Document 93E0L1dQ4xXy2om7wqdgGvnND

Downloaded from http://ije.oxfordjournals.org/ by Troy Chandler on July 19, 2012 Published by Oxford University Press on behalf of the International Epidemiological Association 2012. Advance Access publication 31 March 2012 International Journal of Epidemiology 2012;41:711-721 doi:10.1093/ije/dys042 Impact of occupational carcinogens on lung cancer risk in a general population Sara De Matteis,1,2 Dario Consonni,1 Jay H Lubin,2 Margaret Tucker,2 Susan Peters,3 Roel CH Vermeulen,3 Hans Kromhout,3 Pier Alberto Bertazzi,1 Neil E Caporaso,2 Angela C Pesatori,1 Sholom Wacholder2 and Maria Teresa Landi2* 1Unit of Epidemiology, Department of Preventive Medicine, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico and EPOCA Research Centre, Department of Occupational and Environmental Health, Universita degli Studi di Milano, Milan, Italy, 2Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA and 3Institute for Risk Assessment Sciences, Environmental Epidemiology Division, Utrecht University, Utrecht, The Netherlands Corresponding author. Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD 20892, USA. E-mail: landim@mail.nih.gov Accepted 23 February 2012 Background Exposure to occupational carcinogens is an important preventable cause of lung cancer. Most of the previous studies were in highly exposed industrial cohorts. Our aim was to quantify lung cancer burden attributable to occupational carcinogens in a general population. Methods We applied a new job-exposure matrix (JEM) to translate lifetime work histories, collected by personal interview and coded into standard job titles, into never, low and high exposure levels for six known/suspected occupational lung carcinogens in the Environment and Genetics in Lung cancer Etiology (EAGLE) population-based case-control study, conducted in Lombardy region, Italy, in 2002-05. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated in men (1537 cases and 1617 controls), by logistic regression adjusted for potential confounders, including smoking and co-exposure to JEM carcinogens. The popu lation attributable fraction (PAF) was estimated as impact measure. Results Men showed an increased lung cancer risk even at low exposure to asbestos (OR: 1.76; 95% CI: 1.42-2.18), crystalline silica (OR: 1.31; 95% CI: 1.00-1.71) and nickel-chromium (OR: 1.18; 95% CI: 0.90-1.53); risk increased with exposure level. For polycyclic aromatic hydrocarbons, an increased risk (OR: 1.64; 95% CI: 0.99 2.70) was found only for high exposures. The PAFs for any expos ure to asbestos, silica and nickel-chromium were 18.1, 5.7 and 7.0%, respectively, equivalent to an overall PAF of 22.5% (95% CI: 14.1-30.0). This corresponds to about 1016 (95% CI: 637-1355) male lung cancer cases/year in Lombardy. Conclusions These findings support the substantial role of selected occupational carcinogens on lung cancer burden, even at low exposures, in a general population. Keywords lung neoplasms, case-control study, carcinogens, occupational health 711 IMPACT OF OCCUPATIONAL CARCINOGENS ON LUNG CANCER 713 Downloaded from http://ije.oxfordjournals.org/ by Troy Chandler on July 19, 2012 Statistical analysis For each carcinogen, we evaluated a dichotomous ex posure indicator (never/any) and an ordinal variable for intensity of exposure (never/low/high). Further, we analysed duration and cumulative exposure as the sum of the job-specific (intensity score x dur ation) products (with scores set to 1 and 4 for low and high exposure, respectively). Latency was defined as time at lung cancer diagnosis or study enrolment since first exposure. The analyses were conducted using both categorical and continuous variables. For duration and cumulative exposure, we defined the categories according to the quartiles of the exposure