of the categorical variable among the subcohort members, and this variable was entered as a continuous term in the Cox regression model. In addition, we evaluated the association with subtypes of lung cancer (n = 379 for small cell lung cancer, 350 for large cell, 931 for squamous cell carcinoma, and 493 for adenocarcinoma) and laryngeal cancer (n = 122 for glottis and 44 for supraglottis). Furthermore, we studied the interaction between asbestos exposure (yes/no) and smoking (no/former/current) for all three cancers both on a multiplicative and an additive scale. First, we examined whether the joint effect of asbestos and smoking was closer to additivity or multiplicativity for each cancer endpoint. Second, we tested for statistically significant departure from multiplicativity by including an interaction term in the Cox regression model. Third, we tested for statistically significant departure from additivity using the CI of the relative excess risk of cancer due to interaction, according to methods described by Knol and VanderWeele,26 which were adapted for use in Stata (Stata Corporation, College Station, TX). All analyses were performed using the Stata statistical software package (intercooled Stata, version 10). All tests were two-tailed, and differences were regarded as statistically significant at P < 0.05. Finally, population-attributable fractions (PAFs) were calculated for all three cancers on the basis of the HRs for all asbestos exposure variables in the multivariable-adjusted models, using the formula: pi (RRi − 1)/[pi (RRi − 1) + 1], where p is the fraction of exposed subjects in the subcohort, i indexes the exposure level, and RR values are based on HRs.27
RESULTS The distribution of asbestos exposure and potential confounders among male subcohort members and cancer cases in the NLCS is given in Table 1. Lung cancer cases more often reported a family history of lung cancer. In addition, they more often smoked cigarettes, and smoked more cigarettes per day and for more years 8
than subcohort members, as did the laryngeal cancer cases. Cases for all three cancers consumed more alcohol per day and were, on average, more often and longer (highly) exposed to asbestos. Although FINJEM generally revealed a somewhat lower percentage of ever-exposed subjects, DOMJEM showed the lowest percentage of highly exposed subjects. When studying the association between asbestos exposure and covariates in the subcohort (Table 2), subjects exposed to asbestos more often smoked cigarettes and for more years, with the JEMs showing different patterns over the tertiles. Alcohol consumption was higher for those never exposed to asbestos than for those exposed, as classified according to both JEMs. There was an association between exposure to silica and polycyclic aromatic hydrocarbons and asbestos exposure, with DOMJEM showing an increasing pattern over the tertiles of exposure, while the pattern for FINJEM was less clear. Overall, all asbestos exposure variables were positively associated with risk of mesothelioma, lung cancer, and laryngeal cancer, using both DOMJEM and FINJEM, and for the age-adjusted (mesothelioma and laryngeal cancer) and for family history of lung cancer–adjusted (yes/no) (lung cancer) models as well as the multivariable-adjusted models (Tables 3 to 5). Adjusting for potential confounders had no influence on the association with mesothelioma, and little to no effect on the association with lung and laryngeal cancer. Therefore, only multivariable-adjusted results are mentioned in the text hereafter. Overall, DOMJEM revealed a higher HR (95% CI) for the duration of high exposure (tertile 3 vs never: HR = 13.66 [95% CI, 5.86 to 31.84] for mesothelioma; HR = 2.99 [95% CI, 1.39 to 6.41] for lung cancer; and HR = 6.36 [95% CI, 2.18 to 18.53] for laryngeal cancer) than FINJEM (HR = 3.28 [95% CI, 1.82 to 5.92] for mesothelioma; HR = 1.74 [95% CI, 1.20 to 2.54] for lung cancer; and HR = 1.49 [95% CI, 0.75 to 2.97] for laryngeal cancer). FINJEM showed a higher HR (95% CI) for ever versus never exposed (HR = 3.02 [95% CI, 2.11 to 4.34] for mesothelioma; HR = 1.50 [95% CI, 1.27 to 1.78] for lung cancer; and HR = 1.42 [95% CI, 0.99 to 2.03] for laryngeal cancer) than DOMJEM (HR = 2.62 [95% CI, 1.82 to 3.76] for mesothelioma; HR = 1.19 [95% CI, 1.02 to 1.40] for lung cancer; and HR = 1.20 [95% CI, 0.84 to 1.72] for laryngeal cancer). For mesothelioma (Table 3), associations generally reached statistical significance and showed a clear dose–response relation when including the never-exposed subjects (Ptrend < 0.001). When only including the exposed subjects, only DOMJEM showed a significant trend (Ptrend < 0.001). For lung cancer (Table 4), not all associations were statistically significant, though tests for trend were significant when including the never-exposed subjects (Ptrend < 0.05). When only the exposed subjects were considered, trends were no longer significant. Results by histology of lung cancer were fairly comparable to overall lung cancer apart from adenocarcinoma, for which associations with most exposure variables were weaker or absent. The only exception was the duration of high exposure for DOMJEM, which showed a statistically significant association for the continuous variable (HR = 1.43 [95% CI, 1.06 to 1.93]) and positive trend (Ptrend = 0.047) for risk of adenocarcinoma. For laryngeal cancer (Table 5), risk by location showed usually stronger associations for supraglottis than glottis cancer, except for the duration of high exposure for DOMJEM, which was statistically significant for both the highest tertile (HR = 7.09 [95% CI, 2.31 to 21.74]) and the continuous variable, as was the dose–response relation (Ptrend = 0.002). The joint effect of asbestos and smoking for each cancer endpoint was assessed by comparing the HRs of current smokers not exposed to asbestos and never-smokers exposed to asbestos with the HR of current smokers exposed to asbestos (Table 6). Given space
