J Natl Cancer Inst Monogr 2014 Aug;2014(48):130-44
Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD (LMM, SMM, JSC, PH, NR, AB, KPC, QL, SIB, MSL, JNS); Department of Health Sciences Research (SLS, JRC, TMH), Division of Hematology (TGC), and Divison of General Internal Medicine (ML), College of Medicine, Mayo Clinic, Rochester, MN; Department of Cancer Etiology, City of Hope Beckman Research Institute, Duarte, CA (SSW, LB, AL); Prince of Wales Clinical School, University of New South Wales, Sydney, Australia (CMV); Department of Epidemiology, Comprehensive Cancer Center, University of Alabama, Birmingham, AL (CFS); Department of Epidemiology and Biostatistics, School of Medicine, University of California San Francisco, San Francisco, CA (PMB, EAH); Unit of Infections and Cancer (UNIC), Cancer Epidemiology Research Programme, Institut Català d' Oncologia, IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain, CIBER de Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain (SdS, YB); Unit of Clinical Epidemiology, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden (KES); Department of Health Studies, University of Chicago, Chicago, IL (BCHC); Department of Environmental Health Sciences (YZ, TZ) and Department of Biostatistics (TRH), Yale School of Public Health, New Haven, CT; INSERM, Centre for Research in Epidemiology and Population Health (CESP), U1018, Environmental Epidemiology of Cancer Group, Villejuif, France, Univ Paris Sud, UMRS 1018, Villejuif, France (AM, JC, LO); Registry of Hematological Malignancies in Gironde, Bergonié Institute, 33076 Bordeaux, France (AM); Department of Histopathology, Douglass Hanly Moir Pathology, Macquarie Park, Australia, The Australian School of Advanced Medicine, Macquarie University, Sydney, Australia (JJT); Department of Medical Epidemiology and Biostatistics (H-OA) and Department of Oncology and Pathology (BG), Karolinska Institutet, Stockholm, Swed
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.