Document Zna7zkbDoOg14gjXqez16XjJO

Downloaded from oem.bmj.com on May 12, 2011 - Published by group.bmj.com Original article The relationship between multiple myeloma and occupational exposure to six chlorinated solvents Laura S Gold,1,2 Patricia A Stewart,3 Kevin Milliken,1,2 Mark Purdue,4 Richard Severson,5 Noah Seixas,6 Aaron Blair,4 Patricia Hartge,4 Scott Davis,1,2 Anneclaire J De Roos1,2 1Program in Epidemiology, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA 2Department of Epidemiology, University of Washington School of Public Health, Seattle, Washington, USA 3Stewart Exposure Assessments LLC, Arlington, Virginia, USA 4Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA 5Department of Family Medicine and Public Health Sciences, Karmanos Cancer Institute, Wayne State University, Detroit, Michigan USA 6Department of Environmental and Occupational Health Sciences, University of Washington School of Public Health, Seattle, Washington, USA Correspondence to Laura Gold, 1100 Fairview Avenue N, PO Box 19024, Seattle, WA 98109, USA; goldl@u.washington.edu Accepted 9 June 2010 Published Online First 10 September 2010 ABSTRACT Objectives Few studies have examined whether exposure to chlorinated solvents is associated with multiple myeloma. We evaluated associations between multiple myeloma and occupational exposure to six chlorinated solvents: 1,1,1-trichloroethane, trichloroethylene (TCE), methylene chloride (DCM), perchloroethylene, carbon tetrachloride and chloroform. Methods In-person interviews obtained occupational histories and information on jobs with likely solvent exposure. We assigned exposure metrics of probability, frequency, intensity and confidence using job-exposure matrices modified by job-specific questionnaire information. We used logistic regression to estimate ORs and 95% CIs for associations between multiple myeloma and ever exposure to each, and any, chlorinated solvent and analysed whether associations varied by duration and cumulative exposure. We also considered all occupations that were given the lowest confidence scores as unexposed and repeated all analyses. Results Risk of multiple myeloma was elevated for subjects ever exposed to 1,1,1-trichloroethane (OR (95% CI): 1.8 (1.1 to 2.9)). Ever exposure to TCE or DCM also entailed elevated, but not statistically significant, risks of multiple myeloma; these became statistically significant when occupations with low confidence scores were considered unexposed (TCE: 1.7 (1.0 to 2.7); DCM: 2.0 (1.2 to 3.2)). Increasing cumulative exposure to perchloroethylene was also associated with increasing multiple myeloma risk. We observed non-significantly increased multiple myeloma risks with exposure to chloroform; however, few subjects were exposed. Conclusions Evidence from this relatively large casecontrol study suggests that exposures to certain chlorinated solvents may be associated with increased incidence of multiple myeloma; however, the study is limited by relatively low participation (52%) among controls. INTRODUCTION Multiple myeloma is an incurable plasma cell malignancy that accounts for about 20% of deaths from haematopoietic cancers and 2% of deaths from all cancers.1 While the aetiology of multiple myeloma is poorly understood, several studies have reported associations between multiple myeloma and occupations that may entail exposure to chlorinated solvents, including chemical work,2 3 construction work,4 5 painting,6e8 metal work,8e11 farm work5 12e14 and hairdressing.15e17 Few studies have specifically examined whether exposure to chlorinated solvents is associated with What this paper adds < The aetiology of multiple myeloma is poorly understood. < The purpose of this research was to examine relationships between occupational exposures to chlorinated solvents and multiple myeloma. < This research provides evidence that certain chlorinated solvents, most notably trichloroethylene, are associated with increased incidence of multiple myeloma. < While results were less clear, exposure to 1,1,1trichloroethane, methylene chloride, perchloroethylene, carbon tetrachloride and chloroform also conferred increased risk of multiple myeloma in our population. increased risk of multiple myeloma. No relationship has been found between trichloroethylene (TCE) and multiple myeloma,18e24 but the studies were based on small numbers of multiple myeloma cases. Two small studies found increased risks associated with exposure to 1,1,1-trichloroethane (TCA).21 25 In a recent cohort study, a fumigant mixture composed of carbon tetrachloride and carbon disulfide was significantly associated with monoclonal gammopathy of undetermined significance,26 a benign proliferation of plasma cells that likely precedes most multiple myeloma cases.27 Additionally, other lymphohaematopoietic cancers that may have similar aetiologies to multiple myeloma have been linked to occupational exposure to chlorinated solvents. For example, TCE has been associated with increased risk of non-Hodgkin's lymphoma (NHL).22 28 Occupational exposures to carbon tetrachloride, chloroform, methylene chloride (DCM) and perchloroethylene (PCE) have not been evaluated with respect to multiple myeloma risk, but PCE has been linked to NHL21 29 and carbon tetrachloride has been associated with leukaemia30 31 and NHL.32 Using occupational exposure information obtained from job-specific questionnaires in a population-based caseecontrol study, we evaluated associations between multiple myeloma and exposure to six major chlorinated solvents that were widely used occupationally during the time period in which our study subjects were working: TCA, TCE, DCM, PCE, carbon tetrachloride and chloroform. Occup Environ Med 2011;68:391e399. doi:10.1136/oem.2009.054809 391 Original article Downloaded from oem.bmj.com on May 12, 2011 - Published by group.bmj.com METHODS Identification of cases and controls Multiple myeloma cases were identified through the Surveillance, Epidemiology, and End Results (SEER) cancer registries in the Seattle-Puget Sound region of Washington and the Detroit metropolitan area of Michigan. These registries identified cases by reviewing medical records at all hospitals in the region, as well as by reviewing the records of selected pathology