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JOEM r Volume 56, Number 1, January 2014
Occupational Asbestos Exposure and Respiratory Tract Tumors
TABLE 1. Distribution of Potential Confounders and Asbestos Exposure* Among Male Subcohort Members and Cancer Cases in the NLCS, 1986–2003 Subcohort (n = 2,107)
Age at baseline, yrs Family history of lung cancer Cigarette smoking Never Former Current Number of cigarettes per day†‡ Years of smoking†‡ Alcohol consumption, ‡ g/d DOMJEM Never exposed§ Ever exposed§ Duration of exposure, || yrs T1 (median: 4) T2 (median: 18) T3 (median: 37) Cumulative probability × intensity of exposure, unit-years T1 (median: 4) T2 (median: 20) T3 (median: 38) Ever highly exposed|| Duration of high exposure,|| yrs T1 (median: 4) T2 (median: 11) T3 (median: 31) FINJEM Never exposed§ Ever exposed§ Duration of exposure, || yrs T1 (median: 7) T2 (median: 25) T3 (median: 37) Cumulative probability × intensity of exposure, f-y/mL T1 (median: 0.20) T2 (median: 1.58) T3 (median: 6.57) Ever highly exposed|| Duration of high exposure,|| yrs T1 (median: 6) T2 (median: 20) T3 (median: 35)
Pleural Mesothelioma Cases (n = 145)
Lung Cancer Cases (n = 2,592)
Laryngeal Cancer Cases (n = 184)
n
Mean/%
SD
n
Mean/%
SD
n
Mean/%
SD
n
Mean/%
SD
2,107 204
61.3 9.7
4.2
145 NA
61.1 NA
4.1
2,592 321
62.0 12.4
4.1
184 NA
61.8 NA
3.9
264 1,080 763 1,722 1,807 2,066
12.5 51.3 36.2 17.1 33.6 15.0
18 75 52 115 125 140
12.4 51.7 35.9 17.2 33.3 16.2
100 827 1,663 2,243 2,454 2,534
3.9 31.9 64.2 19.8 40.7 18.4
4 63 117 166 180 180
2.2 34.2 63.6 18.3 39.6 22.3
1,498 609
71.1 28.9
69 76
47.6 52.4
1,760 832
67.9 32.1
127 57
69.0 31.0
214 200 195
35.2 32.8 32.0
10 30 36
13.1 39.5 47.4
232 293 307
27.9 35.2 36.9
17 16 24
29.8 28.1 42.1
217 192 200 49
35.7 31.5 32.8 2.3
7 21 48 28
9.2 27.6 63.2 19.3
234 269 329 110
28.1 32.3 39.6 4.2
15 18 24 9
26.3 31.6 42.1 4.9
17 16 16
34.6 32.7 32.7
6 7 15
21.4 25.0 53.6
33 27 50
30.0 24.6 45.4
1 2 6
11.1 22.2 66.7
1,561 546
74.1 25.9
73 72
50.3 49.7
1,732 860
66.8 33.2
130 54
70.7 29.3
186 178 182
34.1 32.6 33.3
20 21 31
27.8 29.2 43.0
261 323 276
30.3 37.6 32.1
20 18 16
37.1 33.3 29.6
182 182 182 292
33.4 33.3 33.3 13.9
21 25 26 42
29.2 34.7 36.1 29.0
245 280 335 521
28.5 32.6 38.9 20.1
17 19 18 29
31.5 35.2 33.3 15.8
102 95 95
35.0 32.5 32.5
12 12 18
28.6 28.6 42.8
146 186 189
28.0 35.7 36.3
8 9 12
27.6 31.0 41.4
10.6 11.9 16.9
11.0 12.1 16.4
10.6 9.2 19.4
9.7 10.2 25.8
*Exposure dichotomized or categorized in never-exposed subjects and tertiles (T) of exposed subjects in the subcohort. †Among former and current smokers only. ‡Sum of categories deviates from total number because of missing values. §Exposure based on the cumulative probability × intensity of exposure (unit-years or f-y/mL). ||Exposure based on the probability × intensity of exposure (unit years or f-y/mL) per job. f-y/mL, fiber-years/mL; NA, not applicable; NLCS, Netherlands Cohort Study.
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JOEM r Volume 56, Number 1, January 2014
Offermans et al
TABLE 2. Association Between Category of Asbestos Exposure and Potential Confounders in the Subcohort in the NLCS, 1986–2003 Asbestos Exposure Based on the Cumulative Probability × Intensity Characteristic DOMJEM Age at baseline, mean, yrs Family history of lung cancer, % Cigarette smoking, % Never Former Current Number of cigarettes per day,* mean Years of smoking,* mean Alcohol consumption, mean, g/d Silica,† % Never exposed T1 (median: 7) T2 (median: 27) T3 (median: 47.5) PAHs,† % Never exposed T1 (median: 4) T2 (median: 18.5) T3 (median: 36) FINJEM Age at baseline, mean, yrs Family history of lung cancer, % Cigarette smoking, % Never Former Current Number of cigarettes per day,* mean Years of smoking,* mean Alcohol consumption, mean, g/d Silica,† % Never exposed T1 (median: 0.33) T2 (median: 1.45) T3 (median: 4.80) PAHs,† % Never exposed T1 (median: 0.08) T2 (median: 0.27) T3 (median: 0.77)
Never Exposed
T1
T2
T3
61.4 9.9
Median: 4 unit-years 61.1 9.7
Median: 20 unit-years 61.3 10.4
Median: 38 unit-years 60.9 7.5
14.0 50.9 35.1 17.1 33.5 15.5
8.8 55.8 35.4 17.4 32.6 14.1
9.9 48.4 41.7 16.6 34.8 12.9
8.0 51.5 40.5 16.7 34.5 15.0
88.4 3.2 4.2 4.2
78.4 16.1 4.6 0.9
82.3 3.1 9.4 5.2
86.5 3.5 4.5 5.5
96.2 0.8 1.5 1.5
81.6 14.7 2.8 0.9
82.8 3.7 10.9 2.6
79.5 4.5 3.5 12.5
61.4 10.1
Median: 0.20 f-y/mL 61.1 8.2
Median: 1.58 f-y/mL 60.4 13.2
Median: 6.57 f-y/mL 61.0 4.4
13.4 51.4 35.2 17.0 33.4 15.7
12.1 53.3 34.6 16.0 32.8 12.0
6.6 55.5 37.9 18.5 34.2 14.9
11.0 44.0 45.0 16.6 36.0 12.9
98.8 0.1 0.4 0.7
81.3 14.8 1.7 2.2
68.7 17.6 9.3 4.4
41.2 6.6 25.3 26.9
97.8 0.5 0.8 0.9
80.2 6.6 3.3 9.9
58.8 13.2 18.1 9.9
68.2 14.8 7.7 9.3
*Among former and current smokers only. †Exposure based on the cumulative probability × intensity of exposure (unit-years or f-y/mL), categorized in never-exposed subjects and tertiles of exposed subjects in the subcohort. f-y/mL, fiber-years/mL; NLCS, Netherlands Cohort Study; PAHs, polycyclic aromatic hydrocarbons.