distribution among controls for each carcinogen. For latency, we used predefined categories of exposure (never, 20-29, 30-39, 40-49, 50-59 and 560 years) to explore their impact on a broader range of years since first exposure. When analysing those variables as continuous, we used the ln (1 + x) transformation to normalize their distribution. We evaluated co-exposure to the JEM carcinogens using Spearman's rank correlation coefficient (ps). For each carcinogen exposure, we calculated odds ratios (ORs), 95% confidence intervals (95% CIs) and tests for trend, using unconditional logistic re gression, separately for males and females, taking subjects never exposed to the carcinogen as reference. All regression models included the following covari ates: residential area (five categories); age (5-year categories); cigarette smoking (ever/never); pack-years (continuous, mean-centred: linear, quad ratic and cubic terms); time since quitting (0 for never/current smokers, 0.5, 1, 2, 5, 10, 20, 530 years); smoking (ever/never) of other types of tobacco (pipe, cigars and cigarillos) and, for each agent, co-exposure to the other carcinogens included in the JEM. We also adjusted for number of jobs held (1, 2, 3, 4, 55), since this variable was negatively asso ciated with lung cancer among non-exposed subjects (Ptrend = 0.014) and positively associated with expos ure to carcinogens among controls (P < 0.0001 from chi-squared test). We used the same approach in our previous article on occupations known/suspected to be associated with lung cancer risk.6 A similar approach was also used in other case-control studies from Northern Italy and France.12,13 We repeated selected analyses after adjusting for education (none, elementary, middle and high school/higher degree) as a surrogate of socio economic status. For the exposures showing an increased OR, we calculated the carcinogen specific and overall PAF by using the formula PEC x (OR - 1)/OR,14 where OR is the adjusted OR and PEC is the proportion of cases ever exposed to the carcinogen under study. The def inition of exposure we used when calculating PAF estimates considers subjects unexposed to the carcino gen under study as belonging to the 'reference' cat egory and everyone even slightly exposed as belonging to the 'exposed' category. Estimates of PAF when using this broad definition of 'exposed' are less prone to bias from non-differential misclassification of exposure, the form of misclassification expected with a JEM approach.15 We estimated ORs for the three main histological lung cancer types (adenocar cinoma, squamous cell and small-cell carcinomas) and tested their homogeneity in a multinomial logistic regression model. We evaluated interactions between each carcinogen (never/any exposure) and cigarette smoking status (never/former/current) on the multiplicative scale, by comparing the likelihood of a logistic regression model containing the main effects of the carcinogen and smoking with that of a model also containing their interaction. As reference, we used subjects never exposed to both smoking and the specific car cinogen under study. In these models, we did not adjust for co-exposure to the other JEM carcinogens to avoid too few subjects per strata. All P-values were two-sided. Analyses were per formed with Stata 11.16 Confidence limits of PAF were calculated with the command aflogit that imple mented the formulas proposed by Greenland and Drescher.17 Results Of the 2100 cases and 2120 controls enrolled in our study, 1943 (92.5%) and 2116 (99.8%) were inter viewed, respectively (Table 1). Two-thirds of the sub jects came from the Milan area. Among men, controls had higher education and held more jobs than cases. About 14-15% of the cases and 6-7% of the controls had previously or newly diagnosed primary