laboratories, oncologists, radiologists and state death certificates. The frequency of these reviews enabled the identification of cases within 1e2 months of diagnosis. Cases eligible to participate in this study were 35e74 years old and were diagnosed with multiple myeloma (ICD-O-2/3 9731:9732) between 1 January 2000 and 31 March 2002. Of the 365 cases who appeared eligible to participate in this study, 64 (18%) died before they could be contacted, 28 (8%) were unable to be located and the physicians of 18 (5%) refused. Of the remaining 255 who were contacted, 74 (29%) refused to participate, leaving a total of 181 cases. Thus, of cases who were alive, able to be located and whose eligibility could be confirmed, 71% (181/255) participated. Case participation was not associated with study site, age or gender. General population controls were selected from a caseecontrol study of NHL that was undertaken at the same time and included the same geographical areas as used for multiple myeloma case recruitment.33 Controls under 65 years of age were identified using random digit dialling; controls 65e74 years of age were identified from the Center for Medicare and Medicaid Services files. We selected controls for our study from among the NHL study controls who (1) had not been previously diagnosed with multiple myeloma, plasmacytoma, NHL or HIV (the latter were excluded because of the association between the virus and lymphoma development),34 (2) were between 35 and 74 years of age, (3) were identified as residents of the Detroit or Seattle-Puget Sound areas between September 1998 and December 2002, and (4) spoke English. Of the 1133 potential controls who were eligible to participate in this multiple myeloma study, 52% (481/1133) participated as NHL study controls. Control participation was not associated with study site or gender, but individuals in the youngest (35e50) and oldest (65e74) age groups were less likely to have participated than those in the middle age group. Informed consent was obtained from each participant before the interview and approval was obtained from the appropriate Institutional Review Boards. Exposure assessment In-person interviews were conducted using a computer-assisted personal interview program. Surrogates were not permitted to complete interviews on behalf of study participants but were allowed to aid in recalling occupational histories, dates and frequencies of exposures. Information on all jobs held for at least 1 year between 1941 for cases and 1946 for controls and the dates of enrolment in the study was collected. Participants reported job start and stop years, job titles and employers for every job they held since age 18. The participants were also asked to describe what the employer made or what service was provided, their main duties, and how many months per year and hours per week they worked in each job. Additionally, for 20 occupations with potential solvent exposure, job-specific questionnaires developed by an industrial hygienist were administered.35 These included questions on the work environment (eg, ventilation practices), job-specific tasks performed by the subject, chemicals used and other factors relevant to exposure assessment.36 To minimise interview time, job-specific modules were administered only when participants held the relevant job for at least 2 years. All jobs were coded according to the Standard Occupational Classification (SOC) system.37 In addition, all jobs held by each participant, regardless of whether job-specific questionnaires were used, were assessed for exposure to each of the six chlorinated solvents; a total of 2264 jobs were reviewed. Exposure metrics of probability, frequency, intensity and confidence were assigned by modifying jobeexposure matrices (JEMs) based on the subjects' answers to the work history and the job module sections of the questionnaire. The JEMs were developed by an industrial hygienist after reviewing over 600 published papers and reports on chlorinated solvents (eg, see Bakke et al38 and Gold et al39). These JEMs were developed for each decade for specific (1) industries, such as the chemical or rubber industry, (2) occupations, such as auto mechanics or hair dressers and (3) tasks, such as degreasing, gluing and painting. Exposure probability was defined as the theoretical percentage of workers reporting the same information who would have been likely to have had exposure to the solvent. Probability was scored as: 0<1% of subjects were likely to have had exposure; 11% to <10% of subjects were likely to have had exposure; 210% to <50% of subjects were likely to have had exposure; 350% to <90% of subjects were likely to have had exposure; and, 4selfreported use or $90% of subjects were likely to have had exposure. For jobs with probability scores of at least 1, frequency and intensity scores were also assigned. Frequency was defined as the average hours per week of exposure to a particular solvent, averaged over the job, and was categorised as: 0<15 min/week; 115 min to <1 h/week; 21 to 10 h/week; 3>10 to 20 h/ week; and 4>20 h/week. The intensity score was the concentration of solvent estimated to have been in the subject's breathing zone, in parts per million (ppm), during the exposure period (not necessarily for a full shift) and was coded as: 1<1 to 10 ppm; 2>10 to 100 ppm; 3>100 to 200 ppm; and 4>200 ppm. Finally, the confidence level was assigned as: 1literature contradictory or no information was available; 2one metric (probability, frequency or intensity) was based on the literature or self-report; 3two metrics were based on the literature or selfreport; and, 4all three metrics were based on the literature or directly from the subject's report. Some general rules were applied across all jobs. If the subject reported information that contradicted the appropriate JEM scores, the subject-specific data were used. If chlorinated solvent exposure was not specifically mentioned but would normally have occurred when performing reported tasks (eg, an auto mechanic reported doing tune-ups and clutch or brake work, but did not report degreasing), the subject was assessed as having been exposed and given probability, frequency and intensity scores from the JEM, but the confidence score was lowered