Dataset Information

Medical history, lifestyle, family history, and occupational risk factors for follicular lymphoma: the InterLymph Non-Hodgkin Lymphoma Subtypes Project.

ABSTRACT:

Background

Follicular lymphoma (FL) has been linked with cigarette smoking and, inconsistently, with other risk factors.

Methods

We assessed associations of medical, hormonal, family history, lifestyle, and occupational factors with FL risk in 3530 cases and 22639 controls from 19 case-control studies in the InterLymph consortium. Age-, race/ethnicity-, sex- and study-adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using logistic regression.

Results

Most risk factors that were evaluated showed no association, except for a few modest or sex-specific relationships. FL risk was increased in persons: with a first-degree relative with non-Hodgkin lymphoma (OR = 1.99; 95% CI = 1.55 to 2.54); with greater body mass index as a young adult (OR = 1.15; 95% CI = 1.04 to 1.27 per 5 kg/m(2) increase); who worked as spray painters (OR = 2.66; 95% CI = 1.36 to 5.24); and among women with Sjögren syndrome (OR = 3.37; 95% CI = 1.23 to 9.19). Lower FL risks were observed in persons: with asthma, hay fever, and food allergy (ORs = 0.79-0.85); blood transfusions (OR = 0.78; 95% CI = 0.68 to 0.89); high recreational sun exposure (OR = 0.74; 95% CI = 0.65 to 0.86, fourth vs first quartile); who worked as bakers or millers (OR = 0.51; 95% CI = 0.28 to 0.93) or university/higher education teachers (OR = 0.58; 95% CI = 0.41 to 0.83). Elevated risks specific to women included current and longer duration of cigarette use, whereas reduced risks included current alcohol use, hay fever, and food allergies. Other factors, including other autoimmune diseases, eczema, hepatitis C virus seropositivity, hormonal drugs, hair dye use, sun exposure, and farming, were not associated with FL risk.

Conclusions

The few relationships observed provide clues suggesting a multifactorial etiology of FL but are limited in the extent to which they explain FL occurrence.

SUBMITTER: Linet MS

PROVIDER: S-EPMC4155461 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature

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Publications

Medical history, lifestyle, family history, and occupational risk factors for follicular lymphoma: the InterLymph Non-Hodgkin Lymphoma Subtypes Project.

Linet Martha S MS Vajdic Claire M CM Morton Lindsay M LM de Roos Anneclaire J AJ Skibola Christine F CF Boffetta Paolo P Cerhan James R JR Flowers Christopher R CR de Sanjosé Silvia S Monnereau Alain A Cocco Pierluigi P Kelly Jennifer L JL Smith Alexandra G AG Weisenburger Dennis D DD Clarke Christina A CA Blair Aaron A Bernstein Leslie L Zheng Tongzhang T Miligi Lucia L Clavel Jacqueline J Benavente Yolanda Y Chiu Brian C H BC

Journal of the National Cancer Institute. Monographs 20140801 48

<h4>Background</h4>Follicular lymphoma (FL) has been linked with cigarette smoking and, inconsistently, with other risk factors.<h4>Methods</h4>We assessed associations of medical, hormonal, family history, lifestyle, and occupational factors with FL risk in 3530 cases and 22639 controls from 19 case-control studies in the InterLymph consortium. Age-, race/ethnicity-, sex- and study-adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using logistic regression.<h4>Results ...[more]