cancer(s) other than lung cancer. Among cases, one-fourth of the women were never smokers vs only 2% of men. In both genders, current smokers were ~50% among cases and <30% among controls. Almost half of the men (cases or controls) were former (quit>6 months ago) smokers when compared with <30% among women. The majority of lung cancers were adenocar cinomas (>50% in women). Lifetime co-exposure to pairs of JEM carcinogens was frequent (Supplementary Table 1, available as Supplementary data at IJE online). In particular, Cr and Ni were strongly correlated: among men ps = 0.75 in cases; ps = 0.83 in controls; among women ps = 1.00 in both; all with P <0.001. For this reason, we combined these agents in a single variable Ni-Cr. Very few women were found to be exposed to the six occupational lung carcinogens, particularly at high levels, except asbestos (11.3% among cases and 10.0% among controls) and PAH (12.1% among cases and 9.8% among controls) (Supplementary Table 2, avail able as Supplementary data at IJE online). Although based on small numbers, we found an increased risk for any exposure to Ni-Cr (OR = 2.80; 95% CI: 1.20 6.54), with a positive trend for intensity (P = 0.03). 714 INTERNATIONAL JOURNAL OF EPIDEMIOLOGY Downloaded from http://ije.oxfordjournals.org/ by Troy Chandler on July 19, 2012 Table 1 Selected characteristics of lung cancer cases and controls with interview data available: the EAGLE study, Lombardy, Italy, 2002-05a,b Subjects characteristics Total participants enrolled Interviewed Area of residence Milan Monza Brescia Pavia Varese P-value Age (years) Mean (SD) P-value Education level None Elementary Middle High University P-value Number of jobs 1 2 3 4 >5 P-value Cigarette smoking Never Former (quit >6 months ago) Current Unknown P-value Cigarette pack-years Mean (SD) P-value Other cancer(s)c No Yes P-value Lung cancer morphology Adenocarcinoma Women Cases N (%) 448 Controls N (%) 500 406 (100.0) 499 (100.0) Men Cases N (%) 1652 Controls N (%) 1620 1537 (100.0) 1617 (100.0) 288 (70.9) 349 (69.9) 24 (5.9) 23 (4.6) 47 (11.6) 53 (10.6) 21 (5.2) 37 (7.4) 26 (6.4) 37 (7.4) 0.55 987 (64.2) 1089 (67.3) 109 (7.1) 94 (5.8) 203 (13.2) 194 (12.0) 107 (7.0) 92 (5.7) 131 (8.5) 148 (9.2) 0.17 64.8 (10.1) 64.1 (10.1) 0.32 66.8 (7.9) 65.8 (8.1) <0.001 21 (5.2) 24 (4.8) 128 (31.5) 143 (28.7) 134 (33.0) 158 (31.7) 104 (25.6) 135 (27.1) 19 (4.7) 39 (7.8) 0.35 91 (5.9) 66 (4.1) 625 (40.7) 431 (26.7) 424 (27.6) 455 (28.1) 314 (20.4) 441 (27.3) 83 (5.4) 224 (13.9) <0.001 166 (40.9) 168 (33.7) 96 (23.7) 158 (31.7) 77 (19.0) 82 (16.4) 30 (7.4) 49 (9.8) 37 (9.1) 42 (8.4) 0.03 375 (24.4) 370 (22.9) 404 (26.3) 356 (22.0) 305 (19.8) 356 (22.0) 194 (12.6) 226 (14.0) 259 (16.9) 309 (19.1) 0.02 103 (25.4) 282 (56.5) 116 (28.6) 110 (22.0) 187 (46.1) 107 (21.4) 0 (0.0) 0 (0.0) <0.001 29 (1.9) 397 (24.6) 723 (47.0) 799 (49.4) 785 (51.1) 420 (26.0) 0 (0.0) 1 (0.1) <0.001 24.3 (23.1) 7.2 (13.5) <0.001 50.9 (28.7) 22.1 (23.2) <0.001 336 (82.8) 448 (89.8) 70 (17.2) 51 (10.2) 0.002 1306 (85.0) 1473 (91.1) 231 (15.0) 144 (8.9) 0.001 220 (54.2) 582 (37.9) (continued) Downloaded from http://ije.oxfordjournals.org/ by Troy Chandler on July 19, 2012 716 INTERNATIONAL JOURNAL OF EPIDEMIOLOGY Table 2 Lung cancer risk for exposure to JEM carcinogens for men in the EAGLE study, Lombardy, Italy, 2002-05a Carcinogens Asbestos Never6 Any Low High P-value Silica Nevere Any Low High P-value Ni-Cr Nevere Cases, N (%) 905 (58.9) 632 (41.1) 546 (35.5) 86 (5.6) 1166 (75.9) 371 (24.1) 328 (21.3) 43 (2.8) 1041 (67.7) Controls, N (%) 1097 (67.8) 520 (32.2) 448 (27.7) 72 (4.5) 1363 (84.3) 254 (15.7) 226 (14.0) 28 (1.7) 1216 (75.2) ORb (95% CI) 1.00 1.73 (1.43-2.09) 1.68 (1.38-2.04) 2.09 (1.39-3.13) 0.001 1.00 1.38 (1.10-1.72) 1.37 (1.09-1.73) 1.46 (0.81-2.61) 0.006 1.00 ORc (95% CI) 1.00 1.78 (1.46-2.18) 1.76 (1.42-2.18) 1.51 (0.94- 2.44) <0.001 1.00 1.31 (1.02-1.68) 1.31 (1.00-1.71) 1.41 (0.77-2.55) 0.02 1.00 PAFd % (95% CI) 18.1 (12.6-23.3) 5.7 (0.4-10.6) Any Low High P-value PAH Nevere Any Low High P-value DME Nevere Any Low High P-value 496 (32.3) 370 (24.1) 126 (8.2) 1137 (74.0) 400 (26.0) 284 (18.5) 116 (7.5) 940 (61.2) 597 (38.8) 476 (31.0) 121 (7.8) 401 (24.8) 328 (20.3) 73 (4.5) 1235 (76.4) 382 (23.6) 321 (19.9) 61 (3.7) 994 (61.5) 623 (38.5) 500 (30.9) 123 (7.6) 1.41 (1.16-1.72) 1.33 (1.08-1.65) 1.77 (1.22-2.56) <0.001 1.00 1.11 (0.90-1.36) 0.90 (0.72-1.13) 2.46 (1.65-3.67) 0.007 1.00 0.90 (0.75-1.09) 0.89 (0.73-1.09) 0.96 (0.68-1.35) 0.44 1.28 (1.00-1.63) 1.18 (0.90-1.53) 1.31 (0.86-1.97) 0.06 1.00 0.87 (0.68-1.10) 0.78 (0.61-1.00) 1.64 (0.99-2.70) 0.75 1.00 0.82 (0.67-1.00) 0.85 (0.69-1.05) 0.70 (0.48-1.00) 0.047 7.0 (0.2-13.3) DME, diesel motor exhausts; Ni-Cr, nickel and chromium compounds; PAF, population attributable fraction;. aP-values were calculated from test for linear trend for never/low/high exposure. bOR calculated with unconditional logistic regression models, adjusted for area, age, smoking and number of jobs. cOR adjusted as specified in the above footnote and also for co-exposure to the other JEM carcinogens. dPAF calculated for any exposure to each carcinogen associated with an increased risk using, as specified in the above footnote, OR and percentage of cases exposed to each carcinogen. eReference category: never exposed to the specific carcinogen. a high prevalence of exposure to asbestos: the Occupational Safety & Health Administration (OSHA) recently estimated 1.3 million workers still being exposed in the USA in the construction and general industry.23 In Italy, it was reported that about 70 000 construction workers in the period 2000-03 were still exposed to asbestos.24 We found a 1.31-fold increased risk for exposure to crystalline silica even among a majority of low-exposed subjects, as observed in only two previous studies.25,26 Of note, only 5 men (3 highly exposed and 2 not exposed) out of 1537 cases and 3 men (1 highly exposed and 2 not exposed) out of 1617 controls re ported having been diagnosed with silicosis. These findings support silica carcinogenicity per se, against the still debated hypothesis of silicosis as necessary intermediate factor for lung cancer aetiology.27-29 The exposed subjects in our study were principally em ployed in the construction sector (e.g. bricklayers), rather than in high-risk industries, such as mining Downloaded from http://ije.oxfordjournals.org/ by Troy Chandler on July 19, 2012 IMPACT OF OCCUPATIONAL CARCINOGENS ON LUNG CANCER 717 Table 3 Lung cancer risk for exposure to JEM carcinogens by main histological types for men in the EAGLE study, Lombardy, Italy, 2002-05a Adenocarcinoma Squamous cell carcinoma Carcinogen Controls, N Cases, N ORc (95% CI) Cases, N ORc (95% CI) Total 1617 582 459 Asbestos Neverd 1097 346 1.00 270 1.00 Any 520 236 1.75 (1.37-2.23) 189 1.85 (1.40-2.43) Low 448 202 1.76 (1.36- 2.29) 163 1.73 (1.29- 2.34) High 72 34 1.67 (0.93-2.97) 26 1.34 (0.69- 2.63) P-value <0.001 0.002 Small-cell carcinoma Cases, N ORc (95% CI) 157 Pb 85 1.00 72 2.04 (1.38, 3.00) 65 1.92 (1.26, 2.92) 7 1.09 (0.40, 2.94) 0.03 0.65 Silica Neverd Any Low High P-value Ni-Cr Neverd Any Low High P-value PAH Neverd Any Low High P-value DME Neverd Any Low High P-value 1363 254 226 28 1216 401 328 73 1235 382 321 61 994 623 500 123 480 1.00 322 102 0.94 (0.68-1.31) 137 94 0.97 (0.69-1.37) 118 85 0.71 (0.30-1.70) 19 0.56 421 1.00 291 161 1.15 (0.84-1.57) 168 127 1.13 (0.81-1.58) 124 34 0.95 (0.55-1.63) 44 0.84 447 1.00 331 135 0.75 (0.56-1.02) 128 103 0.71 (0.52-0.97) 83 32 1.24 (0.66-2.36) 45 0.28 379 1.00 259 203 0.77 (0.60-0.99) 200 162 0.80 (0.62-1.04) 162 41 0.65 (0.41-1.02) 38 