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

Author Manuscript Published OnlineFirst on December 23, 2014; DOI: 10.1158/1055-9965.EPI-14-1145 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

Gabriella Andreotti1, Brenda M. Birmann2, Wendy Cozen3, Anneclaire J De Roos4, Brian C.H. Chiu5, Laura Costas6, Silvia de Sanjosé6, Kirsten Moysich7, Nicola J. Camp8, John J. Spinelli9,9b, Punam Pahwa10,10b, James A. Dosman10, John R. McLaughlin11, Paolo Boffetta12, Anthony Staines13, Dennis Weisenburger14, Véronique Benhaim-Luzon15, Paul Brennan15, Adele Seniori Costantini16, Lucia Miligi16, Marcello Campagna17, Alexandra Nieters18, Nikolaus Becker19, Marc Maynadié20, Lenka Foretová21, Tongzhang Zheng22, Guido Tricot23, Kevin Milliken24, Joseph Krzystan25, Emily Steplowski25, Dalsu Baris1, Mark P. Purdue1

1Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Rockville, MD; 2Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA; 3Department of Preventive Medicine, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA; 4Department of Environmental and Occupational Health, Drexel University School of Public Health, Philadelphia, PA; 5Department of Health Studies, University of Chicago, Chicago, IL; 6Unit of Infections and Cancer, Catalan Institute of Oncology, IDIBELL, University of Barcelona. Barcelona, Spain; 7Department of Cancer Prevention and Control, Roswell Park Cancer Institute, Buffalo, NY; 8Division of Genetic Epidemiology, University of Utah School of Medicine, Salt Lake City, UT; 9Cancer Control Research, BC Cancer Agency, Vancouver, BC; 9bSchool of Population and Public Health, University of British Columbia, Vancouver, BC; 10Canadian Centre for Health and Safety in Agriculture, University of Saskatchewan, Saskatoon, Saskatchewan, Canada; 10bCommunity Health and Epidemiology, University of Saskatchewan, Saskatoon, Saskatchewan, Canada; 11Public Health Ontario, Toronto, Ontario, Canada; 11bSamuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada; 12The Tisch Cancer Institute and Institute for Translational Epidemiology, Icahn School of Medicine at Mount Sinai, New York, NY; 13Department of Public Health, Public Health University College, Dublin, Ireland; 14City of Hope National Medical Center, Duarte, CA; 15International Agency for Research on Cancer, Lyon, France; 16Center for Study and Prevention of Cancer, Unit of Occupational and Environmental Epidemiology, Florence, Italy; 17Department of Public Health, Clinical and Molecular Medicine, Occupational Health Section, University of Cagliari, Monserrato, Italy; 18Division of Clinical Epidemiology, German Cancer Research Centre, Heidelberg, Germany; 19German Cancer Center, Division of Cancer Epidemiology, Heidelberg, Germany; 20Registry of Hematological malignancies of Côte d’Or, EA4184, University of Burgundy, Dijon, France; 21Dept. of Cancer Epidemiology and Genetics, Masaryk Memorial Cancer Institute, Brno, Czech Republic; 22Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT; 23Department of Internal Medicine, University of Iowa, Iowa City, Iowa; 24Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA; 25Information Management Services, Inc., Silver Spring, MD;

Downloaded from cebp.aacrjournals.org on September 23, 2021. © 2014 American Association for Cancer Research. Author Manuscript Published OnlineFirst on December 23, 2014; DOI: 10.1158/1055-9965.EPI-14-1145 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

Financial Support: 1. Funding for the Utah study was in part from the Leukemia and Lymphoma Society 6067-09 (NJC) and the NCI CA152336 (NJC). Data collection for the Utah resource was made possible by the Utah Population Database (UPDB) and the Utah Cancer Registry (UCR). Partial support for all datasets within the UPDB was provided by the University of Utah Huntsman Cancer Institute (HCI) and the HCI Cancer Center Support grant, P30 CA42014 from the NCI. The UCR is funded by contract HHSN261201000026C from the NCI SEER program with additional support from the Utah State Department of Health and the University of Utah. 2. The work was supported by the European Regional Development Fund and the State Budget of the Czech Republic (RECAMO, CZ.1.05/2.1.00/03.0101). The work conducted by Brenda Birmann was supported in part by grants from the NCI (K07 CA115687, CA149445) and the American Cancer Society (RSG-11-020-01-CNE). 3. EPILYMPH was supported by : European Commission (QLK4-CT-2000-00422 and FOOD- CT-2006-023103), Spanish Ministry of Health (CIBERESP, PI11/01810, PI14/01219,RCESP C03/09, RTICESP C03/10, and RTIC RD06/0020/0095), Rio Hortega (CM13/00232), Agència de Gestió d’Ajuts Universitaris i de Recerca–Generalitat de Catalunya (Catalonian Government, 2014SGR756-F), National Institutes of Health (contract NO1-CO-12400), Italian Ministry of Education, University and Research (PRIN 2007 prot.2007WEJLZB, PRIN 2009 prot. 20092ZELR2), Italian Association for Cancer Research (IG grant 11855/2011); Federal Office for Radiation Protection (StSch4261 and StSch4420), José Carreras Leukemia Foundation (DJCLS-R04/08), German Federal Ministry for Education and Research (BMBF-01-EO-1303), Health Research Board, Ireland and Cancer Research Ireland [EpiLymph]. 4. This work was supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics of the National Cancer Institute.