limitations and because HRs for ever versus never exposed were overall higher for FINJEM than for DOMJEM, we will only present results for FINJEM. For mesothelioma, the observed HR of 4.18 for the combined exposure category is lower than the product of HRs for asbestos and smoking (5.39 × 1.35 = 7.28), indicating that the joint effect is less than multiplicative. The observed HR is also lower than expected
10
when using an additive model (5.39 + 1.35 − 1 = 5.74). For lung cancer, the observed HR of 10.21 is lower than the product of asbestos and smoking (7.48 × 1.79 = 13.39), indicating that the joint effect is less than multiplicative. The observed HR is higher than what would have been expected by using an additive model (7.48 + 1.79 − 1 = 8.27). For laryngeal cancer, the observed HR of 20.73 is lower than the product (16.95 × 2.27 = 38.48), indicating that the joint effect is
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JOEM r Volume 56, Number 1, January 2014
Occupational Asbestos Exposure and Respiratory Tract Tumors
TABLE 3. Hazard Ratios, 95% CIs, and PAFs for Pleural Mesothelioma for Categories of Asbestos Exposure,* Estimated With DOMJEM and FINJEM in the NLCS, 1986–2003† Pleural Mesothelioma
DOMJEM Never exposed|| Ever exposed|| Duration of exposure,¶ yrs T1 (median: 4) T2 (median: 18) T3 (median: 37) Ptrend (over the exposed only) Continuous, per 10 yrs Cumulative probability × intensity of exposure, unit-years T1 (median: 4) T2 (median: 20) T3 (median: 38) Ptrend (over the exposed only) Continuous, per 1 unit-year Duration of high exposure,¶ yrs Never highly exposed T1 (median: 4) T2 (median: 11) T3 (median: 31) Ptrend (over the exposed only) Continuous, per 10 yrs FINJEM Never exposed|| Ever exposed|| Duration of exposure,¶ yrs T1 (median: 7) T2 (median: 25) T3 (median: 37) Ptrend (over the exposed only) Continuous, per 10 yrs Cumulative probability × intensity of exposure, f-y/mL T1 (median: 0.20) T2 (median: 1.58) T3 (median: 6.57) Ptrend (over the exposed only) Continuous, per 1 fiber-year Duration of high exposure,¶ yrs Never highly exposed T1 (median: 6) T2 (median: 20) T3 (median: 35) Ptrend (over the exposed only) Continuous, per 10 yrs
Person Years in Subcohort
n
HR‡ (95% CI)
HR§ (95% CI)
PAF, %
107,557 41,688
66 66
1 (ref) 2.61 (1.83–3.73)
1 (ref) 2.62 (1.82–3.76)
31.9
15,469 12,615 13,604
10 26 30
149,245
132
1.02 (0.52–2.02) 3.55 (2.19–5.78) 3.67 (2.32–5.80)
Occupational Asbestos Exposure and Risk of Pleural Mesothelioma, Lung Cancer, and Laryngeal Cancer in the Prospective Netherlands Cohort Study Nadine S.M. Offermans, MSc, Dr. Roel Vermeulen, Prof. Alex Burdorf, Dr. R. Alexandra Goldbohm, Dr. Timo Kauppinen, Prof. Hans Kromhout, and Prof. Piet A. van den Brandt
Objective: To study the association between occupational asbestos exposure and pleural mesothelioma, lung cancer, and laryngeal cancer, specifically addressing risk associated with the lower end of the exposure distribution, risk of cancer subtypes, and the interaction between asbestos and smoking. Methods: Using the Netherlands Cohort Study (n = 58,279 men, aged 55 to 69 years), asbestos exposure was estimated by linkage to job-exposure matrices. After 17.3 years of follow-up, 132 pleural mesothelioma, 2324 lung cancer, and 166 laryngeal cancer cases were available. Results: The multivariable-adjusted model showed overall positive associations between all levels of asbestos exposure and mesothelioma, lung cancer, and laryngeal cancer. Lung adenocarcinoma and glottis cancer showed only a positive association after prolonged higher asbestos exposure (hazard ratio per 10 years increment, 1.43 [95% confidence interval, 1.06 to 1.93] and 1.95 [95% confidence interval, 1.36 to 2.80], respectively). There was no statistically significant interaction between asbestos and smoking. Conclusions: Asbestos levels encountered at the lower end of the exposure distribution may be associated with an increased risk of pleural mesothelioma, lung cancer, and laryngeal cancer.