0.03 1.00 1.66 (1.19-2.33) 1.64 (1.14-2.34) 2.30 (1.09-4.86) 0.001 111 46 40 6 1.00 1.47 (1.05-2.06) 1.31 (0.91-1.89) 1.59 (0.90-2.81) 0.06 105 52 34 18 1.00 0.97 (0.69-1.35) 0.81 (0.57-1.16) 2.44 (1.25-4.76) 0.34 112 45 30 15 1.00 1.04 (0.79-1.38) 1.09 (0.82-1.46) 0.92 (0.55-1.53) 0.94 97 60 45 15 1.00 2.03 (1.26-3.27) 2.11 (1.27-3.52) 2.29 (0.81-6.51) 0.003 0.03 1.00 0.98 (0.60-1.59) 0.79 (0.46-1.37) 1.46 (0.68-3.15) 0.69 0.23 1.00 1.01 (0.63-1.61) 0.87 (0.53-1.44) 2.32 (0.94-5.73) 0.48 0.12 1.00 0.65 (0.43-0.99) 0.67 (0.43-1.04) 0.70 (0.35-1.41) 0.11 0.44 DME, diesel motor exhausts; Ni-Cr, nickel and chromium compounds. aP values were calculated from test for linear trend for never/low/high exposure. bP values were calculated from test of homogeneity between ORs. cOR calculated with unconditional logistic regression models, adjusted for area, age, smoking, number of jobs and for co-exposure of the other JEM carcinogens. dReference category: never exposed to the specific carcinogen. and quarrying, as in most of the first occupational cohort studies.27,28,30-33 As a confirmation, when we excluded from the ana lysis the 328 cases and 254 controls that have ever held a job in the construction sector, only the ORs for any exposure to silica were slightly decreased (OR = 1.2; 95% CI: 0.83-1.62 instead of the original OR = 1.3; 95% CI: 1.02-1.68). Our findings emphasize the high public health impact of silica exposure, which is currently estimated the most common occu pational exposure worldwide, with tens of millions of workers, particularly in the construction sector.2 In Italy, 250 000 workers were reported to be exposed in the period 2000-03.24 718 INTERNATIONAL JOURNAL OF EPIDEMIOLOGY Table 4 Lung cancer risk for the joint exposure to cigarette smoking and asbestos, silica and nickel-chromium for men in the EAGLE study, Lombardy, Italy, 2002-05 Never smokers Former smokers Current smokers Carcinogen Asbestos Never Any Pc-value Silica Never Any Pc-value Ni-Cr Never Any Pc-value Ca/Co 15/277 14/120 24/347 5/50 21/306 8/91 ORa (95% CI) 1.00b 2.47 (1.15-5.31) 1.00b 1.41 (0.51-3.91) 1.00b 1.33 (0.57-3.12) Ca/Co 424/500 299/249 0.19 543/663 180/136 0.94 496/597 227/202 0.86 ORa (95% CI) 14.25 (8.31-24.43) 25.30 (14.51-44.12) 11.82 (7.67-18.23) 18.94 (11.73-30.57) 11.97 (7.54-19.00) 17.41 (10.66-28.43) Ca/Co 466/270 319/150 599/352 186/68 524/312 261/108 ORa (95% CI) 35.67 (20.68-61.53) 49.54 (28.18-87.08) 26.87 (17.34-41.63) 44.98 (27.15-74.52) 26.73 (16.74-42.67) 42.29 (25.54-70.04) Ca, cases; Co, controls; Ni-Cr, nickel and chromium compounds. aCalculated with unconditional logistic regression models, adjusted for area, age and number of jobs. bReference category: never exposed to both carcinogen and smoking. cPmteraction values were calculated from 2-df log-likelihood ratio tests between the model with and without interaction term for joint exposure to smoking (never/former/current smoking status) and the specific carcinogen (never/any exposure). Downloaded from http://ije.oxfordjournals.org/ by Troy Chandler on July 19, 2012 The specificity of association of silica exposure with squamous and small-cell carcinomas, and not with adenocarcinoma, could only be evaluated in a few studies with enough power. A Canadian study found a risk pattern consistent with ours,26 whereas a recent multicentric study from Central-Eastern Europe found increased ORs for all the three histological types.25 Our results could in theory be explained by residual confounding by smoking, considering that these histological types are known to be strongly asso ciated with tobacco exposure.34 To rule out this possibility, we stratified the analyses by smoking status: the increased risk was evident among all smoking strata (although there were few exposed subjects especially among never