by 1. If a subject reported working in an industry that likely involved tasks entailing chlorinated solvent exposure (eg, auto manufacturing) and the job title indicated s/he was not likely to do hands-on work in the production area, the frequency and intensity scores from the JEMs were lowered by 1. If dermal exposure was likely (eg, the subject reported degreasing with a rag), the intensity score was raised by 1. All assignments were conducted by an occupational epidemiologist (LSG) and reviewed by an industrial hygienist (PAS); both were blinded to caseecontrol status. We did not have information about non-occupational sources of chlorinated solvent exposure, such as use of glues or paints for hobbies, so we were not able to include these in each subject's cumulative solvent exposure. However, we did not expect these 392 Occup Environ Med 2011;68:391e399. doi:10.1136/oem.2009.054809 Downloaded from oem.bmj.com on May 12, 2011 - Published by group.bmj.com Original article to be major sources of chlorinated solvent exposure relative to occupational exposures. Statistical analysis We used unconditional logistic regression to estimate ORs and 95% CIs for associations between the risk of multiple myeloma and having ever been exposed (defined as a probability score of at least 2 in any job) to any of the six chlorinated solvents and to each of the six chlorinated solvents. We also analysed whether the risk of multiple myeloma varied by duration, using the summed total years worked in jobs considered exposed to each chlorinated solvent. We performed analyses examining cumulative exposure over each subject's lifetime (for each exposed job, the midpoint of intensity (in ppm)3the midpoint of frequency (in hours/week)3 total years worked, summed over all exposed jobs), again for jobs with a probability score of 2 or greater for a particular solvent. Finally, assuming multiple myeloma develops over a number of years and recent exposures are less relevant than those that took place in the more distant past, we conducted analyses in which potential exposures that occurred within 10 years of the reference date were considered unexposed. Each of the continuous exposure metrics (duration, cumulative and lagged cumulative exposure) was categorised into four groups according to quartiles of the control exposure distribution. Tests of trend were conducted using a linear term for the median duration and cumulative scores among controls in each category. The reference group in each model consisted of study participants who were assessed to have never been exposed (probability <2 in all jobs) to that particular chlorinated solvent. All models included the covariates gender, age (35e50 years (referent), 51e64 years and 65e74 years), race (only white (referent), any black, any Asian and other), education (less than 12 years (referent), 12e15 years and 16 or more years) and SEER site (Seattle and Detroit). Reported p values are two-sided and p values of <0.05 were considered to be statistically significant. As a sensitivity analysis, we considered all occupations that were given confidence scores of 1 as unexposed and repeated all analyses. Evidence has shown that the main source of nondifferential misclassification that falsely attenuates ORs towards the null is incorrect classification of unexposed individuals as exposed in population-based caseecontrol studies in which the prevalence of exposure is low. Incorrectly classifying an equal proportion of exposed individuals as unexposed has been reported not to have substantial effects on risk estimates.40e42 We also performed an additional sub-analysis with stratification by SEER site to evaluate whether the different case-to-control ratios in Seattle and Detroit influenced our results because a greater proportion of controls than cases were from Seattle and the prevalence of industries, occupations and chlorinated solvent exposures also differed by study site. For the site-stratified results, we note associations that were present in only one site. Finally, because uses of TCA, TCE, DCM and carbon tetrachloride may have been correlated, we report the percentages of control subjects exposed to these chemicals alone and to two of these chemicals and provide an estimate of the association with multiple myeloma for subjects who were exposed to all four. RESULTS One case was excluded because of missing covariate information, leaving 180 cases and 481 controls in our final study population. Cases were more likely to be male (55%) than female (45%), were frequently age 65 and older (39%), African American (28%), and most (85%) had at least 12 years of education. Overall, the distributions of sex, age, education and race were similar between cases and controls in Seattle. In Detroit, sex and education were similarly distributed between cases and controls, but cases were more likely than controls to be in the middle versus the oldest age group and were less likely to be of white race only. Among the most commonly held occupations, management and administrative occupations (SOCs 12, 13 and 14; n190 jobs reported) tended not to entail exposure to any of the chlorinated solvents, but occupations such as mechanics and repairers (SOC 61; n79 jobs reported), construction trades (SOC 64; n70 jobs reported), machine operators and tenders (SOCs 75 and 76; n128 jobs reported), fabricators, assemblers and hand working occupations (SOC 77; n85 jobs reported) and handlers, equipment cleaners and labourers (SOC 87; n84 jobs reported) generally were assessed as entailing exposure to one or more of the chlorinated solvents. Exposure to any of the six chlorinated solvents of interest was associated with a statistically significant increased risk of multiple myeloma (OR (95% CI): 1.5 (1.0 to 2.3), data not shown). Associations between exposure to each of the six chlorinated solvents and the risk of multiple myeloma are shown in tables 1e6. Risk of multiple myeloma was significantly elevated for subjects ever exposed to TCA (OR (95% CI): 1.8 (1.1 to 2.9), table 1). However, multiple myeloma risk did not increase by exposure duration or with increased cumulative exposure; in fact, the highest increased risk was observed in the second highest categories for each. Similar results