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.

INTRODUCTION

Multiple myeloma is a B-cell malignancy characterized by abnormal monoclonal plasma cells in the bone marrow, monoclonal immunoglobulin in serum and/or urine, and lytic bone lesions. The etiology of this malignancy remains poorly understood. Past investigations of cigarette smoking and multiple myeloma have generally yielded null results (1, 2), although most studies have been underpowered to detect moderate associations, particularly within population subgroups. To clarify the relationship between cigarette smoking and multiple myeloma, we conducted a pooled analysis of case-control studies participating in the International Multiple Myeloma Consortium (IMMC).

MATERIALS AND METHODS

We pooled individual-level questionnaire data from nine case-control studies in the IMMC that collected data on cigarette smoking (2,670 cases, 11,913 controls). The methods of the participating studies and this pooled analysis have been previously described (3). Smoking status was based on participants’ usual behavior prior to the diagnosis of multiple myeloma or index date for controls; and former/current smoking status was based on direct questions or calculated from smoking duration. In sensitivity analyses, participants who reported quitting within the two years prior to study interview were re-grouped as current smokers.

Data were checked for consistency, outliers, and missing values prior to pooling. Within each study, we computed odds ratios (ORs) and 95% confidence intervals (95% CI) for ever vs. never smoking using unconditional logistic regression with adjustment for gender and age group. We conducted a meta-analysis of study-specific findings using random- and fixed-effects models (4); random effects results are shown in Figure 1. Since the statistical heterogeneity between studies was not significant (Q statistic P=0.10), we pooled the data into a harmonized data set. Pooled ORs and 95% CIs were adjusted for gender, age group, race, education (indicator of socioeconomic status), body mass index (BMI), alcohol consumption, and study center. Tests of trend for categorical variables were calculated by modeling category numbers as continuous parameters. We conducted stratified analyses by gender, race, education, alcohol drinking status, BMI, and study design, and used the likelihood ratio test to identify statistical interaction.

Figure 1.

Study-specific risks of multiple myeloma for ever versus never cigarette smoking, adjusted for gender and age group. P-heterogeneity = 0.10.

RESULTS

In the pooled study population, just over half of the participants were male and the majority self-reported as White. 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 (Table 1). These associations did not change measurably when participants who ceased smoking within two years prior to the completion of the questionnaire were re-categorized as current smokers from former smokers. However, we did find that participants who stopped smoking after age 56 had an almost 40% higher risk of multiple myeloma than those who stopped at age 33 or younger (p-trend=0.004) (Table 1). We saw no significant associations or consistent patterns for smoking frequency, pack-years, or duration.

Table 1.

Risk of multiple myeloma associated with cigarette smoking in pooled study population

Smoking Characteristics	Case	Control	OR1	95% CI1	p-trend
Smoking Status
Never Smoker	1,214	5,149	1.00	-
Ever Smoker	1,448	6,741	0.95	0.87-1.05
Current	487	2,639	0.82	0.73-0.93
Current2	559	2,862	0.89	0.79-1.01
Former	947	4,032	1.03	0.92-1.14
Former3	875	3,809	0.99	0.89-1.10	-
Age started smoking (years) 4
≤15	263	1,493	1.00	-
>15-18	380	2,053	1.07	0.89-1.28
>18-20	164	874	1.06	0.85-1.32
>20	236	1,125	1.16	0.95-1.43	0.26
Smoking Frequency (cigarettes/day) 4
1-10	382	1826	1.00	-
11-20	619	2789	1.00	0.86-1.16
21-30	273	1157	0.92	0.76- 1.12
31-40	91	484	1.04	0.80-1.35
40+	46	265	0.86	0.61-1.22	0.46
Pack-years Smoked 4
≤9.5	206	1315	1.00	-
>9.5-22.5	254	1319	1.14	0.93-1.40
>22.5-42	277	1332	1.12	0.91-1.38
>42	275	1289	1.07	0.87-1.32	0.81
Duration smoked (years to interview) 4
≤16	200	1414	1.00	-
>16-28	231	1353	1.14	0.93-1.41
>28-40	306	1371	1.26	1.02-1.54
>40	286	1328	1.10	0.88-1.37	0.76
Age stopped smoking (years) 5
≤33	182	1023	1.00	-
>33-45	217	1052	1.07	0.86-1.34
>45-56	247	929	1.19	0.94-1.50
>56	273	955	1.39	1.09-1.77	0.004
Years since stopped smoking 5
≤7	267	1073	1.00	-
>7-15	214	991	0.72	0.59-0.89
>15-25	196	916	0.74	0.60-0.92
>25	239	969	0.77	0.62-0.96	0.06

OR: odds ratio; CI: confidence interval

¹Adjusted for gender, age group, race, education, BMI group, ever drink alcohol and study center

²Includes participants who ceased smoking within two years prior to completions of questionnaire

³Excludes participants who ceased smoking within two years prior to completions of questionnaire

⁴Among ever smokers

⁵Among former smokers

Stratified analyses and tests of interaction did not suggest any effect modification by subgroups. However, female ever smokers (OR=0.83, 95% CI 0.72-0.96) and current smokers (OR=0.71, 95% CI 0.58-0.86) had significantly lower risks than female never smokers. Among women, additional stratified analyses and tests of interaction did not reveal evidence of effect modification. We did not observe a difference in the Pearson correlations between smoking status and alcohol frequency by gender (male r=0.11, p<0.001; female r=0.11, p=0.003).

DISCUSSION

In this pooled analysis of 2,670 cases and 11,913 controls, we found no convincing evidence of an association between cigarette smoking multiple myeloma. Null associations between smoking and multiple myeloma were also reported in two recent meta-analyses (1, 2), which included two and four studies from our analysis, respectively. Unlike our study, these meta-analyses did not have access to individual-level data, and therefore were limited in their ability to conduct subgroup analyses.

It is unclear why we observed lower risks of multiple myeloma among women who were ever and current smokers, but not former smokers. The null exposure-response relationships with smoking frequency, pack-years, and duration of smoking among women argue against smoking being a real protective factor. Also, these findings could be due to a possible disease effect with the current smokers being healthier than the former smokers. Disease effect may also explain the higher risk with older age at smoking cessation.

Strengths of our study include the relatively large sample size and the availability of individual-level risk factor data, enabling us to adjust for a variety of potential confounders and investigate associations within subgroups. Inherent limitations of the case-control design of the participating studies are the potential recall bias of past smoking, exposure misclassification, using controls that are not representative of the case source population

The consistency of our findings with previous cohort studies (5-7), which are less susceptible to these design limitations, argue against bias as a major explanation for our findings. In conclusion, the totality of evidence from our pooled analysis confirms that smoking is not associated with multiple myeloma.