smokers; data not shown), supporting the hypothesis of an independent effect of silica with respect to smoking. We estimated a 1.18-fold increased risk for com bined exposure to Ni and Cr among low-exposed workers (e.g. metal mechanics) instead of highly exposed workers in nickel refinery industries35 and chromate production,36 as previously reported. In add ition, previous studies lacked detailed data on smok ing exposure and could not adjust for co-exposure to other carcinogens. Only one similar study found an increased risk also at low levels, but for single Ni exposure.37 Our approach of combining Ni and Cr ex posures has been previously adopted because of the frequent simultaneous use of these carcinogens in most workplaces.38 We found a 1.64-fold increased risk for exposure to PAH only among highly exposed workers employed in metal basic industries, as in a recent large European multicentric study.39 One study reported an increased risk also for any exposure to PAH,40 but it did not adjust for co-exposure to other carcinogens (in par ticular asbestos), which in our study substantially decreased the risk estimates. Our null result for any exposure to DME is consistent with other population-based studies,41-43 but not all,8,44 possibly because of misclassification of the 'nonexposed' subjects in our study due to the high back ground levels of DME in the urban areas. Unlike our study that includes mostly professional drivers (e.g. bus and taxi drivers), the majority of previous discord ant occupational cohorts included highly exposed miners and railroad workers,45-47 had inaccurate DME exposure assessment, scarce or null information on smoking, inadequate latency periods or failed to adjust for other carcinogens.48-51 A multiplicative effect for joint exposure to asbestos and smoking has been found in the majority of studies, even if a high variability of patterns is reported.52,53 In contrast, to our knowledge, this is the first time that it has been found for smoking and silica. The few studies with enough lung cancer cases among never smokers reported a superadditive, but less than multiplicative interaction model.25,26 For Ni-Cr, the comparison with previous studies is limited by the combined exposure variable used: patterns from multiplicative to additive were found for the single carcinogens.35,37,54 The PAFs estimated for any exposure to asbestos, silica and Ni-Cr with a JEM approach are higher IMPACT OF OCCUPATIONAL CARCINOGENS ON LUNG CANCER 719 Downloaded from http://ije.oxfordjournals.org/ by Troy Chandler on July 19, 2012 than that we previously reported of 4.9%.6 This is an expected finding due to the higher sensitivity of the JEM as method of exposure assessment,4 compared with job title approach, therefore more suitable to detect specific hazards across a large range of differ ent job categories, as occur in a general population. In the literature, a wide PAF variability for these three carcinogens, between 1% and 40%, was re ported,2'19'55'56 probably because of differences in study design, exposure assessment methods or adjust ment for confounders. Our industrial setting was also characterized by a low prevalence of high risk sectors (e.g. shipbuilding and railroad equipment manufac turing).6 Although based on different numbers of car cinogens and sources for the risk estimates, our overall PAF (22.5%) was very similar to the overall PAF found in a recent study from UK (21.1%),56 and higher than that found in France (12.5%).55 By applying our PAFs to the lung cancer incidence rates in males in Lombardy in 2 005,57 we estimated that 817 (95% CI: 569-1052), 257 (95% CI: 18-479), 316 (95% CI: 9-600) and 1016 (95% CI: 637-1355) lung cancer cases were attributable to occupational exposure to asbestos, silica, Ni-Cr and these three ex posures