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Medical History, Lifestyle, Family History, and Occupational Risk Factors for Sporadic Burkitt Lymphoma/Leukemia: The Interlymph Non-Hodgkin Lymphoma Subtypes Project

Medical History, Lifestyle, Family History, and Occupational Risk Factors for Sporadic Burkitt... Abstract Background The etiologic role of medical history, lifestyle, family history, and occupational risk factors in sporadic Burkitt lymphoma (BL) is unknown, but epidemiologic and clinical evidence suggests that risk factors may vary by age. Methods We investigated risk factors for sporadic BL in 295 cases compared with 21818 controls in a pooled analysis of 18 case–control studies in the International Lymphoma Epidemiology Consortium (InterLymph). Cases were defined to include typical BL or Burkitt-like lymphoma. Odds ratios (ORs) and 95% confidence intervals (CIs) for associations were calculated separately for younger (<50 years) and older (≥50 years) BL using multivariate logistic regression. Results Cases included 133 younger BL and 159 older BL (age was missing for three cases) and they were evenly split between typical BL (n = 147) and Burkitt-like lymphoma (n = 148). BL in younger participants was inversely associated with a history of allergy (OR = 0.58; 95% CI = 0.32 to 1.05), and positively associated with a history of eczema among individuals without other atopic conditions (OR = 2.54; 95% CI = 1.20 to 5.40), taller height (OR = 2.17; 95% CI = 1.08 to 4.36), and employment as a cleaner (OR = 3.49; 95% CI = 1.13 to 10.7). BL in older participants was associated with a history of hepatitis C virus seropositivity (OR = 4.19; 95% CI = 1.05 to 16.6) based on three exposed cases. Regardless of age, BL was inversely associated with alcohol consumption and positively associated with height. Conclusions Our data suggest that BL in younger and older adults may be etiologically distinct. Burkitt lymphoma (BL) is an aggressive B-cell non-Hodgkin lymphoma (NHL) that occurs as three histologically indistinguishable subtypes: sporadic, endemic, and immunodeficiency-associated BL (1,2). Sporadic BL occurs in developed countries, accounting for about 30% of all lymphoid malignancies in children and 1%–5% of NHL in adults (3,4). Endemic BL occurs in equatorial Africa and Papua New Guinea as the most common childhood cancer and is associated with Epstein–Barr virus and Plasmodium falciparum infections (5). Immunodeficiency-associated BL is seen in those with HIV infection (6) or a history of solid organ transplantation (7). In contrast, risk factors for sporadic BL are unknown because no analytical epidemiological studies have examined risk factors other than infectious agents (8,9). Descriptive epidemiological and clinical studies conducted in developed countries point to age-related differences in BL. These include distinct age-specific incidence peaks of BL, one during childhood and the other at 60 years of age, in a study conducted in the Netherlands (10), as well as distinct peaks in adults in two studies conducted in the United States (6,11), and one study conducted using BL data from four continents excluding Africa (12). Clinical studies indicate a superior treatment outcome in pediatric BL patients compared with older BL patients (13). As with other cancers (14,15), the bimodality of BL and the different clinical outcomes by age suggest distinct etiologies of BL diagnosed at different ages. We investigated the associations between BL and medical history, lifestyle, family history, and occupational risk factors using pooled data from 18 case–control studies conducted in Europe, North America, and Australia as part of the International Lymphoma Epidemiology Consortium (InterLymph) NHL Subtypes Project. Our study is the first analytic epidemiological study to evaluate a broad range of risk factors for BL. The main aim of the study was to identify risk factors for sporadic BL in younger versus older participants (ie, <50 vs ≥50 years old). Methods Detailed methods for the InterLymph NHL Subtypes Project are reported elsewhere in this issue. Briefly, de-identified individual-level data from 18 case–control studies were included in this pooled analysis based on the following criteria: 1) case–control design with incident, histologically confirmed cases of BL and 2) availability of individual-level data for several risk factors of interest by December 31, 2011. Participants with serologically confirmed HIV infection or a history of solid organ transplantation were excluded. Because none of the cases was enrolled from equatorial Africa or Papua New Guinea, all cases in this analysis were considered to be sporadic BL. Ethics review committees at the participating institutions approved the studies and participants were enrolled after providing written informed consent. NHL Subtype Ascertainment and Harmonization Cases were diagnosed as BL, including a diagnosis of Burkitt-like lymphoma (BLL), according to the Working Formulation (16,17) or the 2001 World Health Organization (WHO) classification for hematologic malignancies (18). The histologic definition of BL is based on observing a diffuse and starry-sky pattern at low magnification under the microscope, a homogenous population of medium-sized lymphoid cells with round nuclei, open chromatin, multiple distinct nucleoli, moderate amounts of basophilic cytoplasm and frequent mitotic figures at high magnification, typical immunohistochemistry (positive for CD10, CD20, and Bcl-6 and negative for Bcl-2, and with high Ki-67 proliferation index), and a simple cytogenetic profile involving c-MYC gene translocation. Cases suggestive of BL but showing a more pleomorphic cytology of the tumor cells were diagnosed as BLL. Not all studies retained tissue samples, so centralized pathology review of the diagnoses was not possible. An interdisciplinary team of pathologists and epidemiologists reviewed the pathology reports from the original studies to ensure that the NHL subtype classification was as accurate and specific as possible using guidelines from the InterLymph Pathology Working Group (19,20). Risk Factor Ascertainment and Harmonization Self-reported medical, family, lifestyle, and occupational histories were elicited using a standardized, structured in-person or telephone interview and/or written questionnaire, as reported elsewhere in this issue. The questionnaire data obtained from the contributing studies was harmonized centrally with each individual variable in the dataset reviewed and checked for consistency with related exposure variables. Statistical Analysis As the main study objective was to investigate risk factors for BL in younger and older participants, stratified analyses were conducted with cases and controls categorized as younger participants (<50 years) or older participants (≥50 years), based on the median age at BL diagnosis. Demographic and socioeconomic factors were analyzed. Associations of age-specific BL in younger and older participants with risk factors were estimated by calculating pooled odds ratios (ORs) and 95% confidence intervals (CIs) for each exposure category relative to the stated referent group, as well as the appropriate P values, using fixed-effects logistic regression models that adjusted for study, age, sex, and race/ethnicity (ie, the basic adjusted model). Because the controls from most of the studies were frequency matched by age and sex to all cases (ie, all NHL subtypes) in the study rather than just BL, we conducted all analyses using all controls. Sensitivity analyses using a subset of controls from each study that were individually matched by age and sex to BL cases gave essentially similar results (not shown). Associations with nominal multilevel exposures were evaluated by testing for statistical heterogeneity across the variable categories, whereas associations with ordinal multilevel exposures were evaluated by testing for a monotonic statistical trend in the OR per change in variable category using the likelihood ratio test. A two-sided P value less than .05 without adjustment for multiple comparisons indicated a statistically significant association. Individuals with missing data for the exposure variable of interest were excluded from the model when estimating the association. Interstudy heterogeneity among the 18 studies was evaluated using separate logistic regression models performed within each study and the variability of the study-specific coefficients was quantified by the H statistic as described elsewhere in this issue. The independent association of age-specific BL with variables identified in the basic adjusted model was evaluated by constructing a final logistic regression model including all significantly associated variables and running a forward stepwise multivariate logistic