PMID: 25174024

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Project description:Although risk factors for diffuse large B-cell lymphoma (DLBCL) have been suggested, their independent effects, modification by sex, and association with anatomical sites are largely unknown.In a pooled analysis of 4667 cases and 22639 controls from 19 studies, we used stepwise logistic regression to identify the most parsimonious multivariate models for DLBCL overall, by sex, and for selected anatomical sites.DLBCL was associated with B-cell activating autoimmune diseases (odds ratio [OR] = 2.36, 95% confidence interval [CI] = 1.80 to 3.09), hepatitis C virus seropositivity (OR = 2.02, 95% CI = 1.47 to 2.76), family history of non-Hodgkin lymphoma (OR = 1.95, 95% CI = 1.54 to 2.47), higher young adult body mass index (OR = 1.58, 95% CI = 1.12 to 2.23, for 35+ vs 18.5 to 22.4 kg/m(2)), higher recreational sun exposure (OR = 0.78, 95% CI = 0.69 to 0.89), any atopic disorder (OR = 0.82, 95% CI = 0.76 to 0.89), and higher socioeconomic status (OR = 0.86, 95% CI = 0.79 to 0.94). Additional risk factors for women were occupation as field crop/vegetable farm worker (OR = 1.78, 95% CI = 1.22 to 2.60), hairdresser (OR = 1.65, 95% CI = 1.12 to 2.41), and seamstress/embroider (OR = 1.49, 95% CI = 1.13 to 1.97), low adult body mass index (OR = 0.46, 95% CI = 0.29 to 0.74, for <18.5 vs 18.5 to 22.4 kg/m(2)), hormone replacement therapy started age at least 50 years (OR = 0.68, 95% CI = 0.52 to 0.88), and oral contraceptive use before 1970 (OR = 0.78, 95% CI = 0.62 to 1.00); and for men were occupation as material handling equipment operator (OR = 1.58, 95% CI = 1.02 to 2.44), lifetime alcohol consumption (OR = 0.57, 95% CI = 0.44 to 0.75, for >400 kg vs nondrinker), and previous blood transfusion (OR = 0.69, 95% CI = 0.57 to 0.83). Autoimmune disease, atopy, and family history of non-Hodgkin lymphoma showed similar associations across selected anatomical sites, whereas smoking was associated with central nervous system, testicular and cutaneous DLBCLs; inflammatory bowel disease was associated with gastrointestinal DLBCL; and farming and hair dye use were associated with mediastinal DLBCL.Our results support a complex and multifactorial etiology for DLBCL with some variation in risk observed by sex and anatomical site.

Project description:BackgroundNon-Hodgkin lymphoma (NHL) comprises biologically and clinically heterogeneous subtypes. Previously, study size has limited the ability to compare and contrast the risk factor profiles among these heterogeneous subtypes.MethodsWe pooled individual-level data from 17 471 NHL cases and 23 096 controls in 20 case-control studies from the International Lymphoma Epidemiology Consortium (InterLymph). We estimated the associations, measured as odds ratios, between each of 11 NHL subtypes and self-reported medical history, family history of hematologic malignancy, lifestyle factors, and occupation. We then assessed the heterogeneity of associations by evaluating the variability (Q value) of the estimated odds ratios for a given exposure among subtypes. Finally, we organized the subtypes into a hierarchical tree to identify groups that had similar risk factor profiles. Statistical significance of tree partitions was estimated by permutation-based P values (P NODE).ResultsRisks differed statistically significantly among NHL subtypes for medical history factors (autoimmune diseases, hepatitis C virus seropositivity, eczema, and blood transfusion), family history of leukemia and multiple myeloma, alcohol consumption, cigarette smoking, and certain occupations, whereas generally homogeneous risks among subtypes were observed for family history of NHL, recreational sun exposure, hay fever, allergy, and socioeconomic status. Overall, the greatest difference in risk factors occurred between T-cell and B-cell lymphomas (P NODE < 1.0×10(-4)), with increased risks generally restricted to T-cell lymphomas for eczema, T-cell-activating autoimmune diseases, family history of multiple myeloma, and occupation as a painter. We further observed substantial heterogeneity among B-cell lymphomas (P NODE < 1.0×10(-4)). Increased risks for B-cell-activating autoimmune disease and hepatitis C virus seropositivity and decreased risks for alcohol consumption and occupation as a teacher generally were restricted to marginal zone lymphoma, Burkitt/Burkitt-like lymphoma/leukemia, diffuse large B-cell lymphoma, and/or lymphoplasmacytic lymphoma/Waldenström macroglobulinemia.ConclusionsUsing a novel approach to investigate etiologic heterogeneity among NHL subtypes, we identified risk factors that were common among subtypes as well as risk factors that appeared to be distinct among individual or a few subtypes, suggesting both subtype-specific and shared underlying mechanisms. Further research is needed to test putative mechanisms, investigate other risk factors (eg, other infections, environmental exposures, and diet), and evaluate potential joint effects with genetic susceptibility.

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Dataset Information

Medical history, lifestyle, family history, and occupational risk factors for follicular lymphoma: the InterLymph Non-Hodgkin Lymphoma Subtypes Project.

Background

Methods

Results

Conclusions

Publications

Medical history, lifestyle, family history, and occupational risk factors for follicular lymphoma: the InterLymph Non-Hodgkin Lymphoma Subtypes Project.

Similar Datasets

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