I
n 2006, globally, an estimated 125 million people were still occupationally exposed to asbestos1 with its use even increasing in parts of Asia, South America, and the former Soviet Union.2 In the Netherlands, despite being banned in 1993, asbestos is still a public health concern with respect to asbestos removal and site cleaning in the general environment.3 Asbestos research has been ongoing for decades and evidence has been accumulated that, regardless of fiber type, asbestos causes mesothelioma and lung, laryngeal, and ovarian cancer.4,5 Nevertheless, there remain questions around asbestos carcinogenicity that pertain to risk at the lower end of the exposure distribution,5–7 the possibility of uncontrolled confounding due to smoking and drinking for especially laryngeal cancer,8 From the Department of Epidemiology (Ms Offermans and Mr van den Brandt), GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, the Netherlands; Institute for Risk Assessment Sciences (Dr Vermeulen and Mr Kromhout), Environmental Epidemiology Division, Utrecht University, Utrecht, the Netherlands; Julius Center for Health Sciences and Primary Care (Dr Vermeulen), University Medical Center, Utrecht, the Netherlands; Department of Public Health (Mr Burdorf), Erasmus MC, Rotterdam, the Netherlands; TNO (Dr Goldbohm), Leiden, the Netherlands; and Finnish Institute of Occupational Health (Dr Kauppinen), Helsinki, Finland. This study was supported by a grant (50-50-500-98-6153) from ZonMw. The sponsor had no role in the study design; collection, analysis, and interpretation of data; writing process; or decision where to submit the paper for publication. Authors Offermans, Vermeulen, Burdorf, Goldbohm, Kauppinen, Kromhout, and van den Brandt have no relationships/conditions/circumstances that present potential conflict of interest. The JOEM editorial board and planners have no financial interest related to this research. Address correspondence to: Piet A. van den Brandt, Department of Epidemiology, GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre, PO Box 616, 6200 MD Maastricht, the Netherlands ([email protected]). C 2013 by American College of Occupational and Environmental Copyright Medicine DOI: 10.1097/JOM.0000000000000060
6
Learning Objectives
r Become familiar with previous studies on occupational asr
r
bestos exposure and risk of pleural mesothelioma, lung, and laryngeal cancer, with special attention to data gaps. Summarize the new findings on asbestos-related risks of pleural mesothelioma, lung, and laryngeal cancer specifically addressing risk associated with the lower end of the exposure distribution, risk of cancer subtypes, and the interaction between asbestos and smoking. Discuss the study implications, including job-exposure matrix-based exposure assessment and implications for calculating population-attributable fractions.
the association with subtypes of lung9 and laryngeal cancer,8 and the interaction between asbestos and smoking in relation to lung10 and laryngeal cancer.8 Population-based studies are well suited to address these questions given their overall wide range in exposure levels, including those at the lower end of the exposure distribution (ie, exposure levels in jobs outside asbestos mining, insulation, cement and textile manufacturing, and other more highly exposed jobs), the possibility to control for potential confounders, and large size. The prospective Netherlands Cohort Study (NLCS) started in 1986 among 120,852 men and women of the general population.11,12 Besides questions on occupational history, the NLCS contains extensive information on dietary habits and lifestyle factors. Given the large study size and long follow-up, many cases of asbestos-related cancer have emerged in the NLCS. Therefore, the primary objectives of this study were to assess the following: 1. The overall association between occupational asbestos exposure and the risk of pleural mesothelioma, lung cancer, and laryngeal cancer, with special attention to risk associated with the lower end of the exposure distribution and to potential confounding 2. The association between occupational asbestos exposure and subtypes of lung and laryngeal cancer 3. The possible additive or multiplicative interaction between smoking and asbestos in relation to pleural mesothelioma, lung cancer, and laryngeal cancer Because the proportion of long-term employed women was rather low, this study was conducted only among men. We previously evaluated several methodologies for retrospective occupational exposure assessment within the NLCS. The jobexposure matrices (JEMs) DOMJEM and FINJEM showed rather similar agreement with case-by-case expert assessment and showed moderate agreement among each other.13 To provide insight into the methodological uncertainty associated with the choice of JEM, we present the main risk analyses using both DOMJEM and FINJEM. JOEM r Volume 56, Number 1, January 2014
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JOEM r Volume 56, Number 1, January 2014
MATERIAL AND METHODS Study Population and Cancer Follow-Up The study design and data collection strategies for the NLCS have been described in detail previously.11 In brief, the NLCS started in September 1986 when 58,279 men and 62,573 women aged 55 to 69 years, originating from 204 municipalities in the Netherlands with computerized population registries, were enrolled in the cohort. At baseline, participants completed a self-administered questionnaire on dietary habits and lifestyle, occupational history, and other potential risk factors for cancer.11 For reasons of efficiency in questionnaire processing and follow-up, the case–cohort approach was used.14 Incident cases were enumerated from the entire cohort, whereas the accumulated person-years at risk in the entire cohort were estimated from a random subcohort of 5000 subjects (2411 men and 2589 women), selected immediately after baseline. This subcohort is being followed up for vital status information, while the entire cohort is being monitored for incident cancer by annual record linkage to the Netherlands Cancer Registry and the Dutch Pathology Registry (PALGA).15,16 For these analyses, a total of 17.3 years of follow-up (baseline to December 2003) was available. Completeness of incident cancer coverage was estimated to be almost 100%.17 The NLCS was approved by the institutional review boards of the Netherlands Organisation for Applied Scientific Research TNO (Zeist) and Maastricht University (Maastricht). All prevalent cases at baseline other than skin cancer were excluded, leaving 2336 male subcohort members, 160 pleural mesothelioma cases (International Classification of Diseases for Oncology, Third Edition [ICD-O-3] code C384), 2932 lung cancer cases (ICDO-3 code C34), and 216 laryngeal cancer cases (ICD-O-3 codes C32.0 and C32.1, which refer to cancer of the glottis and supraglottis, respectively). The reason for considering only pleural mesothelioma and cancer of the glottis and supraglottis is the very low number of cases for peritoneal mesothelioma (n = 10) and cancer of the subglottis (n = 4). Subjects without any, or only uncodable, information on occupational history or who never worked professionally were omitted from the analyses. As a result, 2107 male subcohort members, 145 pleural mesothelioma cases, 2592 lung cancer cases, and 184 laryngeal cancer cases were available for analyses after 17.3 years of follow-up.