regression until only variables that were statistically significant at P less than .05 were retained (the final model). In contrast to analyses in the basic adjusted model, individuals with missing variable categories were retained in the final model by including a code for the missing category in the variable. We also conducted histology-specific analyses (typical BL or BLL) and with younger and older cases combined for comparison with the age-specific results. Results were reported only when based on data from six or more studies. Results We studied 295 cases (147 typical BL and 148 BLL) and 21818 controls (Table 1). Most came from population-based studies (83.7% of cases and 76.6% of controls) and from studies conducted in North America (62.4% of cases and 51.9% of controls). The median age of all patients with BL was 52 years (interquartile range: 36–63 years) and was similar for typical BL and BLL (data not shown). No differences were noted between the cases and controls with respect to white, non-Hispanic ethnicity (84.4% vs 93.1%) or socioeconomic class distribution (Table 1). The age-stratified analyses were performed by rounding the median age to a more intuitive cut point of 50 years. Table 1. Demographical characteristics of cases of sporadic Burkitt lymphoma and controls in the InterLymph NHL Subtypes Project*   Controls  Cases  No. (%)†  No. (%)†  All subjects  21818 (100)  295 (100)  Age, y   <30  1267 (5.8)  41 (13.9)   30–39  2001 (9.2)  45 (15.3)   40–49  2926 (13.4)  47 (15.9)   50–59  4508 (20.7)  64 (21.7)   60–69  6104 (28.0)  65 (22.0)   70–79  4127 (18.9)  27 (9.2)   ≥80  860 (3.9)  3 (1.0)  Sex   Male  12809 (58.7)  207 (70.2)   Female  9009 (41.3)  88 (29.8)  Race/ethnicity   White, non-Hispanic  20318 (93.1)  249 (84.4)   Black  342 (1.6)  3 (1.0)   Asian  320 (1.5)  15 (5.1)   Hispanic  356 (1.6)  21 (7.1)   Other/unknown/missing  482 (2.2)  7 (2.4)  Socioeconomic status   Low  8900 (40.8)  117 (39.7)   Medium  6280 (28.8)  80 (27.1)   High  6233 (28.6)  94 (31.9)   Other/missing  405 (1.9)  4 (1.4)  NHL classification   World Health Organization  12488 (57.2)  159 (53.9)   Working Formulation  9330 (42.8)  136 (46.1)  Histological diagnosis   Burkitt lymphoma  —  147 (49.8)   Burkitt-like lymphoma  —  148 (50.2)  BL anatomic site   Nodal  —  120 (40.7)   Extranodal  —  73 (24.7)   Systemic  —  21 (7.1)   Not collected  —  81 (27.5)  Study region   North America  11323 (51.9)  184 (62.4)   Northern Europe  5403 (24.8)  58 (19.7)   Southern Europe  4398 (20.2)  49 (16.6)   Australia  694 (3.2)  4 (1.4)  Study design   Population-based  16707 (76.6)  247 (83.7)   Hospital-based  5111 (23.4)  48 (16.3)    Controls  Cases  No. (%)†  No. (%)†  All subjects  21818 (100)  295 (100)  Age, y   <30  1267 (5.8)  41 (13.9)   30–39  2001 (9.2)  45 (15.3)   40–49  2926 (13.4)  47 (15.9)   50–59  4508 (20.7)  64 (21.7)   60–69  6104 (28.0)  65 (22.0)   70–79  4127 (18.9)  27 (9.2)   ≥80  860 (3.9)  3 (1.0)  Sex   Male  12809 (58.7)  207 (70.2)   Female  9009 (41.3)  88 (29.8)  Race/ethnicity   White, non-Hispanic  20318 (93.1)  249 (84.4)   Black  342 (1.6)  3 (1.0)   Asian  320 (1.5)  15 (5.1)   Hispanic  356 (1.6)  21 (7.1)   Other/unknown/missing  482 (2.2)  7 (2.4)  Socioeconomic status   Low  8900 (40.8)  117 (39.7)   Medium  6280 (28.8)  80 (27.1)   High  6233 (28.6)  94 (31.9)   Other/missing  405 (1.9)  4 (1.4)  NHL classification   World Health Organization  12488 (57.2)  159 (53.9)   Working Formulation  9330 (42.8)  136 (46.1)  Histological diagnosis   Burkitt lymphoma  —  147 (49.8)   Burkitt-like lymphoma  —  148 (50.2)  BL anatomic site   Nodal  —  120 (40.7)   Extranodal  —  73 (24.7)   Systemic  —  21 (7.1)   Not collected  —  81 (27.5)  Study region   North America  11323 (51.9)  184 (62.4)   Northern Europe  5403 (24.8)  58 (19.7)   Southern Europe  4398 (20.2)  49 (16.6)   Australia  694 (3.2)  4 (1.4)  Study design   Population-based  16707 (76.6)  247 (83.7)   Hospital-based  5111 (23.4)  48 (16.3)  * BL = Burkitt lymphoma; NHL = non-Hodgkin lymphoma. † The counts do not add up to the total number of cases/controls due to data missing by design or report. View Large The results from the basic adjusted model showed that BL in younger participants was inversely associated with a history of allergy (OR = 0.52; 95% CI = 0.30 to 0.90) or asthma (OR = 0.35; 95% CI = 0.13 to 0.95; based on four exposed cases). A non-significant inverse association with BL in younger participants was also observed for a history of atopy (OR = 0.68; 95% CI = 0.45 to 1.02), hay fever (OR = 0.60; 95% CI = 0.35 to 1.05), or food allergy (OR = 0.50; 95% CI = 0.17 to 1.50; based on four exposed cases). A history of eczema was unrelated to BL in younger participants. However, when eczema alone without other atopic conditions was considered, it was associated with elevated BL risk (OR = 2.8; 95% CI = 1.35 to 5.86) (Table 2). In contrast to BL in younger participants, a history of allergy, asthma, atopy, hay fever, or eczema was not associated with BL in older participants. Table 2. Association of medical and family history with sporadic Burkitt lymphoma in the InterLymph NHL Subtypes Project from the basic model, stratified by age*   <50 years  ≥50 years  Controls  Cases  OR (95% CI)‡  P  Controls  Cases  OR (95% CI)†  P  No. (%)†  No. (%)†  No. (%)†  No. (%)†  Medical history  Any atopic disorder§   No  3763 (65.4)  89 (67.4)  1.00 (referent)  .058  10156 (70.3)  114 (72.2)  1.00 (referent)  .736   Yes  1878 (32.6)  40 (30.3)  0.68 (0.45 to 1.02)    3977 (27.5)  43 (27.2)  0.94 (0.64 to 1.37)    Allergy||   No  2490 (64.9)  64 (70.3)  1.00 (referent)  .016  7082 (71.3)  64 (68.8)  1.00 (referent)  .760   Yes  1093 (28.5)  21 (23.1)  0.52 (0.30 to 0.90)    2231 (22.5)  23 (24.7)  1.09 (0.64 to 1.85)    Food allergy   No  3146 (82.0)  70 (76.9)  1.00 (referent)  .176  7140 (81.7)  57 (71.3)  1.00 (referent)  .989   Yes  274 (7.1)  4 (4.4)  0.50 (0.17 to 1.50)    586 (6.7)  5 (6.3)  0.99 (0.38 to 2.59)    Asthma   No  4865 (84.6)  109 (82.6)  1.00 (referent)  .015  12296 (85.1)  136 (86.1)  1.00 (referent)  .745   Yes  461 (8.0)  4 (3.0)  0.35 (0.13 to 0.95)    1061 (7.3)  13 (8.2)  1.11 (0.61 to 2.00)    Hay fever   No  2646 (62.9)  68 (62.4)  1.00 (referent)  .062  8543 (71.6)  98 (72.6)  1.00 (referent)  .228   Yes  909 (21.6)  23 (21.1)  0.60 (0.35 to 1.05)    1769 (14.8)  20 (14.8)  0.71 (0.41 to 1.25)    Eczema   No  3583 (83.7)  91 (84.3)  1.00 (referent)  .649  9868 (86.9)  122 (92.4)  1.00 (referent)  .684   Yes¶  516 (12.0)  12 (11.1)  1.16 (0.62 to 2.19)    912 (8.0)  8 (6.1)  0.86 (0.41 to 1.80)    Eczema without other atopic conditions   No eczema  3583 (83.7)  91 (84.3)  1.00 (referent)  .008  9868 (86.9)  122 (92.4)  1.00 (referent)  .805   Eczema without other atopic conditions#  176 (4.1)  9 (8.3)  2.82 (1.35 to 5.86)    402 (3.5)  4 (3.0)  1.06 (0.38 to 2.93)     Eczema with other atopic conditions  340 (7.9)  3 (2.8)  0.41 (0.13 to 1.32)    510 (4.5)  4 (3.0)  0.723 (0.26 to 2.02)    History of hepatitis C virus infection   No  1891 (59.3)  31 (56.4)  1.00 (referent)  .430  4453 (69.7)  30 (62.5)  1.00 (referent)  .066   Yes  42 (1.3)  0 (0.0)  —    109 (1.7)  3 (6.3)  4.10 (1.10 to 15.4)    Blood transfusion   No  3062 (89.8)  71 (86.6)  1.00 (referent)  .228  6091 (70.6)  78 (75.7)  1.00 (referent)  .054   Yes  232 (6.8)  8 (9.8)  1.64 (0.77 to 3.50)    1514 (17.5)  10 (9.7)  0.54 (0.27 to 1.06)    Total number of blood transfusions   No transfusion  3062 (89.8)  71 (86.6)  1.00 (referent)  .201  6091 (70.6)  78 (75.7)  1.00 (referent)  .267   1 transfusion  163 (4.8)  4 (4.9)  1.09 (0.39 to 3.08)    973 (11.3)  6 (5.8)  0.48 (0.21 to 1.13)     2 transfusions  39 (1.1)  1 (1.2)  1.61 (0.21 to 12.2)    292 (3.4)  2 (1.9)  0.74 (0.18 to 3.10)     ≥3 transfusions  23 (0.7)  3 (3.7)  6.46 (1.75 to 23.81)    189 (2.2)  2 (1.9)  0.79 (0.19 to 3.40)    Number of years from first blood transfusion   No transfusion  3062 (89.8)  71 (86.6)  1.00 (referent)  .194  6091 (70.6)  78 (75.7)  1.00 (referent)  .101   <20 years  134 (3.9)  6 (7.3)  2.22 (0.92 to 5.34)    657 (7.6)  3 (2.9)  0.36 (0.11 to 1.16)     20–39 years  85 (2.5)  1 (1.2)  0.51 (0.07 to 3.74)    557 (6.5)  6 (5.8)  0.92 (0.39 to 2.17)    Blood transfusion before 1990   No transfusion  3062 (89.8)  71 (86.6)  1.00 (referent)  .117  6091 (70.6)  78 (75.7)  1.00 (referent)  .068   Transfusion before 1990  158 (4.6)  7 (8.5)  2.22 (0.98 to 5.04)    1118 (13.0)  10 (9.7)  0.65 (0.33 to 1.28)     Transfusion year unknown  11 (0.3)  1 (1.2)  1.97 (0.21 to 18.0)    94 (1.1)  0 (0.0)  —    Family history of non-Hodgkin lymphoma   No  3057 (91.3)  68 (77.3)  1.00 (referent)  .517  9501 (91.8)  111 (91.0)  1.00 (referent)  .272   Yes  40 (1.2)  2 (2.3)  1.71 (0.37 to 7.91)    229 (2.2)  1 (0.8)  0.38 (0.05 to 2.83)    Family history of