Search

Background: Mycosis fungoides and Sézary syndrome (MF/SS) are rare cutaneous T-cell lymphomas. Their etiology is poorly understood., Methods: A pooled analysis of 324 MF/SS cases and 17217 controls from 14 case-control studies from Europe, North America, and Australia, as part of the International Lymphoma Epidemiology Consortium (InterLymph) Non-Hodgkin Lymphoma (NHL) Subtypes Project, was carried out to investigate associations with lifestyle, medical history, family history, and occupational risk factors. Multivariate logistic regression models were used to calculate odds ratios (OR) and 95% confidence intervals (CI)., Results: We found an increased risk of MF/SS associated with body mass index equal to or larger than 30 kg/m(2) (OR = 1.57, 95% CI = 1.03 to 2.40), cigarette smoking for 40 years or more (OR = 1.55, 95% CI = 1.04 to 2.31), eczema (OR = 2.38, 95% CI = 1.73 to 3.29), family history of multiple myeloma (OR = 8.49, 95% CI = 3.31 to 21.80), and occupation as crop and vegetable farmers (OR = 2.37, 95% CI = 1.14 to 4.92), painters (OR = 3.71, 95% CI = 1.94 to 7.07), woodworkers (OR = 2.20, 95% CI = 1.18 to 4.08), and general carpenters (OR = 4.07, 95% CI = 1.54 to 10.75). We also found a reduced risk of MF/SS associated with moderate leisure time physical activity (OR = 0.46, 95% CI = 0.22 to 0.97)., Conclusions: Our study provided the first detailed analysis of risk factors for MF/SS and further investigation is needed to confirm these findings in prospective data and in other populations., (Published by Oxford University Press 2014.)

Background: Accounting for 10%-15% of all non-Hodgkin lymphomas in Western populations, peripheral T-cell lymphomas (PTCL) are the most common T-cell lymphoma but little is known about their etiology. Our aim was to identify etiologic risk factors for PTCL overall, and for specific PTCL subtypes, by analyzing data from 15 epidemiologic studies participating in the InterLymph Consortium., Methods: A pooled analysis of individual-level data for 584 histologically confirmed PTCL cases and 15912 controls from 15 case-control studies conducted in Europe, North America, and Australia was undertaken. Data collected from questionnaires were harmonized to permit evaluation of a broad range of potential risk factors. Odds ratios (OR) and 95% confidence intervals (CI) were calculated using logistic regression., Results: Risk factors associated with increased overall PTCL risk with a P value less than .05 included: a family history of hematologic malignancies (OR = 1.92, 95% CI = 1.30 to 2.84); celiac disease (OR = 17.8, 95% CI = 8.61 to 36.79); eczema (OR = 1.41, 95% CI = 1.07 to 1.85); psoriasis (OR = 1.97, 95% CI = 1.17 to 3.32); smoking 40 or more years (OR = 1.92, 95% CI = 1.41 to 2.62); and employment as a textile worker (ever) (OR = 1.58, 95% CI = 1.05 to 2.38) and electrical fitter (ever) (OR = 2.89, 95% CI = 1.41 to 5.95). Exposures associated with reduced overall PTCL risk included a personal history of allergies (OR = 0.69, 95% CI = 0.54 to 0.87), alcohol consumption (ever) (OR = 0.64, 95% CI = 0.49 to 0.82), and having ever lived or worked on a farm (OR = 0.72, 95% CI = 0.55% to 0.95%). We also observed the well-established risk elevation for enteropathy-type PTCL among those with celiac disease in our data. Conclusions Our pooled analyses identified a number of new potential risk factors for PTCL and require further validation in independent series., (Published by Oxford University Press 2014.)

Background: Non-Hodgkin lymphoma (NHL), the most common hematologic malignancy, consists of numerous subtypes. The etiology of NHL is incompletely understood, and increasing evidence suggests that risk factors may vary by NHL subtype. However, small numbers of cases have made investigation of subtype-specific risks challenging. The International Lymphoma Epidemiology Consortium therefore undertook the NHL Subtypes Project, an international collaborative effort to investigate the etiologies of NHL subtypes. This article describes in detail the project rationale and design., Methods: We pooled individual-level data from 20 case-control studies (17471 NHL cases, 23096 controls) from North America, Europe, and Australia. Centralized data harmonization and analysis ensured standardized definitions and approaches, with rigorous quality control., Results: The pooled study population included 11 specified NHL subtypes with more than 100 cases: diffuse large B-cell lymphoma (N = 4667), follicular lymphoma (N = 3530), chronic lymphocytic leukemia/small lymphocytic lymphoma (N = 2440), marginal zone lymphoma (N = 1052), peripheral T-cell lymphoma (N = 584), mantle cell lymphoma (N = 557), lymphoplasmacytic lymphoma/Waldenström macroglobulinemia (N = 374), mycosis fungoides/Sézary syndrome (N = 324), Burkitt/Burkitt-like lymphoma/leukemia (N = 295), hairy cell leukemia (N = 154), and acute lymphoblastic leukemia/lymphoma (N = 152). Associations with medical history, family history, lifestyle factors, and occupation for each of these 11 subtypes are presented in separate articles in this issue, with a final article quantitatively comparing risk factor patterns among subtypes., Conclusions: The International Lymphoma Epidemiology Consortium NHL Subtypes Project provides the largest and most comprehensive investigation of potential risk factors for a broad range of common and rare NHL subtypes to date. The analyses contribute to our understanding of the multifactorial nature of NHL subtype etiologies, motivate hypothesis-driven prospective investigations, provide clues for prevention, and exemplify the benefits of international consortial collaboration in cancer epidemiology., (Published by Oxford University Press 2014.)

Background: Non-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., Methods: We 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)., Results: Risks 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., Conclusions: Using 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., (Published by Oxford University Press 2014.)