were seen when jobs with low confidence scores were considered unexposed, except the highest increased risk was seen in the first exposure categories for the cumulative and lagged cumulative scores (table 1). Exposure to TCE in any job entailed elevated, but not statistically significant, risk of multiple myeloma (OR (95% CI): 1.4 (0.9 to 2.1), table 2) and this result was seen only in subjects from Detroit (data not shown). Multiple myeloma risk associated with TCE exposure showed increases in magnitude by increasing cumulative exposure and lagged cumulative exposure, although these trends were not statistically significant. When occupations that had low confidence scores were included in the unexposed category, the increased multiple myeloma risk associated with ever-exposure to TCE became statistically significant (OR (95% CI): 1.7 (1.0 to 2.7), table 2) and showed a trend of increasing risk with increasing duration of exposure in which the highest OR was seen in the third highest duration category. Increasing cumulative exposure to TCE was also associated with a statistically significant trend of increasing risk of multiple myeloma in the analysis with low confidence exposures recoded as unexposed and this trend remained when cumulative exposure scores were lagged by 10 years, with the highest risks in the highest categories. Ever-exposure to DCM was associated with elevated risk of multiple myeloma that was not statistically significant (OR (95% CI): 1.5 (0.9 to 2.3), table 3). The increased multiple myeloma risk associated with DCM exposure did not show an apparent trend by increased duration or cumulative exposure. However, when occupations that had low confidence scores were included in the unexposed category, the increased multiple myeloma risks associated with ever-exposure to DCM became statistically significant (OR (95% CI): 2.0 (1.2 to 3.2), table 3) and showed a significant trend of increasing risk with increasing duration of exposure, with the highest OR in the third highest duration category. In these analyses with jobs given low confidence scores considered unexposed, there was no trend of risk with increasing cumulative or lagged cumulative exposure (table 3). Occup Environ Med 2011;68:391e399. doi:10.1136/oem.2009.054809 393 Original article Downloaded from oem.bmj.com on May 12, 2011 - Published by group.bmj.com Table 1 ORs* and 95% CIs for multiple myeloma and occupational exposure to 1,1,1-trichloroethane (TCA) Primary analysis Reanalysis: jobs assessed with low confidence considered unexposed Controls (n[481) Cases (n[180) OR (95% CI) Controls (n[481) Cases (n[180) OR (95% CI) Ever exposedy Duration Unexposed 1e3 years 4e8 years 9e21 years 22e45 years 65 (14%) 416 (86%) 16 (3.3%) 16 (3.3%) 15 (3.1%) 18 (3.7%) Cumulative exposurez x Unexposed 416 (86%) 1e53 17 (3.5%) 54e605 16 (3.3%) 606e3750 16 (3.3%) 3751e57000 16 (3.3%) 10-Year lagged cumulative exposurez x Unexposed 417 (87%) 1e49 16 (3.3%) 50e342 16 (3.3%) 343e2781 16 (3.3%) 2782e49500 16 (3.3%) 36 (20%) 144 (80%) 7 (3.9%) 11 (6.1%) 11 (6.1%) 7 (3.9%) 144 (80%) 7 (3.9%) 10 (5.6%) 8 (4.4%) 11 (6.1%) 147 (82%) 7 (3.9%) 7 (3.9%) 8 (4.4%) 11 (6.1%) 1.8 (1.1 to 2.9) Referent 1.6 (0.6 to 4.3) 2.3 (1.0 to 5.3) 1.9 (0.8 to 4.5) 1.3 (0.5 to 3.3) p Trend 0.17 Referent 1.7 (0.7 to 4.4) 2.2 (0.9 to 5.3) 1.4 (0.5 to 3.4) 1.9 (0.8 to 4.4) p Trend 0.19 Referent 1.8 (0.7 to 4.6) 1.5 (0.6 to 3.3) 1.3 (0.5 to 3.3) 1.8 (0.8 to 4.1) p Trend 0.21 Ever exposedy Duration Unexposed 1e5 years 6e16 years 17e25 years 26e45 years 23 (4.8%) 458 (95%) 9 (1.8%) 3 (0.6%) 7 (1.5%) 4 (0.8%) Cumulative exposurez x Unexposed 458 (95%) 1e378 5 (1.0%) 379e1938 6 (1.3%) 1939e10012 6 (1.3%) 10013e57000 6 (1.3%) 10-Year lagged cumulative exposurez x Unexposed 459 (95%) 1e303 6 (1.3%) 304e1690 5 (1.0%) 1691e4500 6 (1.3%) 4501e49500 5 (1.0%) 17 (9.4%) 163 (91%) 5 (2.8%) 6 (3.3%) 4 (2.2%) 2 (1.1%) 163 (91%) 5 (2.8%) 2 (1.1%) 6 (3.3%) 4 (2.2%) 164 (91%) 5 (2.8%) 0 5 (2.8%) 6 (3.3%) 2.2 (1.1 to 4.4) Referent 1.8 (0.6 to 5.7) 6.7 (1.5 to 29) 1.6 (0.4 to 6.0) 1.3 (0.2 to 7.4) p Trend 0.27 Referent 3.7 (1.0 to 13) 1.1 (0.2 to 5.8) 3.0 (0.9 to 10) 1.5 (0.4 to 5.8) p Trend 0.33 Referent 3.1 (0.9 to 11) NA 2.3 (0.6 to 8.0) 2.8 (0.8 to 9.9) p Trend 0.07 *All models adjusted for age, race, study site, gender and years of education. yEver exposed defined as having at least one job with a probability score of 2 for exposure to TCA and all jobs with a probability score of <2 were considered as unexposed. zSome participants were unexposed in the cumulative scores but not the ever/never and duration analyses because they were exposed for <15 min per week and therefore had a frequency of 0. xCumulative score calculated by multiplying the midpoint of the intensity (in ppm) by the midpoint of the frequency (in hours/week) by the number of years worked in each exposed job. Subjects ever-exposed to PCE were at slightly elevated, but not statistically significant, risk of multiple myeloma when the low confidence assessments were considered either exposed (OR (95% CI): 1.4 (0.9 to 2.4)) or unexposed (OR (95% CI): 1.5 (0.8 to 2.9), table 4). Trends of increasing risk with increasing duration of exposure were not statistically significant, but we did Table 2 ORs* and 95% CIs for multiple myeloma and occupational exposure to trichloroethylene (TCE) Primary analysis Reanalysis: jobs assessed with low confidence considered unexposed Controls (n[481) Cases (n[180) OR (95% CI) Controls (n[481) Cases (n[180) OR (95% CI) Ever exposedy Duration Unexposed 1e4 years 5e11 years 12e29 years 30e51 years 138 (29%) 343 (71%) 32 (6.7%) 35 (7.3%) 36 (7.5%) 35 (7.3%) Cumulative exposurez x Unexposed 345 (72%) 1e318 35 (7.3%) 319e2218 33 (6.9%) 2219e7793 34 (7.1%) 7794e57000 34 (7.1%) 10-Year lagged cumulative exposurez x Unexposed 345 (72%) 1e311 34 (7.1%) 312e2089 34 (7.1%) 2090e7285 34 (7.1%) 7286e50000 34 (7.1%) 66 (37%) 114 (63%) 13 (7.2%) 16 (8.9%) 23 (13%) 14 (7.8%) 116 (64%) 15 (8.3%) 11 (6.1%) 14 (7.8%) 24 (13%) 116 (64%) 16 (8.9%) 11 (6.1%) 12 (6.7%) 25 (14%) 1.4 (0.9 to 2.1) Referent 1.4 (0.7 to 3.0) 1.3 (0.6 to 2.5) 1.5 (0.8 to 2.8) 1.2 (0.6 to 2.6) p Trend 0.41 Referent 1.3 (0.7 to 2.6) 1.0 (0.4 to 2.1) 1.3 (0.6 to 2.6) 1.7 (0.9 to 3.3) p Trend 0.10 Referent 1.4 (0.7 to 2.8) 0.9 (0.4 to 2.0) 1.1 (0.5 to 2.4) 1.8 (0.9 to 3.4) p Trend 0.08 Ever exposedy Duration Unexposed 1e4 years 5e7 years 8e24 years 25e47 years 75 (16%) 406 (84%) 23 (4.8%) 15 (3.1%) 19 (4.0%) 18 (3.7%) Cumulative exposurez x Unexposed 409 (85%) 1e471 18 (3.7%) 472e3000 20 (4.2%) 3001e7644 16 (3.3%) 7645e57000 18 (3.7%) 10-Year lagged cumulative exposurez x Unexposed 409 (85%) 1e415 18 (3.7%) 416e3000 20 (4.2%) 3001e6592 16 (3.3%) 6593e49500 18 (3.7%) 43 (24%) 137 (76%) 6 (3.3%) 6 (3.3%) 20 (11%) 11 (6.1%) 139 (77%) 6 (3.3%) 11 (6.1%) 7 (3.9%) 17 (9.4%) 139 (77%) 6 (3.3%) 11 (6.1%) 6 (3.3%) 18 (10%) 1.7 (1.0 to 2.7) Referent 0.9 (0.3 to 2.4) 1.3 (0.5 to 3.6) 2.5 (1.2 to 5.1) 1.9 (0.8 to 4.5) p Trend 0.04 Referent 1.1 (0.4 to 2.9) 1.6 (0.7 to 3.5) 1.5 (0.6 to 3.9) 2.3 (1.1 to 5.0) p Trend 0.03 Referent 1.1 (0.4 to 2.9) 1.6 (0.7 to 3.5) 1.4 (0.5 to 3.8) 2.3 (1.1 to 5.0) p Trend 0.02 *All models adjusted for age, race, study site, gender and years of education. yEver exposed defined as having at least one job with a probability score of 2 for exposure to TCE and all jobs with a probability score of <2 were considered as unexposed. zSome participants were unexposed in the cumulative scores but not the ever/never and duration analyses because they were exposed for <15 min per week and therefore had a frequency of 0. xCumulative score calculated by multiplying the midpoint of the intensity (in ppm) by the midpoint of the frequency (in hours/week) by the number of years worked in each exposed job. 394 Occup Environ Med 2011;68:391e399. doi:10.1136/oem.2009.054809 Occup Environ Med 2011;68:391e399. doi:10.1136/oem.2009.054809 Downloaded from oem.bmj.com on May 12, 2011 - Published by group.bmj.com Table 3 ORs* and 95% CIs for multiple myeloma and occupational exposure to methylene chloride (DCM) Primary analysis Controls (n[481) Cases (n[180) OR (95% CI) Reanalysis: jobs assessed with low confidence considered unexposed Controls (n[481) Cases (n[180) OR (95% CI) Ever exposedy Duration Unexposed 1e4 years 5e11 years 12e29 years 30e51 years 91 (19%) 390 (81%) 22 (4.6%) 19 (4.0%) 26 (5.4%) 24 (5.0%) Cumulative exposurez x Unexposed 1e318 319e2218 2219e7793 7794e57000 392 (82%) 22 (4.6%) 22 (4.6%) 23 (4.8%) 22 (4.6%) 10-Year lagged cumulative exposurez x Unexposed 398 (83%) 1e311 21 (4.4%) 312e2089 20 (4.2%) 2090e7285 22 (4.6%) 7286e50000 20 (4.2%) 47 (26%) 133 (74%) 9 (5.0%) 11 (6.1%) 17 (9.4%) 10 (5.6%) 135 (75%) 7 (3.9%) 17 (9.4%) 7 (3.9%) 14 (7.8%) 138 (77%) 8 (4.4%) 12 (6.7%) 10 (5.6%) 12 (6.7%) 1.5 (0.9 to 2.3) Referent 1.2 (0.5 to 2.9) 1.8 (0.8 to 4.1) 1.8 (0.9 to 3.5) 1.1 (0.5 to 2.6) p Trend 0.35 Referent 1.2 (0.5 to 2.9) 2.2 (1.1 to 4.6) 0.8 (0.3 to 1.9) 1.6 (0.8 to 3.4) p Trend 0.27 Referent 1.4 (0.6 to 3.3) 1.6 (0.7 to 3.6) 1.2 (0.5 to 2.8) 1.5 (0.7 to 3.2) p Trend 0.39 Ever exposedy Duration Unexposed 1e4 years 5e7 years 8e24 years 25e47 years 54 (11%) 427 (89%) 15 (3.1%) 15 (3.1%) 11 (2.3%) 13 (2.7%) Cumulative exposurez x Unexposed 1e102 103e1122 1123e5493 5494e57000 430 (89%) 12 (2.5%) 14 (2.9%) 13 (2.7%) 12 (2.5%) 10-Year lagged cumulative exposurez x Unexposed 437 (91%) 1e71 11 (2.3%) 72e437 11 (2.3%) 438e3903 11 (2.3%) 3904e49500 11 (2.3%) 37 (21%) 143 (79%) 8 (4.4%) 6 (3.3%) 13 (7.2%) 10 (5.6%) 144 (80%) 5 (2.8%) 13 (7.2%) 8 (4.4%) 10 (5.6%) 147 (82%) 4 (2.2%) 10 (5.6%) 9 (5.0%) 10 (5.6%) 2.0 (1.2 to 3.2) Referent 2.0 (0.8 to 5.1) 1.1 (0.4 to 3.1) 2.7 (1.1 to 6.5) 2.1 (0.9 to 5.2) p Trend 0.01 Referent 1.6 (0.5 to 4.7) 2.8 (1.2 to 6.6) 1.6 (0.6 to 3.8) 2.4 (1.0 to 5.9) p Trend 0.08 Referent 1.3 (0.4e4.4) 2.9 (1.1e7.5) 1.9 (0.7e5.0) 2.4 (1.0e6.1) p Trend 0.06 *All models adjusted for age, race, study site, gender and years of education. yEver exposed defined as having at least one job with a probability score of 2 for exposure to DCM and all jobs with a probability score of <2 were considered as unexposed. zSome participants were unexposed in the cumulative scores but not the ever/never and duration analyses because they were exposed for <15 min per week and therefore had a frequency of 0. xCumulative score calculated by multiplying the midpoint of the intensity (in ppm) by the midpoint of the frequency (in hours/week) by the number of years worked in each exposed job. Original article 395 Original article Downloaded from oem.bmj.com on May 12, 2011 - Published by group.bmj.com Table 4 ORs* and 95% CIs for multiple myeloma and occupational exposure to perchloroethylene (PCE) Primary analysis Reanalysis: jobs assessed with low confidence considered unexposed Controls (n[481) Cases (n[180) OR (95% CI) Controls (n[481) Cases (n[180) OR (95% CI) Ever exposedy Duration Unexposed 1e4 years 5e11 years 12e29 years 30e51 years 63 (13%) 418 (87%) 19 (4.0%) 14 (2.9%) 13 (2.7%) 17 (3.5%) Cumulative exposurez x Unexposed 419 (87%) 1e318 319e2218 2219e7793 7794e57000 16 (3.3%) 15 (3.1%) 16 (3.3%) 15 (3.1%) 10-Year lagged cumulative exposurez x Unexposed 424 (88%) 1e311 13 (2.7%) 312e2089 17 (3.5%) 2090e7285 13 (2.7%) 7286e50000 14 (2.9%) 29 (16%) 151 (84%) 4 (2.2%) 8 (4.4%) 8 (4.4%) 9 (5.0%) 151 (84%) 5 (2.8%) 6 (3.3%) 4 (2.2%) 14 (7.8%) 154 (86%) 4 (2.2%) 4 (2.2%) 5 (2.8%) 13 (7.2%) 1.4 (0.9 to 2.4) Referent 0.8 (0.3 to 2.5) 1.9 (0.8 to 4.9) 1.5 (0.6 to 3.9) 1.6 (0.7 to 3.9) p Trend 0.20 Referent 1.3 (0.4 to 3.8) 1.4 (0.5 to 3.8) 0.7 (0.2 to 2.1) 2.5 (1.1 to 5.4) p Trend 0.04 Referent 1.2 (0.4 to 3.8) 0.7 (0.2 to 2.3) 1.1 (0.4 to 3.3) 2.5 (1.1 to 5.6) p Trend 0.03 Ever exposedy Duration Unexposed 1e4 years 5e7 years 8e24 years 25e47 years 28 (5.8%) 453 (94%) 9 (1.9%) 5 (1.0%) 7 (1.5%) 7 (1.5%) Cumulative exposurez x Unexposed 453 (94%) 1e353 354e1430 1431e4875 4876e13500 7 (1.5%) 7 (1.5%) 7 (1.5%) 7 (1.5%) 10-Year lagged cumulative exposurez x Unexposed 457 (95%) 1e194 195e1586 1587e4875 4876e13500 6 (1.3%) 6 (1.3%) 6 (1.3%) 6 (1.3%) 16 (8.9%) 164 (91%) 3 (1.7%) 3 (1.7%) 4 (2.2%) 6 (3.3%) 164 (91%) 1 (0.6%) 1 (0.6%) 4 (2.2%) 10 (5.6%) 164 (91%) 1 (0.6%) 1 (0.6%) 4 (2.2%) 10 (5.6%) 1.5 (0.8 to 2.9) Referent 0.9 (0.2 to 3.5) 2.0 (0.4 to 9.2) 1.3 (0.3 to 4.6) 2.1 (0.7 to 6.8) p Trend 0.18 Referent 0.3 (0.04 to 3.0) 0.5 (0.1 to 4.4) 1.5 (0.4 to 5.4) 3.3 (1.2 to 9.5) p Trend 0.02 Referent 0.4 (0.04 to 3.2) 0.5 (0.1 to 4.7) 1.7 (0.5 to 6.5) 4.1 (1.4 to 12) p Trend 0.01 *All models adjusted for