leukemia   No  3451 (91.6)  74 (80.4)  1.00 (referent)  .088  9409 (90.9)  107 (87.7)  1.00 (referent)  .644   Yes  65 (1.7)  0 (0.0)  —    321 (3.1)  5 (4.1)  1.26 (0.49 to 3.21)      <50 years  ≥50 years  Controls  Cases  OR (95% CI)‡  P  Controls  Cases  OR (95% CI)†  P  No. (%)†  No. (%)†  No. (%)†  No. (%)†  Medical history  Any atopic disorder§   No  3763 (65.4)  89 (67.4)  1.00 (referent)  .058  10156 (70.3)  114 (72.2)  1.00 (referent)  .736   Yes  1878 (32.6)  40 (30.3)  0.68 (0.45 to 1.02)    3977 (27.5)  43 (27.2)  0.94 (0.64 to 1.37)    Allergy||   No  2490 (64.9)  64 (70.3)  1.00 (referent)  .016  7082 (71.3)  64 (68.8)  1.00 (referent)  .760   Yes  1093 (28.5)  21 (23.1)  0.52 (0.30 to 0.90)    2231 (22.5)  23 (24.7)  1.09 (0.64 to 1.85)    Food allergy   No  3146 (82.0)  70 (76.9)  1.00 (referent)  .176  7140 (81.7)  57 (71.3)  1.00 (referent)  .989   Yes  274 (7.1)  4 (4.4)  0.50 (0.17 to 1.50)    586 (6.7)  5 (6.3)  0.99 (0.38 to 2.59)    Asthma   No  4865 (84.6)  109 (82.6)  1.00 (referent)  .015  12296 (85.1)  136 (86.1)  1.00 (referent)  .745   Yes  461 (8.0)  4 (3.0)  0.35 (0.13 to 0.95)    1061 (7.3)  13 (8.2)  1.11 (0.61 to 2.00)    Hay fever   No  2646 (62.9)  68 (62.4)  1.00 (referent)  .062  8543 (71.6)  98 (72.6)  1.00 (referent)  .228   Yes  909 (21.6)  23 (21.1)  0.60 (0.35 to 1.05)    1769 (14.8)  20 (14.8)  0.71 (0.41 to 1.25)    Eczema   No  3583 (83.7)  91 (84.3)  1.00 (referent)  .649  9868 (86.9)  122 (92.4)  1.00 (referent)  .684   Yes¶  516 (12.0)  12 (11.1)  1.16 (0.62 to 2.19)    912 (8.0)  8 (6.1)  0.86 (0.41 to 1.80)    Eczema without other atopic conditions   No eczema  3583 (83.7)  91 (84.3)  1.00 (referent)  .008  9868 (86.9)  122 (92.4)  1.00 (referent)  .805   Eczema without other atopic conditions#  176 (4.1)  9 (8.3)  2.82 (1.35 to 5.86)    402 (3.5)  4 (3.0)  1.06 (0.38 to 2.93)     Eczema with other atopic conditions  340 (7.9)  3 (2.8)  0.41 (0.13 to 1.32)    510 (4.5)  4 (3.0)  0.723 (0.26 to 2.02)    History of hepatitis C virus infection   No  1891 (59.3)  31 (56.4)  1.00 (referent)  .430  4453 (69.7)  30 (62.5)  1.00 (referent)  .066   Yes  42 (1.3)  0 (0.0)  —    109 (1.7)  3 (6.3)  4.10 (1.10 to 15.4)    Blood transfusion   No  3062 (89.8)  71 (86.6)  1.00 (referent)  .228  6091 (70.6)  78 (75.7)  1.00 (referent)  .054   Yes  232 (6.8)  8 (9.8)  1.64 (0.77 to 3.50)    1514 (17.5)  10 (9.7)  0.54 (0.27 to 1.06)    Total number of blood transfusions   No transfusion  3062 (89.8)  71 (86.6)  1.00 (referent)  .201  6091 (70.6)  78 (75.7)  1.00 (referent)  .267   1 transfusion  163 (4.8)  4 (4.9)  1.09 (0.39 to 3.08)    973 (11.3)  6 (5.8)  0.48 (0.21 to 1.13)     2 transfusions  39 (1.1)  1 (1.2)  1.61 (0.21 to 12.2)    292 (3.4)  2 (1.9)  0.74 (0.18 to 3.10)     ≥3 transfusions  23 (0.7)  3 (3.7)  6.46 (1.75 to 23.81)    189 (2.2)  2 (1.9)  0.79 (0.19 to 3.40)    Number of years from first blood transfusion   No transfusion  3062 (89.8)  71 (86.6)  1.00 (referent)  .194  6091 (70.6)  78 (75.7)  1.00 (referent)  .101   <20 years  134 (3.9)  6 (7.3)  2.22 (0.92 to 5.34)    657 (7.6)  3 (2.9)  0.36 (0.11 to 1.16)     20–39 years  85 (2.5)  1 (1.2)  0.51 (0.07 to 3.74)    557 (6.5)  6 (5.8)  0.92 (0.39 to 2.17)    Blood transfusion before 1990   No transfusion  3062 (89.8)  71 (86.6)  1.00 (referent)  .117  6091 (70.6)  78 (75.7)  1.00 (referent)  .068   Transfusion before 1990  158 (4.6)  7 (8.5)  2.22 (0.98 to 5.04)    1118 (13.0)  10 (9.7)  0.65 (0.33 to 1.28)     Transfusion year unknown  11 (0.3)  1 (1.2)  1.97 (0.21 to 18.0)    94 (1.1)  0 (0.0)  —    Family history of non-Hodgkin lymphoma   No  3057 (91.3)  68 (77.3)  1.00 (referent)  .517  9501 (91.8)  111 (91.0)  1.00 (referent)  .272   Yes  40 (1.2)  2 (2.3)  1.71 (0.37 to 7.91)    229 (2.2)  1 (0.8)  0.38 (0.05 to 2.83)    Family history of leukemia   No  3451 (91.6)  74 (80.4)  1.00 (referent)  .088  9409 (90.9)  107 (87.7)  1.00 (referent)  .644   Yes  65 (1.7)  0 (0.0)  —    321 (3.1)  5 (4.1)  1.26 (0.49 to 3.21)    * CI = confidence interval; NHL = non-Hodgkin lymphoma; OR = odds ratio. † The counts do not add up to the total number of cases/controls due to data missing by design or report. ‡ Adjusted for age, sex, race/ethnicity, and study. § Atopic disorders include asthma, eczema, hay fever, or other allergies, excluding drug allergies. || History of allergy included plant, food, animal, dust, insect, or mold allergy. ¶ Eczema, with or without other atopic conditions. # Eczema alone, excluding participants who reported eczema and other atopic conditions. View Large We observed an elevated risk of BL among older participants who reported of a history of hepatitis C virus (HCV) seropositivity (OR = 4.1; 95% CI = 1.10 to 15.4), based on three exposed cases in the six studies that reported HCV serostatus (Table 2). The relationship between BL and HCV seropositivity in younger participants was indeterminate because none of the 31 younger cases reported a seropositive history. A history of prior blood transfusion (yes vs no) was unrelated to BL in younger participants but was inversely associated with BL risk in older participants. Younger participants who reported receiving three or more transfusions had an elevated risk of BL in (OR = 6.46; 95% CI = 1.75 to 23.8), but this result was based on only three exposed cases and the risk was not increased in the older participants with higher numbers of transfusions (Table 2). Peptic ulcer and hormone use were not associated with BL in younger or older participants (data not shown). The risk of BL in younger or older participants was not associated with a history of NHL or leukemia among first-degree relatives, but the number of cases was small in both groups (Table 2). With respect to anthropometric factors, the risk of BL doubled in the tallest participants (quartile 4) compared with the shortest ones (quartile 1), both in the younger (OR = 2.14; 95% CI = 1.07 to 4.25) and the older (OR = 1.79; 95% CI = 0.92 to 3.49) age groups (Table 3). BL was not associated with usual weight or body mass index in younger participants, but a non-significant inverse association was observed between BL and body mass index in older participants (Ptrend = .07). With respect to lifestyle factors, the risks for both younger and older BL were inversely associated with alcohol consumption (Table 3), particularly among older participants. A history of cigarette smoking was not associated with BL in either younger or older participants (Table 3). We observed a non-significantly elevated risk of BL among younger participants who reported the use of light-colored hair dye compared with never use (OR = 3.0; 95% CI = 0.91 to 9.9), but the association with BL among older participants was indeterminate because only one older case was exposed. BL among older participants was not associated with the use of dark hair dyes (OR = 1.29; 95% CI = 0.46 to 3.63) based on nine exposed cases, and among younger participants, only two cases were exposed. BL was not associated with recreational sun exposure in either younger or older participants (Table 3). Table 3. Association of anthropometry and lifestyle factors with sporadic Burkitt lymphoma in the InterLymph NHL Subtypes Project from the basic model, stratified by age*   <50 years  ≥50 years  Controls  Cases  OR (95% CI)‡  P  Controls  Cases  OR (95% CI)‡  P  N (%)†  N (%)†  N (%)†  N (%)†  Usual adult height§   Quartile 1 (low)  816 (17.1)  12 (12.0)   1.00 (referent)  .029  3039 (26.7)  19 (20.9)   1.00 (referent)  .301   Quartile 2  979 (20.5)  14 (14.0)   1.03 (0.46 to 2.28)    2693 (23.7)  22 (24.2)   1.57 (0.83 to 2.97)     Quartile 3  1174 (24.6)  21 (21.0)   1.27 (0.60 to 2.70)    2703 (23.8)  24 (26.4)   1.66 (0.87 to 3.15)     Quartile 4 (high)  1612 (33.8)  47 (47.0)   2.14 (1.07 to 4.25)    2528 (22.2)  24 (26.4)   1.79 (0.92 to 3.49)    Usual adult weight||   Quartile 1 (low)  1342 (28.2)  22 (22.0)   1.00 (referent)  .294  2452 (21.6)  24 (26.4)   1.00 (referent)  .636   Quartile 2  1122 (23.6)  23 (23.0)   1.26 (0.68 to 2.33)    2555 (22.5)  22 (24.2)   0.93 (0.51 to 1.68)     Quartile 3  1102 (23.1)  29 (29.0)   1.67 (0.93 to 3.00)    3032 (26.7)  19 (20.9)   0.68 (0.37 to 1.27)     Quartile 4 (high)  1015 (21.3)  20 (20.0)   1.05 (0.54 to 2.02)    2924 (25.7)  24 (26.4)   0.80 (0.43 to 1.46)    Usual adult body mass index (kg/m2)   15–<18.5  105 (2.2)  1 (1.0)   0.49 (0.07 to 3.77)    146 (1.3)  3 (3.3)   1.94 (0.55 to 6.89)     18.5–<22.5  1320 (27.7)  24 (24.0)   1.00 (referent)  .71  1879 (16.5)  19 (20.9)   1.00 (referent)  .07   22.5–<25  1250 (26.2)  31 (31.0)   1.31 (0.75 to 2.29)    2724 (24.0)  20 (22.0)   0.68 (0.36 to 1.29)     25–<30  1434 (30.1)  27 (27.0)   0.91 (0.50 to 1.65)    4415 (38.8)  28 (30.8)   0.52 (0.28 to 0.96)     30–<35  345 (7.2)  9 (9.0)   1.11 (0.49 to 2.56)    1344 (11.8)  17 (18.7)   