Occupational Exposure Assessment Information on lifetime occupational history until 1986 was obtained from the questionnaire completed at study enrolment. Questions concerned the job title, name and type of the company, products made in the department, and period of employment. On the basis of these questions, occupations were coded according to the Standard Occupational Classification of 1984 of the Dutch Central Bureau of Statistics, supplemented by a three-digit code assigned within the NLCS based on the job title. Subjects could enter a maximum of five occupations, which was generally sufficient to cover the lifetime occupational history for the large majority of the cohort, because cohort subjects held on average 1.9 job codes during their working life up to 1986. For all subjects, the job code was assessed for each of the maximally five occupations held between starting work and 1986.
Job-Exposure Matrices We applied two JEMs, the DOMJEM from the Netherlands and the Finnish FINJEM, as described previously.13 Briefly, DOMJEM is a generic JEM developed by occupational exposure experts in the Netherlands for application in general population studies. It contains a combined measure of the probability × intensity of exposure, which is semiquantitative (no, low, or high exposure) with a weighting of 0, 1, and 4, respectively.18 FINJEM was constructed
Occupational Asbestos Exposure and Respiratory Tract Tumors
for exposure assessment in large register-based studies, is based on both expert assessment and exposure measurements, and contains a time axis.19 Although FINJEM was constructed for Finland, exposure estimates were not adapted to Dutch occupational circumstances before applying it in the NLCS.
Asbestos Exposure Variables Several exposure variables were defined: ever versus never exposed to asbestos (yes/no), duration of exposure (years), cumulative exposure (CE; fiber-years/mL [f-y/mL] [FINJEM] or unit-years [DOMJEM], see explanation hereafter), and duration of high exposure (years). The CE is a combined measure of the probability (P), intensity (I), and duration (years) of exposure. Ever versus never exposed is based on the CE, in that subjects were classified as being ever exposed to asbestos when CE > 0. For occupations with P × I > 0, duration of employment was summed to obtain the duration of exposure. For DOMJEM, the CE measure was estimated by summing the product of P × I and duration over the reported occupations. The DOMJEM scores of no, low, and high exposure for P × I were arbitrarily assigned values of 0, 1, and 4, respectively, to mirror the log-normal (multiplicative) nature of occupational exposure levels, hence the expression in unit-years. The weighting was based on reported levels for semiquantitatively scored exposure, thereby ensuring a balanced weighting between intensity and duration in the calculation of CE.20 To arrive at the CE for FINJEM, first the P × I per job code was estimated using the time-specific exposure information in the time axis of this JEM, before summing P × I over the reported occupations. For those workers who started working before 1945, exposure was set to zero, because there was hardly any asbestos industry in the Netherlands in the period before 1945. For the duration of high exposure, first, the P × I per occupation was categorized into no, low, or high exposure on the basis of the distribution in the subcohort. Second, duration of employment was summed for those occupations with a high P × I to obtain the duration of high exposure. Participants were classified into never-exposed subjects and tertiles of those exposed to asbestos on the basis of the distribution among the subcohort for the duration of exposure and CE (reference group is the never exposed) and for the duration of high exposure (reference group is the never highly exposed). Continuous variables were also used. For the duration of (high) exposure, an increment of 10 years was used; while for the CE, an increment of 1 f-y/mL (FINJEM) or unit-year (DOMJEM) was used.