age, race, study site, gender and years of education. yEver exposed defined as having at least one job with a probability score of 2 for exposure to PCE and all jobs with a probability score of <2 were considered as unexposed. zSome participants were unexposed in the cumulative scores but not the ever/never and duration analyses because they were exposed for <15 min per week and therefore had a frequency of 0. xCumulative score calculated by multiplying the midpoint of the intensity (in ppm) by the midpoint of the frequency (in hours/week) by the number of years worked in each exposed job. observe statistically significant trends for increasing cumulative and lagged cumulative exposure both when the low confidence occupations were considered exposed and unexposed. In all cumulative exposure analyses of PCE, the highest ORs were seen in the highest exposure categories (table 4). Exposure to carbon tetrachloride was not associated with an increased risk of multiple myeloma when jobs with low confidence scores were included among the exposed (OR (95% CI): 1.1 (0.7 to 1.8), table 5), but when these jobs were included among the unexposed, we observed a non-statistically significant increase in risk of multiple myeloma (OR (95% CI): 1.6 (0.8 to 3.0)) and a trend of significantly increased risk with increasing duration of exposure that was only observed among Seattle participants (data not shown). We did not observe trends of increased risk with increasing cumulative or lagged cumulative exposure to carbon tetrachloride. We did not observe an increased risk of multiple myeloma with exposure to chloroform when jobs with low confidence scores were considered exposed (OR (95% CI): 1.4 (0.7 to 2.8), table 6). However, exposure to chloroform was associated with elevated, but not statistically significant, risk of multiple myeloma when subjects with low confidence were considered unexposed (OR (95% CI): 2.5 (0.8 to 7.6), table 6). We did not observe significant trends with increased duration or cumulative exposure to chloroform when jobs with low confidence scores were considered exposed or unexposed, but the highest ORs were in the highest exposed categories in these analyses. However, few subjects were assessed as exposed to chloroform (n41) and we were not able to examine site-specific trends. Finally, we found that 16% of controls were exposed to both TCE and carbon tetrachloride (13% were exposed to TCE but not carbon tetrachloride; 2.5% were exposed to carbon tetrachloride but not TCE); 13% of controls were exposed to both TCE and DCM (16% were exposed to TCE but not DCM; 6.2% were exposed to DCM but not TCE); 11% of controls were exposed to TCA and TCA (17% were exposed to TCE but not TCA; 2.1% were exposed to TCA but not TCE); 9.1% of controls were exposed to carbon tetrachloride and DCM (9.1% were exposed to carbon tetrachloride but not DCM; 9.8% were exposed to DCM but not carbon tetrachloride); 11% were exposed to DCM and TCA (2.5% were exposed to TCA but not DCM; 7.9% were exposed to DCM but not TCA); 6.7% were exposed to carbon tetrachloride and TCA (12% were exposed to carbon tetrachloride but not TCA; 6.9% were exposed to TCA but not carbon tetrachloride). Ever exposure to TCE, TCA, DCM and carbon tetrachloride was non-significantly associated with increased risk of multiple myeloma (OR (95% CI): 1.7 (0.8 to 3.5), data not shown). DISCUSSION Evidence from this relatively large caseecontrol study suggests that exposures to certain chlorinated solvents were associated with increased incidence of multiple myeloma. We observed elevated risk estimates for each of the six chlorinated solvents we examined; however, increased risks were not always statistically significant and we did not always observe linear exposureeresponse patterns. The most consistent results were observed for TCE, with multiple myeloma risk increasing with greater exposure when low confidence exposure assignments were considered unexposed. We also observed elevated risks for multiple myeloma from exposure to TCA, DCM and PCE; however, all showed non-linear exposureeresponse gradients, in which the highest risks were associated with moderate, rather than high, exposure in at least one analysis. While a non-linear doseeresponse is biologically possible, the more traditional expectation is that risks rise with increasing levels of exposure. Exposure to carbon tetrachloride was associated with elevated, but usually not statistically significant, increased risk of multiple myeloma, with a significant trend of 396 Occup Environ Med 2011;68:391e399. doi:10.1136/oem.2009.054809 Downloaded from oem.bmj.com on May 12, 2011 - Published by group.bmj.com Original article Table 5 ORs* and 95% CIs for multiple myeloma and occupational exposure to carbon tetrachloride Primary analysis Reanalysis: jobs assessed with low confidence considered unexposed Controls (n[481) Cases (n[180) OR (95% CI) Controls (n[481) Cases (n[180) OR (95% CI) Ever exposedy Duration Unexposed 1e2 years 3e4 years 5e11 years 12e44 years 88 (18%) 393 (82%) 14 (2.9%) 26 (5.4%) 26 (5.4%) 22 (4.6%) Cumulative exposurez x Unexposed 399 (83%) 1e204 205e1280 1281e3750 3751e48000 20 (4.2%) 21 (4.4%) 24 (5.0%) 17 (3.5%) 10-Year lagged cumulative exposurez x Unexposed 399 (83%) 1e204 20 (4.2%) 205e1280 21 (4.4%) 1281e3750 24 (5.0%) 3751e48000 17 (3.5%) 33 (18%) 147 (82%) 1 (0.6%) 6 (3.3%) 16 (8.9%) 10 (5.6%) 148 (82%) 8 (4.4%) 5 (2.8%) 7 (3.9%) 12 (6.7%) 148 (82%) 9 (5.0%) 5 (2.8%) 7 (3.9%) 11 (6.1%) 1.1 (0.7 to 1.8) Referent 0.2 (0.03 to 1.9) 0.7 (0.3 to 1.7) 1.7 (0.8 to 3.5) 1.4 (0.6 to 3.2) p Trend 0.30 Referent 1.4 (0.6 to 3.4) 0.7 (0.2 to 1.9) 0.8 (0.3 to 2.1) 1.9 (0.8 to 4.4) p Trend 0.16 Referent 1.6 (0.7 to 3.9) 0.7 (0.2 to 1.8) 0.8 (0.3 to 2.1) 1.7 (0.7 to 4.1) p Trend 0.29 Ever exposedy Duration Unexposed 1e4 years 5e7 years 8e24 years 25e42 years 37 (7.7%) 444 (92%) 18 (3.7%) 5 (1.0%) 10 (2.1%) 4 (0.8%) Cumulative exposurez x Unexposed 449 (93%) 1e215 216e1500 1501e5625 5626e48000 8 (1.7%) 9 (1.9%) 7 (1.5%) 8 (1.7%) 10-Year lagged cumulative exposurez x Unexposed 449 (93%) 1e215 216e1500 1501e5625 5626e48000 8 (1.7%) 9 (1.9%) 7 (1.5%) 8 (1.7%) 17 (9.4%) 163 (91%) 4 (2.2%) 3 (1.7%) 4 (2.2%) 6 (3.3%) 164 (91%) 2 (1.1%) 4 (2.2%) 6 (3.3%) 4 (2.2%) 164 (91%) 3 (1.7%) 