1.08 (0.54 to 2.14)     35–50  127 (2.7)  2 (2.0)   0.73 (0.16 to 3.24)    455 (4.0)  2 (2.2)   0.37 (0.08 to 1.66)    Alcohol consumption status 2 years prior to diagnosis/interview   Non-drinker  1065 (23.4)  32 (29.9)   1.00 (referent)  .211  3103 (23.4)  54 (36.0)   1.00 (referent)  .05   Former drinker  96 (2.1)  0 (0.0)  —    468 (3.5)  2 (1.3)   0.48 (0.10 to 2.25)     Current drinker  1394 (30.7)  22 (20.6)   0.75 (0.36 to 1.57)    3335 (25.1)  21 (14.0)   0.44 (0.21 to 0.91)     Drinker, status unknown  1480 (32.6)  38 (35.5)   0.68 (0.39 to 1.20)    3240 (24.4)  53 (35.3)   0.65 (0.41 to 1.03)    Age at first alcohol consumption   Non-drinker  1065 (23.4)  32 (29.9)   1.00 (referent)  .192  3103 (23.4)  54 (36.0)   1.00 (referent)  .07   <20 years  662 (14.6)  13 (12.1)   1.26 (0.51 to 3.12)    1478 (11.1)  7 (4.7)   0.38 (0.15 to 0.98)     20–29 years  1045 (23.0)  11 (10.3)   0.48 (0.19 to 1.19)    1801 (13.6)  15 (10.0)   0.58 (0.28 to 1.19)     ≥30 years  102 (2.2)  2 (1.9)   1.10 (0.24 to 5.14)    654 (4.9)  3 (2.0)   0.36 (0.10 to 1.23)     Drinker, age start unknown  1161 (25.6)  34 (31.8)   0.63 (0.35 to 1.16)    3110 (23.4)  51 (34.0)   0.65 (0.41 to 1.05)    Duration of alcohol consumption¶  6048 (100.0)  133 (100.0)   0.98 (0.94 to 1.02)  .353  15086 (100.0)  159 (100.0)   0.98 (0.96 to 1.00)  .047  Ethanol per week as an adult, consumed from any type of alcoholic beverage#   Non-drinker  1065 (23.4)  32 (29.9)   1.00 (referent)  .409  3103 (23.4)  54 (36.0)   1.00 (referent)  .043   Q1 (low)  730 (16.1)  22 (20.6)   0.81 (0.45 to 1.45)    1508 (11.4)  24 (16.0)   0.75 (0.45 to 1.27)     Q2  676 (14.9)  17 (15.9)   0.83 (0.44 to 1.58)    1532 (11.5)  13 (8.7)   0.42 (0.22 to 0.80)     Q3  670 (14.8)  10 (9.3)   0.56 (0.26 to 1.18)    1548 (11.7)  21 (14.0)   0.69 (0.40 to 1.20)     Q4 (high)  683 (15.0)  10 (9.3)   0.57 (0.26 to 1.25)    1682 (12.7)  17 (11.3)   0.51 (0.27 to 0.94)     Drinker, grams unknown  211 (4.6)  1 (0.9)   0.19 (0.02 to 2.42)    773 (5.8)  1 (0.7)   0.16 (0.01 to 2.26)    Lifetime alcohol consumed   Non-drinker  1065 (23.4)  32 (29.9)  1.00 (referent)  .604  3103 (23.4)  54 (36.0)   1.00 (referent)  .025   1–100 kg  581 (12.8)  10 (9.3)  1.02 (0.40 to 2.55)    765 (5.8)  8 (5.3)   0.90 (0.36 to 2.24)     101–200 kg  226 (5.0)  2 (1.9)  0.56 (0.12 to 2.68)    404 (3.0)  2 (1.3)   0.37 (0.08 to 1.67)     201–400 kg  150 (3.3)  2 (1.9)  0.83 (0.17 to 4.01)    497 (3.7)  2 (1.3)   0.23 (0.05 to 1.06)     >400 kg  116 (2.6)  2 (1.9)  1.10 (0.23 to 5.28)    640 (4.8)  3 (2.0)   0.22 (0.06 to 0.86)     Drinker, consumption unknown  1897 (41.8)  44 (41.1)  0.63 (0.37 to 1.06)    4737 (35.7)  61 (40.7)   0.63 (0.40 to 0.98)    Cigarette smoking status 2 years prior to diagnosis/interview   Non-smoker  2511 (43.2)  68 (53.1)  1.00 (referent)  .552  5760 (39.8)  58 (37.7)  1.00 (referent)  .912   Former smoker  1075 (18.5)  19 (14.8)  0.85 (0.5 to 1.47)    4777 (33.0)  55 (35.7)  0.92 (0.62 to 1.34)     Current smoker  1774 (30.5)  29 (22.7)  0.72 (0.45 to 1.14)    2645 (18.3)  29 (18.8)  0.88 (0.54 to 1.42)     Smoker, status unknown  125 (2.2)  2 (1.6)  0.73 (0.16 to 3.37)    399 (2.8)  5 (3.2)  1.21 (0.41 to 3.56)    Color of hair dye used   Never hair dye  426 (13.3)  6 (9.7)  1.00 (referent)  .007  1318 (17.5)  7 (12.7)   1.00 (referent)  .291   Light  189 (5.9)  8 (12.9)  2.99 (0.91 to 9.88)    690 (9.2)  1 (1.8)   0.26 (0.03 to 2.16)     Dark  407 (12.7)  2 (3.2)  0.35 (0.06 to 1.92)    1319 (17.5)  9 (16.4)   1.29 (0.46 to 3.63)     Ever hair dye, color unknown  116 (3.6)  1 (1.6)  0.15 (0.01 to 1.89)    310 (4.1)  2 (3.6)   0.57 (0.07 to 4.98)     Male**  1995 (62.1)  44 (71.0)  —    3716 (49.4)  35 (63.6)  —    Recreational sun exposure††   Quartile 1 (low)  409 (16.1)  7 (13.7)  1.00 (referent)  .930  1425 (22.0)  12 (28.6)  1.00 (referent)  .725   Quartile 2  654 (25.7)  13 (25.5)  1.16 (0.44 to 3.00)    1324 (20.5)  7 (16.7)  0.61 (0.24 to 1.56)     Quartile 3  445 (17.5)  10 (19.6)  1.17 (0.43 to 3.19)    1190 (18.4)  8 (19)  0.80 (0.32 to 2.00)     Quartile 4 (high)  726 (28.5)  13 (25.5)  0.92 (0.36 to 2.39)    1729 (26.7)  10 (23.8)  0.66 (0.28 to 1.57)      <50 years  ≥50 years  Controls  Cases  OR (95% CI)‡  P  Controls  Cases  OR (95% CI)‡  P  N (%)†  N (%)†  N (%)†  N (%)†  Usual adult height§   Quartile 1 (low)  816 (17.1)  12 (12.0)   1.00 (referent)  .029  3039 (26.7)  19 (20.9)   1.00 (referent)  .301   Quartile 2  979 (20.5)  14 (14.0)   1.03 (0.46 to 2.28)    2693 (23.7)  22 (24.2)   1.57 (0.83 to 2.97)     Quartile 3  1174 (24.6)  21 (21.0)   1.27 (0.60 to 2.70)    2703 (23.8)  24 (26.4)   1.66 (0.87 to 3.15)     Quartile 4 (high)  1612 (33.8)  47 (47.0)   2.14 (1.07 to 4.25)    2528 (22.2)  24 (26.4)   1.79 (0.92 to 3.49)    Usual adult weight||   Quartile 1 (low)  1342 (28.2)  22 (22.0)   1.00 (referent)  .294  2452 (21.6)  24 (26.4)   1.00 (referent)  .636   Quartile 2  1122 (23.6)  23 (23.0)   1.26 (0.68 to 2.33)    2555 (22.5)  22 (24.2)   0.93 (0.51 to 1.68)     Quartile 3  1102 (23.1)  29 (29.0)   1.67 (0.93 to 3.00)    3032 (26.7)  19 (20.9)   0.68 (0.37 to 1.27)     Quartile 4 (high)  1015 (21.3)  20 (20.0)   1.05 (0.54 to 2.02)    2924 (25.7)  24 (26.4)   0.80 (0.43 to 1.46)    Usual adult body mass index (kg/m2)   15–<18.5  105 (2.2)  1 (1.0)   0.49 (0.07 to 3.77)    146 (1.3)  3 (3.3)   1.94 (0.55 to 6.89)     18.5–<22.5  1320 (27.7)  24 (24.0)   1.00 (referent)  .71  1879 (16.5)  19 (20.9)   1.00 (referent)  .07   22.5–<25  1250 (26.2)  31 (31.0)   1.31 (0.75 to 2.29)    2724 (24.0)  20 (22.0)   0.68 (0.36 to 1.29)     25–<30  1434 (30.1)  27 (27.0)   0.91 (0.50 to 1.65)    4415 (38.8)  28 (30.8)   0.52 (0.28 to 0.96)     30–<35  345 (7.2)  9 (9.0)   1.11 (0.49 to 2.56)    1344 (11.8)  17 (18.7)   1.08 (0.54 to 2.14)     35–50  127 (2.7)  2 (2.0)   0.73 (0.16 to 3.24)    455 (4.0)  2 (2.2)   0.37 (0.08 to 1.66)    Alcohol consumption status 2 years prior to diagnosis/interview   Non-drinker  1065 (23.4)  32 (29.9)   1.00 (referent)  .211  3103 (23.4)  54 (36.0)   1.00 (referent)  .05   Former drinker  96 (2.1)  0 (0.0)  —    468 (3.5)  2 (1.3)   0.48 (0.10 to 2.25)     Current drinker  1394 (30.7)  22 (20.6)   0.75 (0.36 to 1.57)    3335 (25.1)  21 (14.0)   0.44 (0.21 to 0.91)     Drinker, status unknown  1480 (32.6)  38 (35.5)   0.68 (0.39 to 1.20)    3240 (24.4)  53 (35.3)   0.65 (0.41 to 1.03)    Age at first alcohol consumption   Non-drinker  1065 (23.4)  32 (29.9)   1.00 (referent)  .192  3103 (23.4)  54 (36.0)   1.00 (referent)  .07   <20 years  662 (14.6)  13 (12.1)   1.26 (0.51 to 3.12)    1478 (11.1)  7 (4.7)   0.38 (0.15 to 0.98)     20–29 years  1045 (23.0)  11 (10.3)   0.48 (0.19 to 1.19)    1801 (13.6)  15 (10.0)   0.58 (0.28 to 1.19)     ≥30 years  102 (2.2)  2 (1.9)   1.10 (0.24 to 5.14)    654 (4.9)  3 (2.0)   0.36 (0.10 to 1.23)     Drinker, age start unknown  1161 (25.6)  34 (31.8)   0.63 (0.35 to 1.16)    3110 (23.4)  51 (34.0)   0.65 (0.41 to 1.05)    Duration of alcohol consumption¶  6048 (100.0)  133 (100.0)   0.98 (0.94 to 1.02)  .353  15086 (100.0)  159 (100.0)   0.98 (0.96 to 1.00)  .047  Ethanol per week as an adult, consumed from any type of alcoholic beverage#   Non-drinker  1065 (23.4)  32 (29.9)   1.00 (referent)  .409  3103 (23.4)  54 (36.0)   1.00 (referent)  .043   Q1 (low)  730 (16.1)  22 (20.6)   0.81 (0.45 to 1.45)    1508 (11.4)  24 (16.0)   0.75 (0.45 to 1.27)     Q2  676 (14.9)  17 (15.9)   0.83 (0.44 to 1.58)    1532 (11.5)  13 (8.7)   0.42 (0.22 to 0.80)     Q3  670 (14.8)  10 (9.3)   0.56 (0.26 to 1.18)    1548 (11.7)  21 (14.0)   0.69 (0.40 to 1.20)     Q4 (high)  683 (15.0)  10 (9.3)   0.57 (0.26 to 1.25)    1682 (12.7)  17 (11.3)   0.51 (0.27 to 0.94)     Drinker, grams unknown  211 (4.6)  1 (0.9)   0.19 (0.02 to 2.42)    773 (5.8)  1 (0.7)   0.16 (0.01 to 2.26)    Lifetime alcohol consumed   Non-drinker  1065 (23.4)  32 (29.9)  1.00 (referent)  .604  3103 (23.4)  54 (36.0)   1.00 (referent)  .025   1–100 kg  581 (12.8)  10 (9.3)  1.02 (0.40 to 2.55)    765 (5.8)  8 (5.3)   0.90 (0.36 to 2.24)     101–200 kg  226 (5.0)  2 (1.9)  0.56 (0.12 to 2.68)    404 (3.0)  2 (1.3)   0.37 (0.08 to 1.67)     201–400 kg  150 (3.3)  2 (1.9)  0.83 (0.17 to 4.01)    497 (3.7)  2 (1.3)   0.23 (0.05 to 1.06)     >400 kg  116 (2.6)  2 (1.9)  1.10 (0.23 to 5.28)    640 (4.8)  3 (2.0)   0.22 (0.06 to 0.86)     Drinker, consumption unknown  1897 (41.8)  44 (41.1)  0.63 (0.37 to 1.06)    4737 (35.7)  61 (40.7)   0.63 (0.40 to 0.98)    Cigarette smoking status 2 years prior to diagnosis/interview   Non-smoker  2511 (43.2)  68 (53.1)  1.00 (referent)  .552  5760 (39.8)  58 (37.7)  1.00 (referent)  .912   Former smoker  1075 (18.5)  19 (14.8)  0.85 (0.5 to 1.47)    4777 (33.0)  55 (35.7)  0.92 (0.62 to 1.34)     Current smoker  1774 (30.5)  29 (22.7)  0.72 (0.45 to 1.14)    2645 (18.3)  29 (18.8)  0.88 (0.54 to 1.42)     Smoker, status unknown  125 (2.2)  2 (1.6)  0.73 (0.16 to 3.37)    399 (2.8)  5 (3.2)  1.21 (0.41 to 3.56)    Color of hair dye used   Never hair dye  426 (13.3)  6 (9.7)  1.00 (referent)  .007  1318 (17.5)  7 (12.7)   1.00 (referent)  .291   Light  189 (5.9)  8 (12.9)  2.99 (0.91 to 9.88)    690 (9.2)  1 (1.8)   0.26 (0.03 to 2.16)     Dark  407 (12.7)  2 (3.2)  0.35 (0.06 to 1.92)    1319 (17.5)  9 (16.4)   1.29 (0.46 to 3.63)     Ever hair dye, color unknown  116 (3.6)  1 (1.6)  0.15 (0.01 to 1.89)    310 (4.1)  2 (3.6)   0.57 (0.07 to 4.98)     Male**  1995 (62.1)  44 (71.0)  —    3716 (49.4)  35 (63.6)  —    Recreational sun exposure††   Quartile 1 (low)  409 (16.1)  7 (13.7)  1.00 (referent)  .930  1425 (22.0)  12 (28.6)  1.00 (referent)  .725   Quartile 2  654 (25.7)  13 (25.5)  1.16 (0.44 to 3.00)    1324 (20.5)  7 (16.7)  0.61 (0.24 to 1.56)     Quartile 3  445 (17.5)  10 (19.6)  1.17 (0.43 to 3.19)    1190 (18.4)  8 (19)  0.80 (0.32 to 2.00)     Quartile 4 (high)  726 (28.5)  13 (25.5)  0.92 (0.36 to 2.39)    1729 (26.7)  10 (23.8)  0.66 (0.28 to 1.57)    * CI = confidence interval; NHL = non-Hodgkin lymphoma; OR = odds ratio. † The counts do not add up to the total number of cases/controls due to data missing by design or report. ‡ Adjusted for age, sex, race/ethnicity, and study. § Height quartile cutoffs are: 172, 177.8, and 182cm for Q1-2, Q2-3, and Q3-4, respectively, for males, and 159, 163.0, and 168cm, respectively, for females. || Weight quartile cutoffs are: 72.6, 80, and 89kg for Q1-2, Q2-3, and Q3-4, respectively, for males, and 58.1, 65, and 74.8, respectively, for females. ¶ Adjusted for age, sex, race/ethnicity, and study. # Alcohol quartile cutoff points: 44.4, 110.7, and 252g, respectively, for Q1-2, Q2-3, and Q3-4, respectively. ** Males were not included in the analysis of use of hair dye. †† Recreational sun exposure (hours per week, study-specific quartiles available upon request). View Large Among 31 occupations evaluated, we observed an increased risk of BL among younger participants who reported employment as a cleaner (OR = 2.6; 95% CI = 1.01 to 6.83), especially a char worker cleaner (OR = 3.8; 95% CI = 1.26 to 11.3) based on four exposed cases (Table 4). A char worker cleaner is a person employed to clean and maintain the interiors of buildings. Occupation as a cleaner was not associated with BL among older participants nor was any other occupation associated with BL in younger or older participants (data not shown). Table 4. Association of cleaning-related occupations with sporadic Burkitt lymphoma in the InterLymph NHL Subtypes Project from the basic model, stratified by age*   <50 years  ≥50 years    Controls  Cases      Controls  Cases        N (%)†  N (%)†  OR (95% CI)‡  P  N (%)†  N (%)†  OR (95% CI)‡  P  Cleaners   No  3026 (88.5)  59 (85.5)  1.00 (referent)  .077  6721 (94.5)  54 (96.4)  1.00 (referent)  .863   Yes  137 (4.0)  5 (7.2)  2.62 (1.01 to 6.83)    337 (4.7)  2 (3.6)  0.88 (0.21 to 3.70)    Duration of employment as cleaner   Never  3026 (88.5)  59 (85.5)  1.00 (referent)  .158  6721 (94.5)  54 (96.4)  1.00 (referent)  .051   1–10 years  109 (3.2)  5 (7.2)  3.27 (1.24 to 8.60)    188 (2.6)  0 (0.0)  —     >10 years  23 (0.7)  0 (0.0)  —    143 (2.0)  1 (1.8)  1.14 (0.15 to 8.48)     Yes, missing duration  5 (0.1)  0 (0.0)  —    6 (0.1)  1 (1.8)  – (3.69 to infinity)    Charworker cleaner or related work§   No  3071 (89.8)  60 (87.0)  1.00 (referent)  .040  6473 (96.2)  52 (100.0)  1.00 (referent)  .124   Yes  86 (2.5)  4 (5.8)  3.76 (1.26 to 11.3)    203 (3.0)  0 (0.0)  —    Duration of employment as charworker cleaner   Never  3071 (89.8)  60 (87.0)  1.00 (referent)  .095  6473 (96.2)  52 (100.0)  1.00 (referent)  .500   1–10 years  64 (1.9)  4 (5.8)  5.00 (1.65 to 15.21)    103 (1.5)  0 (0.0)  —     >10 years  18 (0.5)  0 (0.0)  —    99 (1.5)  0 (0.0)  —     Yes, missing duration  4 (0.1)  0 (0.0)  —    1 (0.0)  0 (0.0)  —      <50 years  ≥50 years    Controls  Cases      Controls  Cases        N (%)†  N (%)†  OR (95% CI)‡  P  N (%)†  N (%)†  OR (95% CI)‡  P  Cleaners   No  3026 (88.5)  59 (85.5)  1.00 (referent)  .077  6721 (94.5)  54 (96.4)  1.00 (referent)  .863   Yes  137 (4.0)  5 (7.2)  2.62 (1.01 to 6.83)    337 (4.7)  2 (3.6)  0.88 (0.21 to 3.70)    Duration of employment as cleaner   Never  3026 (88.5)  59 (85.5)  1.00 (referent)  .158  6721 (94.5)  54 (96.4)  1.00 (referent)  .051   1–10 years  109 (3.2)  5 (7.2)  3.27 (1.24 to 8.60)    188 (2.6)  0 (0.0)  —     >10 years  23 (0.7)  0 (0.0)  —    143 (2.0)  1 (1.8)  1.14 (0.15 to 8.48)     Yes, missing duration  5 (0.1)  0 (0.0)  —    6 (0.1)  1 (1.8)  – (3.69 to infinity)    Charworker cleaner or related work§   No  3071 (89.8)  60 (87.0)  1.00 (referent)  .040  6473 (96.2)  52 (100.0)  1.00 (referent)  .124   Yes  86 (2.5)  4 (5.8)  3.76 (1.26 to 11.3)    203 (3.0)  0 (0.0)  —    Duration of employment as charworker cleaner   Never  3071 (89.8)  60 (87.0)  1.00 (referent)  .095  6473 (96.2)  52 (100.0)  1.00 (referent)  .500   1–10 years  64 (1.9)  4 (5.8)  5.00 (1.65 to 15.21)    103 (1.5)  0 (0.0)  —     >10 years  18 (0.5)  0 (0.0)  —    99 (1.5)  0 (0.0)  —     Yes, missing duration  4 (0.1)  0 (0.0)  —    1 (0.0)  0 (0.0)  —    * CI = confidence interval; NHL = non-Hodgkin lymphoma; OR = odds ratio. † The counts do not add up to the total number of cases/controls due to data missing by design or report. ‡ OR (95% CI): adjusted for age, sex, race/ethnicity, and study. § Charworker cleaner is a person who is employed to clean and maintain the interiors of buildings. View Large In the final model, BL in younger participants was associated with a history of allergy (OR = 0.58; 95% CI = 0.32 to 1.05), eczema without other atopic conditions (OR = 2.54; 95% CI = 1.20 to 5.40), taller height (OR = 2.17; 95% CI = 1.08 to 4.36), the use of light-colored hair dye (OR = 2.89; 95% CI = 0.84 to 9.94), and working in a cleaning occupation (OR = 3.49; 95% CI = 1.13 to 10.7) (Table 5). BL in older participants was independently associated with a history of HCV infection (OR = 4.19; 95% CI = 1.05 to 16.6), usual adult body mass index (Ptrend = .049), and consumption of at least one drink of alcohol per month (OR = 0.63; 95% CI = 0.40 to 0.98). Table 5. Independent risk factors for younger and older sporadic Burkitt lymphoma in the InterLymph NHL Subtypes Project from the final model*    OR (95% CI)  P  <50 years   Allergy†   No  1.00 (referent)  .065   Yes  0.58 (0.32 to 10.5)     Eczema without other atopic conditions   No eczema  1.00     Eczema with no other atopic conditions  2.54 (1.20 to 5.40)     Eczema with other atopic conditions  0.51 (0.15 to 1.74)  .041   Usual adult height‡   Quartile 1 (low)  1.00 (referent)  .028   Quartile 2  1.03 (0.46 to 2.30)     Quartile 3  1.31 (0.62 to 2.80)     Quartile 4  2.17 (1.08 to 4.36)     Color of hair dye used   Never hair dye  1.00 (referent)  .014   Light  2.89 (0.84 to 9.94)     Dark  0.37 (0.06 to 2.06)     Charworker cleaner or related work§   No  1.00 (referent)  .054   Yes  3.49 (1.13 to 10.7)    ≥50 years   Hepatitis C virus infection   Negative  1.00 (referent)  .070   Positive  4.19 (1.05 to 16.61)     Usual adult body mass index (kg/m2)   15–<18.5  1.00 (referent)  .049   18.5–<22.5  0.55 (0.15 to 1.97)     22.5–<25  0.37 (0.10 to 1.32)     25–<30  0.27 (0.08 to 0.98)     30–<35  0.56 (0.15 to 2.08)     35–50  0.16 (0.02 to 1.05)     History of alcohol consumption   Non-drinker  1.00 (referent)  .001   Drinker (at least 1 drink per month)  0.63 (0.40 to 0.98)       OR (95% CI)  P  <50 years   Allergy†   No  1.00 (referent)  .065   Yes  0.58 (0.32 to 10.5)     Eczema without other atopic conditions   No eczema  1.00     Eczema with no other atopic conditions  2.54 (1.20 to 5.40)     Eczema with other atopic conditions  0.51 (0.15 to 1.74)  .041   Usual adult height‡   Quartile 1 (low)  1.00 (referent)  .028   Quartile 2  1.03 (0.46 to 2.30)     Quartile 3  1.31 (0.62 to 2.80)     Quartile 4  2.17 (1.08 to 4.36)     Color of hair dye used   Never hair dye  1.00 (referent)  .014   Light  2.89 (0.84 to 9.94)     Dark  0.37 (0.06 to 2.06)     Charworker cleaner or related work§   No  1.00 (referent)  .054   Yes  3.49 (1.13 to 10.7)    ≥50 years   Hepatitis C virus infection   Negative  1.00 (referent)  .070   Positive  4.19 (1.05 to 16.61)     Usual adult body mass index (kg/m2)   15–<18.5  1.00 (referent)  .049   18.5–<22.5  0.55 (0.15 to 1.97)     22.5–<25  0.37 (0.10 to 1.32)     25–<30  0.27 (0.08 to 0.98)     30–<35  0.56 (0.15 to 2.08)     35–50  0.16 (0.02 to 1.05)     History of alcohol consumption   Non-drinker  1.00 (referent)  .001   Drinker (at least 1 drink per month)  0.63 (0.40 to 0.98)    * Table reports results from the final stepwise regression analysis models. CI = confidence interval; NHL = non-Hodgkin