combined, respectively. If we consider also the increased risk found for high exposure to PAH, corresponding to a PAF of 2.9% (95% CI: 0.1-5.9), there would be 131 additional potentially avoidable cases (95% CI: 5-266). These numbers sharply con trast with those officially reported to and compen sated by the Italian Workers' Compensation Authority. For instance, in the period 1999-2004, only 399 work-related lung cancer cases (on average 66.5/year) were reported in Lombardy and about half of them compensated.58 The present study has a number of strengths: enrolment of incident cases and randomly sampled population controls, large sample size, elevated par ticipation rates and face-to-face interviews by trained operators. Reliability of self-reported job history is considered good and not an important source of recall bias.4 The 'DOM-JEM' has unique qualities: it was de veloped blindly to case-control status to avoid poten tial differential exposure misclassification7 by a team of trained experts with an excellent inter-rater agree ment (between 77% and 95%). Moreover, it covers all the occupations and was also designed to have a high specificity to take into account the low exposure prevalence to occupational carcinogens in popula tion-based studies, thus increasing the proportion of subjects correctly classified as unexposed, which can decrease potential misclassification bias.4 The major drawback of the JEM approach is the possibility of non-differential exposure misclassification, due to the assignment of individual exposure to a specific carcinogen based on job title only.9 Therefore, attenu ation of the true association estimates and of expos ure-response trends is likely.59 Another possible limitation of our study is recall bias. However, we expect the resulting misclassification to be mostly non-differential because we asked about occupations, not exposure to agents. Moreover, the coding of occupations was blind with respect to case-control status. Although our detailed collection of smoking history allowed us to strictly control for smoking exposures, residual confounding from smoking cannot be completely ruled out. However, the likelihood of occurrence of substantial confounding by smoking is rare in occupational epidemiology.60 The lack of reliable risk estimates for women creates an underestimate of the true occupational lung cancer burden, but it is likely small, given the female minor ity in workplaces where the evaluated exposures occurred.61 Conclusion In conclusion, our results provide strong evidence that past occupational exposure to asbestos, crystalline silica, nickel-chromium compounds and possibly PAH still causes a substantial proportion of lung cancer cases. Although in Italy asbestos use dropped before its ban by law in 1992, it continues to have the greatest impact on lung cancer burden. This result endorses the concern of many international groups currently campaigning for a global ban on all asbestos around the world.62 Our findings support the need for policies aimed at strengthening environmental control measures and health surveillance at workplaces where dangerous exposures still exist. Supplementary Data Supplementary Data are available at IJE online. Funding Intramural Research Program of the National Institutes of Health, National Cancer Institute, Division of Cancer Epidemiology and Genetics; the Lombardy Region (Environmental Epidemiology Program); the CARIPLO Foundation, Milan, Italy; Istituto Nazionale per l'Assicurazione contro gli Infortuni sul Lavoro, INAIL, Rome, Italy. Acknowledgements The authors express their gratitude to all the EAGLE study participants and collaborators (listed on the eagle website at http://eagle.cancer.gov/) whose con tribution made this study possible. Conflict of interest: None declared.