Conflict of Interest: The authors of this paper have no conflicts of interest to disclose.

Running Title: Smoking and Multiple Myeloma

Word Count: Abstract=235, Text=803

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.

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.

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.

References 1. Castillo JJ, Dhami PK, Curry S, Brennan K. No association between cigarette smoking and incidence of plasma cell myeloma: a meta-analysis of 17 observational studies. Am J Hematol 2012;87:729-31. 2. Psaltopoulou T, Sergentanis TN, Kanellias N, Kanavidis P, Terpos E, Dimopoulos MA. Tobacco smoking and risk of multiple myeloma: a meta-analysis of 40 observational studies. Int J Cancer 2013;132:2413-31. 3. Andreotti G, Birmann B, De Roos AJ, Spinelli J, Cozen W, Camp NJ, Moysich K, Chiu B, Steplowski E, Krzystan J, Boffetta P, Benhaim-Luzon V, Brennan P, de Sanjosé S, Costas L, Costantini AS, Miligi L, Cocco P, Becker N, Foretová L, Maynadié M, Nieters A, Staines A, Tricot G, Milliken K, Weisenburger D, Zheng T, Baris D, Purdue MP. A pooled analysis of alcohol consumption and risk of multiple myeloma in the international multiple myeloma consortium. Cancer Epidemiol Biomarkers Prev 2013;22:1620-7. 4. Viechtbauer W. Confidence intervals for the amount of heterogeneity in meta-analysis. Stat Med 2007;26:37-52. 5. Kroll ME, Murphy F, Pirie K, Reeves GK, Green J, Beral V. Alcohol drinking, tobacco smoking and subtypes of haematological malignancy in the UK Million Women Study. Br J Cancer 2012;107:879-87. 6. Walter RB, Brasky TM, Milano F, White E. Vitamin, mineral, and specialty supplements and risk of hematologic malignancies in the prospective VITamins And Lifestyle (VITAL) study. Cancer Epidemiol Biomarkers Prev 2011;20:2298-308. 7. Fernberg P, Odenbro A, Bellocco R, Boffetta P, Pawitan Y, Zendehdel K, Adami J. 2. Tobacco use, body mass index, and the risk of leukemia and multiple myeloma: a nationwide cohort study in Sweden. Cancer Res 2007;67:5983-6.

Table 1. Risk of multiple myeloma associated with cigarette smoking in pooled study population

Smoking Characteristics Case Control OR 1 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 Smoked4 ≤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 smoking5 ≤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 1 Adjusted for gender, age group, race, education, BMI group, ever drink alcohol and study center 2 Includes participants who ceased smoking within two years prior to completions of questionnaire 3 Excludes participants who ceased smoking within two years prior to completions of questionnaire 4 Among ever smokers 5 Among former smokers

Study OR (95% CI) Cases / Controls

Canada 1.32 (1.00−1.74) 252 / 969

EpiLymph 1.02 (0.76−1.36) 151 / 1364

FHCRC 0.87 (0.71−1.06) 375 / 961

Italy 0.94 (0.68−1.29) 140 / 656

NCI Population Health Study 0.98 (0.80−1.21) 313 / 1294

NCI−Connecticut 0.71 (0.50−1.01) 80 / 393

Nebraska 0.97 (0.57−1.66) 32 / 697

RPCI 0.76 (0.51−1.11) 75 / 338

Utah 0.54 (0.29−1.01) 30 / 9

Overall 0.92 (0.81−1.05) 1448 / 6741

0.125 0.25 0.50 1.0 2.0 4.0 8.0 Odds Ratios

Figure 1. StudyDownloaded-specific fromrisks cebp.aacrjournals.org of multiple myeloma on for September ever versus 23, 2021.never © cigarette 2014 American smoking, Association adjusted for for Cancer gender Research. and age group. P-heterogeneity = 0.10. Author Manuscript Published OnlineFirst on December 23, 2014; DOI: 10.1158/1055-9965.EPI-14-1145 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

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

Gabriella Andreotti, Brenda M. Birmann, Wendy Cozen, et al.

Cancer Epidemiol Biomarkers Prev Published OnlineFirst December 23, 2014.

Updated version Access the most recent version of this article at: doi:10.1158/1055-9965.EPI-14-1145

Author Author manuscripts have been peer reviewed and accepted for publication but have not yet been Manuscript edited.

E-mail alerts Sign up to receive free email-alerts related to this article or journal.

Reprints and To order reprints of this article or to subscribe to the journal, contact the AACR Publications Subscriptions Department at [email protected].

Permissions To request permission to re-use all or part of this article, use this link http://cebp.aacrjournals.org/content/early/2014/12/23/1055-9965.EPI-14-1145. Click on "Request Permissions" which will take you to the Copyright Clearance Center's (CCC) Rightslink site.