lymphoma; OR = odds ratio. † History of allergy includes participants who reported eczema plus other atopic conditions. ‡ Height quartile cutoffs are: 172, 177.8, and 182cm for Q1-2, Q2-3, and Q3-4, respectively, for males, and 159, 163.0, and 168cm, respectively, for females. § Charworker cleaner is a person who is employed to clean and maintain the interior of buildings. View Large The associations with BL found in the age-specific analyses were attenuated or became statistically non-significant when the histological subtypes of BL and BLL were analyzed individually or with the younger and older cases combined (data not shown). There was no evidence of significant interstudy heterogeneity across the studies for the associations found in this study (data not shown). Discussion Our study, which is the first to evaluate a broad range of noninfectious risk factors for BL, showed some differences and similarities between BL in younger and older participants. Specifically, we observed significant inverse associations between BL in younger participants and a history of allergy, and significant positive associations with a history of eczema alone and working in a cleaning occupation, especially as a char worker cleaner. Conversely, among older participants, we observed a positive association with a history of HCV infection based on three exposed cases. Among both younger and older participants, BL was positively associated with height and inversely associated with alcohol consumption. These associations were attenuated or not statistically significant when the histological subtypes of typical BL and BLL were analyzed individually or when younger and older cases were combined. Our results provide epidemiological support for the hypothesis that younger and older adult sporadic BL may be distinct biologically or etiologically (11,12). Our results agree with recent epidemiologic and clinical studies that reported multiple incidence peaks and different outcomes by age (6,10–13,15,21), all suggesting the possibility of etiologically and clinically distinct BL entities at different ages. Because no single parameter is a gold standard for BL diagnosis, and because the diagnosis of BL may be difficult, particularly in older patients (22), diagnostic uncertainty may be a factor in our results. Expert hematopathologists agree on the diagnosis of BL in 80%–90% of pediatric cases, but in only 26%–48% of adult cases (22), in part because the classification of older adult BL has been in some flux during the period of the study (1). Thus, some cases previously diagnosed as BLL might now be reclassified as BL or as a gray-zone lymphoma with features intermediate between BL and diffuse large B-cell lymphoma (4). Gray-zone lymphoma, which is characterized by a pleomorphic tumor cell morphology and complex cytogenetics, sometimes including a combination of c-MYC and BCL2 or BCL6 gene rearrangements (referred to as “double hit” lymphoma) (23), is overrepresented in older patients and has an extremely poor prognosis with standard treatment (24). Further studies are needed to confirm the age-related BL entities and to elucidate their molecular abnormalities. The significant inverse association between younger BL and a history of allergy mirrors the associations that have been reported for diffuse large B-cell lymphoma and follicular lymphoma (25). Allergic diseases appear to be protective against certain NHL subtypes, but the mechanism is unknown. Assuming these results are valid, protective effects could be mediated via immunological hypersensitivity (26) or antitumor cytotoxicity (27). We found a significant positive association between a history of HCV infection and BL only in older participants, based on three cases of BL with HCV infection. This result agrees with the fivefold risk for BL reported among elderly patients in US Medicare data who had two or more insurance claims for HCV infection (28). Although HCV and HIV coinfection are common, particularly in intravenous drug users, coinfection with HIV is unlikely to explain our results because serologically confirmed HIV-positive cases were excluded in the cases in our study. Because HCV infection may increase risk for some NHL subtypes (29), perhaps by inducing chronic immune activation (30), further studies are needed to investigate the potential role of HCV infection in older adult BL. BL in both younger and older participants was positively associated with height. This association has also been reported for other cancers (31,32) and might be indicative of the role of early-life exposures that influence height and also impact risk for cancer, such as insulin-like growth factors. Insulin-like growth factors are correlated with adult height and are thought to modulate cell proliferation and/or turnover (33,34). Our finding that the risk for BL was decreased in both younger and older participants who consumed alcohol is in accord with a previous report using much of the same data (35), but it is unexplained. In contrast to the previous reports of a positive association between use of dark hair dye and NHL risk (36–40), we found a positive association between the use of light-colored hair dye and BL only in younger participants. These results are conflicting and highlight the difficulty of evaluating hair dye use in rare cancers such as BL. A history of working in cleaning occupations, especially as a char worker cleaner, was positively associated with BL in younger participants. This result is similar to the associations reported for all NHL (41) and may point to a role for chemicals that are found in products used for cleaning. The strengths of our pooled analysis include having relatively large case numbers from geographically diverse areas and centrally harmonized data classification and analysis procedures. Because up to one-third of BL cases may be HIV-associated, exclusion of HIV infected cases enabled us to focus our interpretation on adult sporadic BL. The limitations include possible selection and recall biases common to case–control studies, and possible diagnostic errors related to the use of older lymphoma classification systems such as the Working Formulation (16,17) and the 2001 WHO classification for hematologic malignancies (42). Lack of access to archival tissues and slides precluded a central pathology review to confirm and update the diagnoses (1). Lack of tumor Epstein–Barr virus status or molecular characterization also precluded us from evaluating whether Epstein–Barr virus or molecular abnormalities are correlated with the epidemiological clues for distinct BL biology and/or etiology (43). Other limitations include multiple significance tests, which increases the number of expected false-positive findings, and missing data, for example, for HCV infection status, which could have reduced the power to detect weak associations. To summarize, we found both similar and contrasting age-specific patterns of associations for BL with medical history, anthropometric, lifestyle, and occupational risk factors in younger and older participants. These results support the hypothesis that BL in younger and older patients may be etiologically distinct. Funding This pooled analysis was supported by the Intramural Research Program of the National Cancer Institute/National Institutes of Health and National Cancer Institute/National Institutes of Health (R01 CA14690, U01 CA118444, and R01 CA92153-S1). InterLymph annual meetings during 2010–2013 were supported by the Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute/National Institutes of Health (2010–2013); Lymphoma Coalition (2010–2013); National Institutes of Health Office of Rare Diseases Research (2010); National Cancer Institute/National Institutes of Health (R13 CA159842 01) (2011); University of Cagliari, Provincial Administration of Cagliari, Banca di Credito Sardo, and Consorzio Industriale Sardo, Italy (2011); Intramural Research Program of the National Cancer Institute/National Institutes of Health (2012); and Faculté de Médecine de Dijon, Institut de Veille Sanitaire, Registre des hémopathies malignes de Côte d’Or, INSERM, Institut National du Cancer, Université de Bourgogne, Groupe Ouest Est d’Etude des Leucémies et Autres Maladies du Sang (GOELAMS), l’Institut Bergonié, The Lymphoma Study Association (LYSA), Registre Régional des Hémopathies de Basse Normandie, and the City of Dijon, France (2013). Meeting space at the 2013 Annual Meeting of the American Association for Cancer Research (AACR) was provided by the Molecular Epidemiology Group (MEG) of the AACR. Individual studies were supported by: the Canadian Institutes for Health Research (CIHR), Canadian Cancer Society, and Michael Smith Foundation for Health Research (British Columbia); Intramural Research Program of the National Cancer Institute/National