Statistical Analyses Age-adjusted (for lung cancer, also adjusted for family history of lung cancer [yes/no]) and multivariable-adjusted hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) were estimated by using Cox proportional hazards (PH) models. Because age is the natural time scale in studies of disease occurrence, attained age was used as date of entry in the analyses.21 In models with (attained) age as date of entry, baseline age should also be considered a covariate when there is a cohort effect or when the proportional hazards assumption is violated,22 which was the case in our analyses. Because most PH assumptions was no longer violated after adjustment for baseline age, we included baseline age as a covariate in our analyses. The total person-years at risk were estimated from the subcohort,23 and standard errors were estimated by using a robust covariance matrix estimator to account for increased variance due to sampling the subcohort from the entire cohort.24 The covariates included in the multivariate models were either a priori selected risk factors based on the literature or variables that changed the age-adjusted regression coefficients by at least 10% (using a backward stepwise procedure). For mesothelioma, only
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JOEM r Volume 56, Number 1, January 2014
Offermans et al
current smoking (yes/no), the number of cigarettes smoked per day, and years of smoking cigarettes were considered potential confounders. Although we can assume that mesothelioma is solely caused by asbestos, we added these covariates for confirmation purposes only. For lung cancer, the full covariate model consisted of current smoking (yes/no), the number of cigarettes smoked per day, years of smoking cigarettes, and occupational exposure to crystalline silica and polycyclic aromatic hydrocarbons. For laryngeal cancer, alcohol consumption was entered in the model in addition to current smoking (yes/no), the number of cigarettes smoked per day, and years of smoking cigarettes. Risk factors that were added to the model but did not satisfy the 10% rule and were not mentioned earlier were fruits and vegetables for all cancers and nickel, chromium, and welding fumes for lung cancer. All covariates were entered into the models as continuous variables, except for current smoking (yes/no). The number of cigarettes smoked per day and years of smoking cigarettes were added to the model as both centered and noncentered variables because of possible problems with collinearity. As results of both analyses were comparable (not shown), we only presented the noncentered variables. To enable comparison, the age-adjusted (for mesothelioma and laryngeal cancer) and family history of lung cancer–adjusted (for lung cancer) analyses were restricted to subjects included in the multivariable-adjusted analyses (ie, with no missing values on confounding variables), which left 1962 subcohort members and 132 cases for pleural mesothelioma, 1962 subcohort members and 2324 cases for lung cancer, and 1931 subcohort members and 166 cases for laryngeal cancer for analyses. For each analysis, the proportional hazards assumption was tested by using the scaled Schoenfeld residuals.25 Trends for all subjects and only including the exposed were evaluated with the Wald test by assigning subjects the median value for each level of the categorical variable among the subcohort members, and this variable was entered as a continuous term in the Cox regression model. In addition, we evaluated the association with subtypes of lung cancer (n = 379 for small cell lung cancer, 350 for large cell, 931 for squamous cell carcinoma, and 493 for adenocarcinoma) and laryngeal cancer (n = 122 for glottis and 44 for supraglottis). Furthermore, we studied the interaction between asbestos exposure (yes/no) and smoking (no/former/current) for all three cancers both on a multiplicative and an additive scale. First, we examined whether the joint effect of asbestos and smoking was closer to additivity or multiplicativity for each cancer endpoint. Second, we tested for statistically significant departure from multiplicativity by including an interaction term in the Cox regression model. Third, we tested for statistically significant departure from additivity using the CI of the relative excess risk of cancer due to interaction, according to methods described by Knol and VanderWeele,26 which were adapted for use in Stata (Stata Corporation, College Station, TX). All analyses were performed using the Stata statistical software package (intercooled Stata, version 10). All tests were two-tailed, and differences were regarded as statistically significant at P < 0.05. Finally, population-attributable fractions (PAFs) were calculated for all three cancers on the basis of the HRs for all asbestos exposure variables in the multivariable-adjusted models, using the formula: pi (RRi − 1)/[pi (RRi − 1) + 1], where p is the fraction of exposed subjects in the subcohort, i indexes the exposure level, and RR values are based on HRs.27
RESULTS The distribution of asbestos exposure and potential confounders among male subcohort members and cancer cases in the NLCS is given in Table 1. Lung cancer cases more often reported a family history of lung cancer. In addition, they more often smoked cigarettes, and smoked more cigarettes per day and for more years 8
