A pooled analysis of cigarette smoking and risk of multiple myeloma from the international multiple myeloma consortium.

BACKGROUND: Past investigations of cigarette smoking and multiple myeloma have been underpowered to detect moderate associations, particularly within subgroups. To clarify this association, we conducted a pooled analysis of nine case-control studies in the International Multiple Myeloma Consortium, with individual-level questionnaire data on cigarette smoking history and other covariates. METHODS: Using a pooled population of 2,670 cases and 11,913 controls, we computed odds ratios (OR) and 95% confidence intervals (CI) relating smoking to multiple myeloma risk using unconditional logistic regression adjusting for gender, age group, race, education, body mass index, alcohol consumption, and study center. RESULTS: Neither ever smokers (OR, 0.95; 95% CI, 0.87-1.05), current smokers (OR, 0.82; 95% CI, 0.73-0.93), nor former smokers (OR, 1.03; 95% CI, 0.92-1.14) had increased risks of multiple myeloma compared with never smokers. Analyses of smoking frequency, pack-years, and duration did not reveal significant or consistent patterns, and there was no significant effect modification by subgroups. CONCLUSION: Findings from this large pooled analysis do not support the hypothesis of cigarette smoking as a causal factor for multiple myeloma. IMPACT: Cigarette smoking is one of the most important risk factors for cancer, but the association with multiple myeloma was inconclusive. This study had excellent power to detect modest associations, and had individual-level data to evaluate confounding and effect modification by potentially important factors that were not evaluated in previous studies. Our findings confirm that smoking is not a risk factor for multiple myeloma. Cancer Epidemiol Biomarkers Prev; 24(3); 631-4. ©2014 AACR.

A pooled analysis of alcohol consumption and risk of multiple myeloma in the international multiple myeloma consortium.

BACKGROUND: Recent findings suggest that alcohol consumption may reduce risk of multiple myeloma. METHODS: To better understand this relationship, we conducted an analysis of six case-control studies participating in the International Multiple Myeloma Consortium (1,567 cases, 7,296 controls). Summary ORs and 95% confidence intervals (CI) relating different measures of alcohol consumption and multiple myeloma risk were computed by unconditional logistic regression with adjustment for age, race, and study center. RESULTS: Cases were significantly less likely than controls to report ever drinking alcohol (men: OR = 0.72; 95% CI, 0.59-0.89; women: OR = 0.81; 95% CI, 0.68-0.95). The inverse association with multiple myeloma was stronger when comparing current to never drinkers (men: OR = 0.57; 95% CI, 0.45-0.72; women: OR = 0.55; 95% CI, 0.45-0.68), but null among former drinkers. We did not observe an exposure-response relationship with increasing alcohol frequency, duration, or cumulative lifetime consumption. Additional adjustment for body mass index, education, or smoking did not affect our results; and the patterns of association were similar for each type of alcohol beverage examined. CONCLUSIONS: Our study is, to our knowledge, the largest of its kind to date, and our findings suggest that alcohol consumption may be associated with reduced risk of multiple myeloma. IMPACT: Prospective studies, especially those conducted as pooled analyses with large sample sizes, are needed to confirm our findings and further explore whether alcohol consumption provides true biologic protection against this rare, highly fatal malignancy.

The relationship between multiple myeloma and occupational exposure to six chlorinated solvents.

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 case-control 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.

Occupation and multiple myeloma: an occupation and industry analysis.

BACKGROUND: Multiple myeloma (MM) is an incurable plasma cell malignancy with a poorly understood etiology. The purpose of our research was to examine the relationships between lifetime occupations and MM in a relatively large case-control study. METHODS: MM cases (n = 180) were identified through cancer registries in the Seattle-Puget Sound area and Detroit. Population-based controls (n = 481) were identified using random digit dialing and Medicare and Medicaid Services files. In-person interviews were conducted to ascertain occupational histories. Standard occupational classification (SOC) and standard industrial classification (SIC) codes were assigned to each job held by each participant. Unconditional logistic regression was used to generate odds ratios (ORs) and 95% confidence intervals (CIs) for associations between MM and having ever worked in each occupation/industry and according to duration of employment in an occupation/industry. RESULTS: The risk of MM was associated with several manufacturing occupations and industries, including machine operators and tenders, not elsewhere classified (SOC 76) (OR = 1.8, CI = 1.0-3.3); textile, apparel, and furnishing machine operators and tenders (SOC 765) (OR = 6.0, CI = 1.7-21); and machinery manufacturing, except electrical (SIC 35) (OR = 3.3, CI = 1.7-6.7). Several service occupations and industries, such as food and beverage preparation (SOC 521) (OR = 2.0, CI = 1.1-3.8), were also associated with MM. One occupation that has been associated with MM in several previous studies, painters, paperhangers, and plasterers (SOC 644) was associated with a non-significantly elevated risk (OR = 3.6, CI = 0.7-19). CONCLUSIONS: We found associations between the risk of MM and employment in several manufacturing and service-related occupations and industries.

Associations of common variants in genes involved in metabolism and response to exogenous chemicals with risk of multiple myeloma.

BACKGROUND: We examined risk of multiple myeloma (MM) associated with variants in genes involved in metabolism and response to exogenous chemicals [cytochrome P450 enzymes (CYP1B1, CYP2C9), epoxide hydrolase (EPHX1), paraoxonase 1 (PON1), arylhydrocarbon hydroxylase receptor (AHR), and NAD(P)H:quinone oxidoreductase (NQO1)]. METHODS: This study included 279 MM cases and 782 controls in a pooled analysis of two population-based case-control studies. One common variant from each candidate gene was genotyped using DNA from blood or buccal cells. We estimated risk of MM associated with each genotype, controlling for race, gender, study site, and age, using odds ratios (OR) and 95% confidence intervals (CI). RESULTS: Evaluations of the CYP1B1 V432L variant (rs1056836) suggested increased risk of MM among persons with the CG and GG genotypes compared to the CC genotype [OR (95% CI)=1.4 (1.0-2.0)]. Similar results were seen in analyses stratified by race and gender. We did not find any associations between MM and the CYP2C9, EPHX1, NQO1, or PON1 genes. CONCLUSIONS: CYP1B1 activates chemicals such as polycyclic aromatic hydrocarbons and dioxins to create oxidized, reactive intermediates, and higher gene activity has been shown for the G allele. We conducted the largest analysis to date on MM and these genetic variants and our results provide preliminary evidence that variation in CYP1B1 may influence susceptibility to MM.