Institutes of Health (Iowa/Minnesota); National Cancer Institute/National Institutes of Health (N01-CP-ES-11027) (Kansas); National Cancer Institute/National Institutes of Health (R01 CA50850) (Los Angeles); National Cancer Institute/National Institutes of Health (R01 CA92153 and P50 CA97274), Lymphoma Research Foundation (164738), and the Henry J. Predolin Foundation (Mayo Clinic); Intramural Research Program of the National Cancer Institute/National Institutes of Health and Public Health Service (contracts N01-PC-65064, N01-PC-67008, N01-PC-67009, N01-PC-67010, and N02-PC-71105) (NCI-SEER); National Cancer Institute/National Institutes of Health (R01CA100555 and R03CA132153) and American Institute for Cancer Research (99B083) (Nebraska [newer]); National Cancer Institute/National Institutes of Health (N01-CP-95618) and State of Nebraska Department of Health (LB-506) (Nebraska [older]); National Cancer Institute/National Institutes of Health (R01CA45614, RO1CA154643-01A1, and R01CA104682) (UCSF1); National Cancer Institute/National Institutes of Health (CA143947, CA150037, R01CA087014, R01CA104682, RO1CA122663, and RO1CA154643-01A1) (UCSF2); National Heart Lung and Blood Institute/National Institutes of Health (hematology training grant award T32 HL007152), National Center for Research Resources/National Institutes of Health (UL 1 RR024160), and National Cancer Institute/National Institutes of Health (K23 CA102216 and P50 CA130805) (University of Rochester); National Cancer Institute/National Institutes of Health (CA62006 and CA165923) (Yale); Association pour la Recherche contre le Cancer, Fondation de France, AFSSET, and a donation from Faberge employees (Engela); European Commission (QLK4-CT-2000-00422 and FOOD-CT-2006-023103), Spanish Ministry of Health (CIBERESP, PI11/01810, 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, 2009SGR1026), 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, Cancer Research, Ireland, and Czech Republic MH CZ - DRO (MMCI, 00209805) (EpiLymph); National Cancer Institute/National Institutes of Health (CA51086), European Community (Europe Against Cancer Programme), and Italian Alliance Against Cancer (Lega Italiana per la Lotta contro i Tumori) (Italy, multicenter); Italian Association for Cancer Research (Italy, Aviano-Milan); Italian Association for Cancer Research (Italy, Aviano-Naples); Swedish Cancer Society (2009/659), Stockholm County Council (20110209), Strategic Research Program in Epidemiology at Karolinska Institut, Swedish Cancer Society (02 6661), Danish Cancer Research Foundation, Lundbeck Foundation (R19-A2364), Danish Cancer Society (DP 08-155), National Cancer Institute/National Institutes of Health (5R01 CA69669-02), and Plan Denmark (SCALE); Leukaemia & Lymphoma Research, UK; and Australian National Health and Medical Research Council (ID990920), Cancer Council NSW, and University of Sydney Faculty of Medicine (New South Wales). 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Medical History, Lifestyle, Family History, and Occupational Risk Factors for Sporadic Burkitt Lymphoma/Leukemia: The Interlymph Non-Hodgkin Lymphoma Subtypes Project

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Oxford University Press
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Published by Oxford University Press 2014.
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1052-6773
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1745-6614
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10.1093/jncimonographs/lgu003
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25174031
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Abstract

Abstract Background The etiologic role of medical history, lifestyle, family history, and occupational risk factors in sporadic Burkitt lymphoma (BL) is unknown, but epidemiologic and clinical evidence suggests that risk factors may vary by age. Methods We investigated risk factors for sporadic BL in 295 cases compared with 21818 controls in a pooled analysis of 18 case–control studies in the International Lymphoma Epidemiology Consortium (InterLymph). Cases were defined to include typical BL or Burkitt-like lymphoma. Odds ratios (ORs) and 95% confidence intervals (CIs) for associations were calculated separately for younger (<50 years) and older (≥50 years) BL using multivariate logistic regression. Results Cases included 133 younger BL and 159 older BL (age was missing for three cases) and they were evenly split between typical BL (n = 147) and Burkitt-like lymphoma (n = 148). BL in younger participants was inversely associated with a history of allergy (OR = 0.58; 95% CI = 0.32 to 1.05), and positively associated with a history of eczema among individuals without other atopic conditions (OR = 2.54; 95% CI = 1.20 to 5.40), taller height (OR = 2.17; 95% CI = 1.08 to 4.36), and employment as a cleaner (OR = 3.49; 95% CI = 1.13 to 10.7). BL in older participants was associated with a history of hepatitis C virus seropositivity (OR = 4.19; 95% CI = 1.05 to 16.6) based on three exposed cases. Regardless of age, BL was inversely associated with alcohol consumption and positively associated with height. Conclusions Our data suggest that BL in younger and older adults may be etiologically distinct. Burkitt lymphoma (BL) is an aggressive B-cell non-Hodgkin lymphoma (NHL) that occurs as three histologically indistinguishable subtypes: sporadic, endemic, and immunodeficiency-associated BL (1,2). Sporadic BL occurs in developed countries, accounting for about 30% of all lymphoid malignancies in children and 1%–5% of NHL in adults (3,4). Endemic BL occurs in equatorial Africa and Papua New Guinea as the most common childhood cancer and is associated with Epstein–Barr virus and Plasmodium falciparum infections (5). Immunodeficiency-associated BL is seen in those with HIV infection (6) or a history of solid organ transplantation (7). In contrast, risk factors for sporadic BL are unknown because no analytical epidemiological studies have examined risk factors other than infectious agents (8,9). Descriptive epidemiological and clinical studies conducted in developed countries point to age-related differences in BL. These include distinct age-specific incidence peaks of BL, one during childhood and the other at 60 years of age, in a study conducted in the Netherlands (10), as well as distinct peaks in adults in two studies conducted in the United States (6,11), and one study conducted using BL data from four continents excluding Africa (12). Clinical studies indicate a superior treatment outcome in pediatric BL patients compared with older BL patients (13). As with other cancers (14,15), the bimodality of BL and the different clinical outcomes by age suggest distinct etiologies of BL diagnosed at different ages. We investigated the associations between BL and medical history, lifestyle, family history, and occupational risk factors using pooled data from 18 case–control studies conducted in Europe, North America, and Australia as part of the International Lymphoma Epidemiology Consortium (InterLymph) NHL Subtypes Project. Our study is the first analytic epidemiological study to evaluate a broad range of risk factors for BL. The main aim of the study was to identify risk factors for sporadic BL in younger versus older participants (ie, <50 vs ≥50 years old). Methods Detailed methods for the InterLymph NHL Subtypes Project are reported elsewhere in this issue. Briefly, de-identified individual-level data from 18 case–control studies were included in this pooled analysis based on the following criteria: 1) case–control design with incident, histologically confirmed cases of BL and 2) availability of individual-level data for several risk factors of interest by December 31, 2011. Participants with serologically confirmed HIV infection or a history of solid organ transplantation were excluded. Because none of the cases was enrolled from equatorial Africa or Papua New Guinea, all cases in this analysis were considered to be sporadic BL. Ethics review committees at the participating institutions approved the studies and participants were enrolled after providing written informed consent. NHL Subtype Ascertainment and Harmonization Cases were diagnosed as BL, including a diagnosis of Burkitt-like lymphoma (BLL), according to the Working Formulation (16,17) or the 2001 World Health Organization (WHO) classification for hematologic malignancies (18). The histologic definition of BL is based on observing a diffuse and starry-sky pattern at low magnification under the microscope, a homogenous population of medium-sized lymphoid cells with round nuclei, open chromatin, multiple distinct nucleoli, moderate amounts of basophilic cytoplasm and frequent mitotic figures at high magnification, typical immunohistochemistry (positive