than subcohort members, as did the laryngeal cancer cases. Cases for all three cancers consumed more alcohol per day and were, on average, more often and longer (highly) exposed to asbestos. Although FINJEM generally revealed a somewhat lower percentage of ever-exposed subjects, DOMJEM showed the lowest percentage of highly exposed subjects. When studying the association between asbestos exposure and covariates in the subcohort (Table 2), subjects exposed to asbestos more often smoked cigarettes and for more years, with the JEMs showing different patterns over the tertiles. Alcohol consumption was higher for those never exposed to asbestos than for those exposed, as classified according to both JEMs. There was an association between exposure to silica and polycyclic aromatic hydrocarbons and asbestos exposure, with DOMJEM showing an increasing pattern over the tertiles of exposure, while the pattern for FINJEM was less clear. Overall, all asbestos exposure variables were positively associated with risk of mesothelioma, lung cancer, and laryngeal cancer, using both DOMJEM and FINJEM, and for the age-adjusted (mesothelioma and laryngeal cancer) and for family history of lung cancer–adjusted (yes/no) (lung cancer) models as well as the multivariable-adjusted models (Tables 3 to 5). Adjusting for potential confounders had no influence on the association with mesothelioma, and little to no effect on the association with lung and laryngeal cancer. Therefore, only multivariable-adjusted results are mentioned in the text hereafter. Overall, DOMJEM revealed a higher HR (95% CI) for the duration of high exposure (tertile 3 vs never: HR = 13.66 [95% CI, 5.86 to 31.84] for mesothelioma; HR = 2.99 [95% CI, 1.39 to 6.41] for lung cancer; and HR = 6.36 [95% CI, 2.18 to 18.53] for laryngeal cancer) than FINJEM (HR = 3.28 [95% CI, 1.82 to 5.92] for mesothelioma; HR = 1.74 [95% CI, 1.20 to 2.54] for lung cancer; and HR = 1.49 [95% CI, 0.75 to 2.97] for laryngeal cancer). FINJEM showed a higher HR (95% CI) for ever versus never exposed (HR = 3.02 [95% CI, 2.11 to 4.34] for mesothelioma; HR = 1.50 [95% CI, 1.27 to 1.78] for lung cancer; and HR = 1.42 [95% CI, 0.99 to 2.03] for laryngeal cancer) than DOMJEM (HR = 2.62 [95% CI, 1.82 to 3.76] for mesothelioma; HR = 1.19 [95% CI, 1.02 to 1.40] for lung cancer; and HR = 1.20 [95% CI, 0.84 to 1.72] for laryngeal cancer). For mesothelioma (Table 3), associations generally reached statistical significance and showed a clear dose–response relation when including the never-exposed subjects (Ptrend < 0.001). When only including the exposed subjects, only DOMJEM showed a significant trend (Ptrend < 0.001). For lung cancer (Table 4), not all associations were statistically significant, though tests for trend were significant when including the never-exposed subjects (Ptrend < 0.05). When only the exposed subjects were considered, trends were no longer significant. Results by histology of lung cancer were fairly comparable to overall lung cancer apart from adenocarcinoma, for which associations with most exposure variables were weaker or absent. The only exception was the duration of high exposure for DOMJEM, which showed a statistically significant association for the continuous variable (HR = 1.43 [95% CI, 1.06 to 1.93]) and positive trend (Ptrend = 0.047) for risk of adenocarcinoma. For laryngeal cancer (Table 5), risk by location showed usually stronger associations for supraglottis than glottis cancer, except for the duration of high exposure for DOMJEM, which was statistically significant for both the highest tertile (HR = 7.09 [95% CI, 2.31 to 21.74]) and the continuous variable, as was the dose–response relation (Ptrend = 0.002). The joint effect of asbestos and smoking for each cancer endpoint was assessed by comparing the HRs of current smokers not exposed to asbestos and never-smokers exposed to asbestos with the HR of current smokers exposed to asbestos (Table 6). Given space
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JOEM r Volume 56, Number 1, January 2014
Occupational Asbestos Exposure and Respiratory Tract Tumors
TABLE 1. Distribution of Potential Confounders and Asbestos Exposure* Among Male Subcohort Members and Cancer Cases in the NLCS, 1986–2003 Subcohort (n = 2,107)
Age at baseline, yrs Family history of lung cancer Cigarette smoking Never Former Current Number of cigarettes per day†‡ Years of smoking†‡ Alcohol consumption, ‡ g/d DOMJEM Never exposed§ Ever exposed§ Duration of exposure, || yrs T1 (median: 4) T2 (median: 18) T3 (median: 37) Cumulative probability × intensity of exposure, unit-years T1 (median: 4) T2 (median: 20) T3 (median: 38) Ever highly exposed|| Duration of high exposure,|| yrs T1 (median: 4) T2 (median: 11) T3 (median: 31) FINJEM Never exposed§ Ever exposed§ Duration of exposure, || yrs T1 (median: 7) T2 (median: 25) T3 (median: 37) Cumulative probability × intensity of exposure, f-y/mL T1 (median: 0.20) T2 (median: 1.58) T3 (median: 6.57) Ever highly exposed|| Duration of high exposure,|| yrs T1 (median: 6) T2 (median: 20) T3 (median: 35)
Pleural Mesothelioma Cases (n = 145)
Lung Cancer Cases (n = 2,592)
Laryngeal Cancer Cases (n = 184)
n
Mean/%
SD
n
Mean/%
SD
n
Mean/%
SD
n
Mean/%
SD
2,107 204
61.3 9.7
4.2
145 NA
61.1 NA
4.1
2,592 321
62.0 12.4
4.1
184 NA
61.8 NA
3.9
264 1,080 763 1,722 1,807 2,066
12.5 51.3 36.2 17.1 33.6 15.0
18 75 52 115 125 140
12.4 51.7 35.9 17.2 33.3 16.2
100 827 1,663 2,243 2,454 2,534
3.9 31.9 64.2 19.8 40.7 18.4
4 63 117 166 180 180
2.2 34.2 63.6 18.3 39.6 22.3
1,498 609
71.1 28.9
69 76
47.6 52.4
1,760 832
67.9 32.1
127 57
69.0 31.0
214 200 195
35.2 32.8 32.0
10 30 36
13.1 39.5 47.4
232 293 307
27.9 35.2 36.9
17 16 24
29.8 28.1 42.1
217 192 200 49
35.7 31.5 32.8 2.3
7 21 48 28
9.2 27.6 63.2 19.3
234 269 329 110
28.1 32.3 39.6 4.2
15 18 24 9
26.3 31.6 42.1 4.9
17 16 16
34.6 32.7 32.7
6 7 15
21.4 25.0 53.6
33 27 50
30.0 24.6 45.4
1 2 6
11.1 22.2 66.7
1,561 546
74.1 25.9
73 72
50.3 49.7
1,732 860
66.8 33.2
130 54
70.7 29.3
186 178 182
34.1 32.6 33.3
20 21 31
27.8 29.2 43.0
261 323 276
30.3 37.6 32.1
20 18 16
37.1 33.3 29.6
182 182 182 292
33.4 33.3 33.3 13.9
21 25 26 42
29.2 34.7 36.1 29.0
245 280 335 521
28.5 32.6 38.9 20.1
17 19 18 29
31.5 35.2 33.3 15.8
102 95 95
35.0 32.5 32.5
12 12 18
28.6 28.6 42.8
146 186 189
28.0 35.7 36.3
8 9 12
27.6 31.0 41.4
10.6 11.9 16.9
11.0 12.1 16.4
10.6 9.2 19.4
9.7 10.2 25.8
*Exposure dichotomized or categorized in never-exposed subjects and tertiles (T) of exposed subjects in the subcohort. †Among former and current smokers only. ‡Sum of categories deviates from total number because of missing values. §Exposure based on the cumulative probability × intensity of exposure (unit-years or f-y/mL). ||Exposure based on the probability × intensity of exposure (unit years or f-y/mL) per job. f-y/mL, fiber-years/mL; NA, not applicable; NLCS, Netherlands Cohort Study.