4 (2.2%) 5 (2.8%) 4 (2.2%) 1.6 (0.8 to 3.0) Referent 0.8 (0.3 to 2.6) 1.7 (0.4 to 7.6) 1.1 (0.3 to 4.0) 6.9 (1.8 to 27) p Trend 0.01 Referent 0.9 (0.2 to 4.6) 1.5 (0.4 to 5.1) 3.2 (1.0 to 10) 1.3 (0.4 to 4.7) p Trend 0.51 Referent 1.5 (0.4 to 5.9) 1.4 (0.4 to 4.9) 2.6 (0.8 to 8.8) 1.3 (0.4 to 4.7) p Trend 0.52 *All models adjusted for age, race, study site, gender and years of education. yEver exposed defined as having at least one job with a probability score of 2 for exposure to carbon tetrachloride and all jobs with a probability score of <2 were considered as unexposed. zSome participants were unexposed in the cumulative scores but not the ever/never and duration analyses because they were exposed for <15 min per week and therefore had a frequency of 0. xCumulative score calculated by multiplying the midpoint of the intensity (in ppm) by the midpoint of the frequency (in hours/week) by the number of years worked in each exposed job. increasing risk with greater duration of exposure when low confidence exposure assignments were considered unexposed. We also observed a suggestion that exposure to chloroform was associated with increased multiple myeloma risk; however, few subjects in our study were exposed to chloroform. The most common task that entailed exposure to TCA, TCE and carbon tetrachloride was degreasing of metal parts. Many of the subjects who were considered as having been possibly exposure to these chemicals through degreasing were machine operators and were employed at automotive manufacturing companies in Detroit and at aircraft manufacturing companies and in the military in Seattle. Workers at auto plants in Detroit and at aeroplane plants in Seattle who were involved in finishing tasks such as packaging were assessed as possibly exposed to TCA and TCE through glues. Janitors and custodians were considered to have been possibly exposed to TCE through the use of furniture polishing and floor-stripping products. Possible exposure to DCM and PCE likely occurred most often through the use of glues. In Detroit, subjects who worked at automotive manufacturing companies were assessed to have possibly used glues on assembly lines or when packaging products, whereas in Seattle, glues were more often associated with aircraft manufacturing companies and tyre repair at service stations. Another commonly assessed source of possible exposure to DCM and PCE was degreasing in car garages and in aircraft manufacturing plants. Janitors and cleaners were considered to have been exposed to DCM through the use of cleaning products. Although a less common source of PCE exposure than glues, work in the dry cleaning industry was associated with high intensity PCE exposure. Although previous studies have not examined exposure to chlorinated solvents and multiple myeloma specifically, associations between occupations that might entail exposure to chlorinated solvents and multiple myeloma have been noted. A meta-analysis of associations between chemical workers and many types of cancer found these workers were at significantly increased risk of multiple myeloma (meta-standardised incidence ratio (95% CI): 2.2 (1.3 to 3.8)),2 but particular exposures that these workers had that may have led to multiple myeloma were not clear from this study. Many studies have found that occu- pation in agriculture was associated with increased risk of multiple myeloma,12 but these jobs tended to include exposure to many potentially carcinogenic substances, and specific exposures that might increase risk of multiple myeloma have not been identified. One mechanism through which chlorinated solvents may induce cancer is by damaging or altering DNA. TCE and carbon tetrachloride have been shown to form DNA adducts and mutations in brain, testis, pancreas, kidney, liver, lung and spleen cells in rodents.43 44 DNA hypomethylation of proto- oncogenes, which is hypothesised to precede several types of cancer,45 has also been associated with exposure to TCE45 and chloroform.46 Solvents can also affect the immune system, which may be relevant since multiple myeloma is increased in patients expe- riencing immune system dysregulation, such as patients with HIV,47e49 certain autoimmune diseases50 and organ transplants.51 52 Suppressed immunity may lead to susceptibility to viruses that could potentially cause cytogenetic trans- formations, leading to multiple myeloma. Stimulated immunity is associated with proliferation of plasma cells, which could in turn increase errors in DNA replication that may lead to multiple myeloma. Another hypothesis is that the breakdown of immunological responses may compromise the ability of T cells to eliminate cancer-causing cells.53 Long-term exposure to occupationally relevant levels of TCE in air has been shown to Occup Environ Med 2011;68:391e399. doi:10.1136/oem.2009.054809 397 Original article Downloaded from oem.bmj.com on May 12, 2011 - Published by group.bmj.com Table 6 ORs* and 95% CIs for multiple myeloma and occupational exposure to chloroform Primary analysis Controls (n[481) Cases (n[180) OR (95% CI) Reanalysis: jobs assessed with low confidence considered unexposed Controls (n[481) Cases (n[180) OR (95% CI) Ever exposedy Duration Unexposed 1e4 years 5e7 years 8e17 years 18e45 years 27 (5.6%) 454 (94%) 9 (1.9%) 6 (1.3%) 6 (1.3%) 6 (1.3%) Cumulative exposurez x Unexposed 454 (94%) 1e18 6 (1.3%) 19e204 7 (1.5%) 205e3223 8 (1.7%) 3224e57106 6 (1.3%) 10-Year lagged cumulative exposurez x Unexposed 455 (95%) 1e21 7 (1.5%) 22e204 5 (1.0%) 205e3223 8 (1.7%) 3224e54000 6 (1.3%) 14 (7.8%) 166 (92%) 2 (1.1%) 3 (1.7%) 4 (2.2%) 5 (2.8%) 167 (93%) 3 (1.7%) 2 (1.1%) 2 (1.1%) 6 (3.3%) 167 (93%) 4 (2.2%) 1 (0.6$) 2 (1.1%) 6 (3.3%) 1.4 (0.7 to 2.8) Referent 0.4 (0.1 to 2.2) 1.8 (0.4 to 7.7) 2.0 (0.5 to 8.0) 2.1 (0.6 to 7.4) p Trend 0.16 Referent 1.7 (0.4 to 7.2) 0.9 (0.2 to 4.8) 0.5 (0.1 to 2.4) 2.6 (0.8 to 9.2) p Trend 0.12 Referent 2.4 (0.7 to 8.9) 0.5 (0.1 to 4.8) 0.5 (0.1 to 2.4) 2.7 (0.8 to 9.3) p Trend 0.12 Ever exposedy Duration Unexposed 1e3 years 4e10 years 11e17 years 18e40 years 6 (1.3%) 475 (99%) 2 (0.4%) 1 (0.2%) 2 (0.4%) 1 (0.2%) Cumulative exposurez x Unexposed 475 (99%) 1e204 1 (0.2%) 205e1908 2 (0.4%) 1909e12750 2 (0.4%) 12751e49500 1 (0.2%) 10-Year lagged cumulative exposurez