A Pooled Analysis of Cigarette Smoking and Risk of Multiple Myeloma from the International Multiple Myeloma Consortium

Abstract

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 (ORs) and 95% confidence intervals (CIs) 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 to 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.

Young Adult and Usual Adult Body Mass Index and Multiple Myeloma Risk: A Pooled Analysis in the International Multiple Myeloma Consortium (IMMC)

“…We categorized age at interview by decade (<50, 50–59, 60–69, 70+ years) and race/ethnicity into three groups (White, Black, Other/unknown). We harmonized education level into five categories (<12 years of study; 12+ years or high school graduate; some attendance at college, technical, or vocational school after high school; graduation from college without further studies; or, other) and defined participants’ history of tobacco use (ever, never) and alcohol intake (ever, never)(26, 38). …”

Joint associations of smoking and television viewing time on cancer and cardiovascular disease mortality

“…The interaction between baseline TV time and smoking status was assessed by the likelihood ratio (LR) test of a model that contained the interaction term for TV time and smoking nested within a model not including the interaction term. Sensitivity analyses were undertaken, excluding participants who died in the first 2 years ( n = 67), those who changed their TV viewing habits by >2 hr/d from baseline ( n = 746), and cancer deaths without an established link with smoking ( n = 28; ICD10 codes C55, C56, C73, C795, C833, C835, C900) . Statistical analyses were performed using Stata V14 (StataCorp LP, College Station, TX).…”

Association of VEGF and VDR gene- gene and gene- smoking interaction on risk of multiple myeloma in Chinese Han population

“…Cigarette smoking has been suggested to play a crucial role in increasing the risk of some types of cancer risk, but the association with MM risk was inconclusive [25, 26]. In current study, we found that the smoking rate was higher in MM cases than controls, it means that smoking may be positively associated with MM risk, so in this study we investigated not only gene- gene interaction, but also gene- environment interaction between SNPs and smoking.…”