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JOEM r Volume 56, Number 1, January 2014
Offermans et al
TABLE 2. Association Between Category of Asbestos Exposure and Potential Confounders in the Subcohort in the NLCS, 1986–2003 Asbestos Exposure Based on the Cumulative Probability × Intensity Characteristic DOMJEM Age at baseline, mean, yrs Family history of lung cancer, % Cigarette smoking, % Never Former Current Number of cigarettes per day,* mean Years of smoking,* mean Alcohol consumption, mean, g/d Silica,† % Never exposed T1 (median: 7) T2 (median: 27) T3 (median: 47.5) PAHs,† % Never exposed T1 (median: 4) T2 (median: 18.5) T3 (median: 36) FINJEM Age at baseline, mean, yrs Family history of lung cancer, % Cigarette smoking, % Never Former Current Number of cigarettes per day,* mean Years of smoking,* mean Alcohol consumption, mean, g/d Silica,† % Never exposed T1 (median: 0.33) T2 (median: 1.45) T3 (median: 4.80) PAHs,† % Never exposed T1 (median: 0.08) T2 (median: 0.27) T3 (median: 0.77)
Never Exposed
T1
T2
T3
61.4 9.9
Median: 4 unit-years 61.1 9.7
Median: 20 unit-years 61.3 10.4
Median: 38 unit-years 60.9 7.5
14.0 50.9 35.1 17.1 33.5 15.5
8.8 55.8 35.4 17.4 32.6 14.1
9.9 48.4 41.7 16.6 34.8 12.9
8.0 51.5 40.5 16.7 34.5 15.0
88.4 3.2 4.2 4.2
78.4 16.1 4.6 0.9
82.3 3.1 9.4 5.2
86.5 3.5 4.5 5.5
96.2 0.8 1.5 1.5
81.6 14.7 2.8 0.9
82.8 3.7 10.9 2.6
79.5 4.5 3.5 12.5
61.4 10.1
Median: 0.20 f-y/mL 61.1 8.2
Median: 1.58 f-y/mL 60.4 13.2
Median: 6.57 f-y/mL 61.0 4.4
13.4 51.4 35.2 17.0 33.4 15.7
12.1 53.3 34.6 16.0 32.8 12.0
6.6 55.5 37.9 18.5 34.2 14.9
11.0 44.0 45.0 16.6 36.0 12.9
98.8 0.1 0.4 0.7
81.3 14.8 1.7 2.2
68.7 17.6 9.3 4.4
41.2 6.6 25.3 26.9
97.8 0.5 0.8 0.9
80.2 6.6 3.3 9.9
58.8 13.2 18.1 9.9
68.2 14.8 7.7 9.3
*Among former and current smokers only. †Exposure based on the cumulative probability × intensity of exposure (unit-years or f-y/mL), categorized in never-exposed subjects and tertiles of exposed subjects in the subcohort. f-y/mL, fiber-years/mL; NLCS, Netherlands Cohort Study; PAHs, polycyclic aromatic hydrocarbons.
limitations and because HRs for ever versus never exposed were overall higher for FINJEM than for DOMJEM, we will only present results for FINJEM. For mesothelioma, the observed HR of 4.18 for the combined exposure category is lower than the product of HRs for asbestos and smoking (5.39 × 1.35 = 7.28), indicating that the joint effect is less than multiplicative. The observed HR is also lower than expected
10
when using an additive model (5.39 + 1.35 − 1 = 5.74). For lung cancer, the observed HR of 10.21 is lower than the product of asbestos and smoking (7.48 × 1.79 = 13.39), indicating that the joint effect is less than multiplicative. The observed HR is higher than what would have been expected by using an additive model (7.48 + 1.79 − 1 = 8.27). For laryngeal cancer, the observed HR of 20.73 is lower than the product (16.95 × 2.27 = 38.48), indicating that the joint effect is
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JOEM r Volume 56, Number 1, January 2014
Occupational Asbestos Exposure and Respiratory Tract Tumors
TABLE 3. Hazard Ratios, 95% CIs, and PAFs for Pleural Mesothelioma for Categories of Asbestos Exposure,* Estimated With DOMJEM and FINJEM in the NLCS, 1986–2003† Pleural Mesothelioma
DOMJEM Never exposed|| Ever exposed|| Duration of exposure,¶ yrs T1 (median: 4) T2 (median: 18) T3 (median: 37) Ptrend (over the exposed only) Continuous, per 10 yrs Cumulative probability × intensity of exposure, unit-years T1 (median: 4) T2 (median: 20) T3 (median: 38) Ptrend (over the exposed only) Continuous, per 1 unit-year Duration of high exposure,¶ yrs Never highly exposed T1 (median: 4) T2 (median: 11) T3 (median: 31) Ptrend (over the exposed only) Continuous, per 10 yrs FINJEM Never exposed|| Ever exposed|| Duration of exposure,¶ yrs T1 (median: 7) T2 (median: 25) T3 (median: 37) Ptrend (over the exposed only) Continuous, per 10 yrs Cumulative probability × intensity of exposure, f-y/mL T1 (median: 0.20) T2 (median: 1.58) T3 (median: 6.57) Ptrend (over the exposed only) Continuous, per 1 fiber-year Duration of high exposure,¶ yrs Never highly exposed T1 (median: 6) T2 (median: 20) T3 (median: 35) Ptrend (over the exposed only) Continuous, per 10 yrs
Person Years in Subcohort
n
HR‡ (95% CI)
HR§ (95% CI)
PAF, %
107,557 41,688
66 66
1 (ref) 2.61 (1.83–3.73)
1 (ref) 2.62 (1.82–3.76)
31.9
15,469 12,615 13,604
10 26 30
149,245
132
1.02 (0.52–2.02) 3.55 (2.19–5.78) 3.67 (2.32–5.80)