x Unexposed 475 (99%) 1e204 1 (0.2%) 205e1627 2 (0.4%) 1628e4500 2 (0.4%) 4501e49500 1 (0.2%) 7 (3.9%) 173 (96%) 0 2 (1.1%) 1 (0.6%) 4 (2.2%) 174 (97%) 2 (1.1%) 0 1 (0.6%) 3 (1.7%) 174 (97%) 2 (1.1%) 0 1 (0.6%) 3 (1.7%) 2.5 (0.8 to 7.6) Referent NA 4.5 (0.4 to 53) 1.2 (0.1 to 14) 7.5 (0.8 to 72) p Trend 0.09 Referent 4.1 (0.4 to 47) NA 0.9 (0.1 to 11) 7.7 (0.8 to 79) p Trend 0.11 Referent 4.1 (0.4 to 47) NA 0.9 (0.1 to 11) 7.9 (0.8 to 82) p Trend 0.09 *All models adjusted for age, race, study site, gender and years of education. yEver exposed defined as having at least one job with a probability score of 2 for exposure to chloroform and all jobs with a probability score of <2 were considered as unexposed. zSome participants were unexposed in the cumulative scores but not the ever/never and duration analyses because they were exposed for <15 min per week and therefore had a frequency of 0. xCumulative score calculated by multiplying the midpoint of the intensity (in ppm) by the midpoint of the frequency (in hours/week) by the number of years worked in each exposed job. lead to greater numbers of activated CD4+ T cells, and higher levels of markers of increased immune response were significant at lower (0.1 and 0.5 mg/ml), but not higher (2.5 mg/ml) doses of TCE,54 which suggests that carcinogenesis that is preceded by stimulated immunity may not follow a typical exposureeresponse pattern. These studies suggest that immune alterations may lie on the aetiological pathway between chlorinated solvent exposure and the development of multiple myeloma, but further research is necessary. This study was the first caseecontrol study to analyse exposure to these six chlorinated solvents in relation to incidence of multiple myeloma. The use of detailed occupational information improved assessment of solvent exposure compared to analyses based solely on job titles. However, our study had several weaknesses. Even with the additional efforts undertaken to improve exposure assessment, exposure misclassification likely occurred. Also, participation rates were relatively low among cases and controls. Although case participation was not associated with age, sex or study site, control participation did vary by age category. We were not able to assess whether non-participants were similar to participants in terms of race or socioeconomic status, which are tied to occupation and, potentially, solvent exposure. This might have resulted in selection bias if, for example, controls in certain types of jobs with likely solvent exposure were less likely to have participated in our study than cases in those jobs, although we observed no evidence that this occurred. Although every effort was made to contact multiple myeloma patients within 1e2 months of diagnosis, a substantial proportion of cases (18%) died before they could be contacted and 29% of those we did contact refused to participate, possibly because they were too ill. Our findings, therefore, might reflect relationships between chlorinated solvents and less aggressive forms of multiple myeloma. In addition, we cannot rule out the possibility of recall bias affecting our results. However, this bias was likely minimised since the questions in the job-specific questionnaires focused on job tasks rather than specific chemical exposures. Small numbers of participants exposed to certain chlorinated solvents increased the possibility of false positive and false negative chance findings and the potential impact that misclassification could have had on the associations. In addition, the possibility of false associations was increased by the number of associations we examined. Also, concomitant exposures likely occurred in many of the occupations that entailed exposure to chlorinated solvents, so we cannot rule out the possibility that these confounded the relationship between chlorinated solvent exposure and the risk of multiple myeloma. However, it is unlikely that these other exposures were so highly correlated with chlorinated solvent exposure that they caused substantial degrees of confounding.55 Finally, another limitation of our findings is that assignments of some of the chlorinated solvents were likely correlated, especially TCE, DCM, TCA and carbon tetrachloride, which were commonly used as degreasers. In many situations, we were not able to determine which specific chlorinated solvent was used. We attempted to overcome this challenge by assigning probabilities of exposure, based on published information on the probability that that given solvent was being used in a particular decade.38 39 However, it is still likely that the correlation of assignments led to some misclassification of exposure. Therefore, it is possible that not all of the solvents we examined are truly involved in multiple myeloma aetiology, but instead appeared to be associated with multiple myeloma because their uses and exposure assignments were correlated. In summary, this research provides some evidence that certain chlorinated solventsdnotably TCEdare associated with increased incidence of multiple myeloma. While results were less clear, exposure to TCA, DCM, PCE, carbon tetrachloride and chloroform may also confer increased risk of multiple myeloma. 398 Occup Environ Med 2011;68:391e399. doi:10.1136/oem.2009.054809 Downloaded from oem.bmj.com on May 12, 2011 - Published by group.bmj.com Original article In order to establish causality, larger studies including more multiple myeloma cases should be undertaken. 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Occup Environ Med 2011 68: 391-399 originally published online September 10, 2010 doi: 10.1136/oem.2009.054809 Updated information and services can be found at: http://oem.bmj.com/content/68/6/391.full.html References Email alerting service These include: This article cites 53 articles, 16 of which can be accessed free at: http://oem.bmj.com/content/68/6/391.full.html#ref-list-1 Receive free email alerts when new articles cite this article. Sign up in the box at the top right corner of the online article. Notes To request permissions go to: http://group.bmj.com/group/rights-licensing/permissions To order reprints go to: http://journals.bmj.com/cgi/reprintform To subscribe to BMJ go to: http://group.bmj.com/subscribe/