for CD10, CD20, and Bcl-6 and negative for Bcl-2, and with high Ki-67 proliferation index), and a simple cytogenetic profile involving c-MYC gene translocation. Cases suggestive of BL but showing a more pleomorphic cytology of the tumor cells were diagnosed as BLL. Not all studies retained tissue samples, so centralized pathology review of the diagnoses was not possible. An interdisciplinary team of pathologists and epidemiologists reviewed the pathology reports from the original studies to ensure that the NHL subtype classification was as accurate and specific as possible using guidelines from the InterLymph Pathology Working Group (19,20). Risk Factor Ascertainment and Harmonization Self-reported medical, family, lifestyle, and occupational histories were elicited using a standardized, structured in-person or telephone interview and/or written questionnaire, as reported elsewhere in this issue. The questionnaire data obtained from the contributing studies was harmonized centrally with each individual variable in the dataset reviewed and checked for consistency with related exposure variables. Statistical Analysis As the main study objective was to investigate risk factors for BL in younger and older participants, stratified analyses were conducted with cases and controls categorized as younger participants (<50 years) or older participants (≥50 years), based on the median age at BL diagnosis. Demographic and socioeconomic factors were analyzed. Associations of age-specific BL in younger and older participants with risk factors were estimated by calculating pooled odds ratios (ORs) and 95% confidence intervals (CIs) for each exposure category relative to the stated referent group, as well as the appropriate P values, using fixed-effects logistic regression models that adjusted for study, age, sex, and race/ethnicity (ie, the basic adjusted model). Because the controls from most of the studies were frequency matched by age and sex to all cases (ie, all NHL subtypes) in the study rather than just BL, we conducted all analyses using all controls. Sensitivity analyses using a subset of controls from each study that were individually matched by age and sex to BL cases gave essentially similar results (not shown). Associations with nominal multilevel exposures were evaluated by testing for statistical heterogeneity across the variable categories, whereas associations with ordinal multilevel exposures were evaluated by testing for a monotonic statistical trend in the OR per change in variable category using the likelihood ratio test. A two-sided P value less than .05 without adjustment for multiple comparisons indicated a statistically significant association. Individuals with missing data for the exposure variable of interest were excluded from the model when estimating the association. Interstudy heterogeneity among the 18 studies was evaluated using separate logistic regression models performed within each study and the variability of the study-specific coefficients was quantified by the H statistic as described elsewhere in this issue. The independent association of age-specific BL with variables identified in the basic adjusted model was evaluated by constructing a final logistic regression model including all significantly associated variables and running a forward stepwise multivariate logistic regression until only variables that were statistically significant at P less than .05 were retained (the final model). In contrast to analyses in the basic adjusted model, individuals with missing variable categories were retained in the final model by including a code for the missing category in the variable. We also conducted histology-specific analyses (typical BL or BLL) and with younger and older cases combined for comparison with the age-specific results. Results were reported only when based on data from six or more studies. Results We studied 295 cases (147 typical BL and 148 BLL) and 21818 controls (Table 1). Most came from population-based studies (83.7% of cases and 76.6% of controls) and from studies conducted in North America (62.4% of cases and 51.9% of controls). The median age of all patients with BL was 52 years (interquartile range: 36–63 years) and was similar for typical BL and BLL (data not shown). No differences were noted between the cases and controls with respect to white, non-Hispanic ethnicity (84.4% vs 93.1%) or socioeconomic class distribution (Table 1). The age-stratified analyses were performed by rounding the median age to a more intuitive cut point of 50 years. Table 1. Demographical characteristics of cases of sporadic Burkitt lymphoma and controls in the InterLymph NHL Subtypes Project*   Controls  Cases  No. (%)†  No. (%)†  All subjects  21818 (100)  295 (100)  Age, y   <30  1267 (5.8)  41 (13.9)   30–39  2001 (9.2)  45 (15.3)   40–49  2926 (13.4)  47 (15.9)   50–59  4508 (20.7)  64 (21.7)   60–69  6104 (28.0)  65 (22.0)   70–79  4127 (18.9)  27 (9.2)   ≥80  860 (3.9)  3 (1.0)  Sex   Male  12809 (58.7)  207 (70.2)   Female  9009 (41.3)  88 (29.8)  Race/ethnicity   White, non-Hispanic  20318 (93.1)  249 (84.4)   Black  342 (1.6)  3 (1.0)   Asian  320 (1.5)  15 (5.1)   Hispanic  356 (1.6)  21 (7.1)   Other/unknown/missing  482 (2.2)  7 (2.4)  Socioeconomic status   Low  8900 (40.8)  117 (39.7)   Medium  6280 (28.8)  80 (27.1)   High  6233 (28.6)  94 (31.9)   Other/missing  405 (1.9)  4 (1.4)  NHL classification   World Health Organization  12488 (57.2)  159 (53.9)   Working Formulation  9330 (42.8)  136 (46.1)  Histological diagnosis   Burkitt lymphoma  —  147 (49.8)   Burkitt-like lymphoma  —  148 (50.2)  BL anatomic site   Nodal  —  120 (40.7)   Extranodal  —  73 (24.7)   Systemic  —  21 (7.1)   Not collected  —  81 (27.5)  Study region   North America  11323 (51.9)  184 (62.4)   Northern Europe  5403 (24.8)  58 (19.7)   Southern Europe  4398 (20.2)  49 (16.6)   Australia  694 (3.2)  4 (1.4)  Study design   Population-based  16707 (76.6)  247 (83.7)   Hospital-based  5111 (23.4)  48 (16.3)    Controls  Cases  No. (%)†  No. (%)†  All subjects  21818 (100)  295 (100)  Age, y   <30  1267 (5.8)  41 (13.9)   30–39  2001 (9.2)  45 (15.3)   40–49  2926 (13.4)  47 (15.9)   50–59  4508 (20.7)  64 (21.7)   60–69  6104 (28.0)  65 (22.0)   70–79  4127 (18.9)  27 (9.2)   ≥80  860 (3.9)  3 (1.0)  Sex   Male  12809 (58.7)  207 (70.2)   Female  9009 (41.3)  88 (29.8)  Race/ethnicity   White, non-Hispanic  20318 (93.1)  249 (84.4)   Black  342 (1.6)  3 (1.0)   Asian  320 (1.5)  15 (5.1)   Hispanic  356 (1.6)  21 (7.1)   Other/unknown/missing  482 (2.2)  7 (2.4)  Socioeconomic status   Low  8900 (40.8)  117 (39.7)   Medium  6280 (28.8)  80 (27.1)   High  6233 (28.6)  94 (31.9)   Other/missing  405 (1.9)  4 (1.4)  NHL classification   World Health Organization  12488 (57.2)  159 (53.9)   Working Formulation  9330 (42.8)  136 (46.1)  Histological diagnosis   Burkitt lymphoma  —  147 (49.8)   Burkitt-like lymphoma  —  148 (50.2)  BL anatomic site   Nodal  —  120 (40.7)   Extranodal  —  73 (24.7)   Systemic  —  21 (7.1)   Not collected  —  81 (27.5)  Study region   North America  11323 (51.9)  184 (62.4)   Northern Europe  5403 (24.8)  58 (19.7)   Southern Europe  4398 (20.2)  49 (16.6)   Australia  694 (3.2)  4 (1.4)  Study design   Population-based  16707 (76.6)  247 (83.7)   Hospital-based  5111 (23.4)  48 (16.3)  * BL = Burkitt lymphoma; NHL = non-Hodgkin lymphoma. † The counts do not add up to the total number of cases/controls due to data missing by design or report. View Large The results from the basic adjusted model showed that BL in younger participants was inversely associated with a history of allergy (OR = 0.52; 95% CI = 0.30 to 0.90) or asthma (OR = 0.35; 95% CI = 0.13 to 0.95; based on four exposed cases). A non-significant inverse association with BL in younger participants was also observed for a history of atopy (OR = 0.68; 95% CI = 0.45 to 1.02), hay fever (OR = 0.60; 95% CI = 0.35 to 1.05), or food allergy (OR = 0.50; 95% CI = 0.17 to 1.50; based on four exposed cases). A history of eczema was unrelated to BL in younger participants. However, when eczema alone without other atopic conditions was considered, it was associated with elevated BL risk (OR = 2.8; 95% CI = 1.35 to 5.86) (Table 2). In contrast to BL in younger participants, a history of allergy, asthma, atopy, hay fever, or eczema was not associated with BL in older participants. Table 2. Association of medical and family history with sporadic Burkitt lymphoma in the InterLymph NHL Subtypes Project from the basic model, stratified by age*   <50 years  ≥50 years  Controls  Cases  OR (95% CI)‡  P  Controls  Cases  OR (95% CI)†  P  No. (%)†  No. (%)†  No. (%)†  No. (%)†  Medical history  Any atopic disorder§   No  3763 (65.4)  89 (67.4)  1.00 (referent)  .058  10156 (70.3)  114 (72.2)  1.00 (referent)  .736   Yes  1878 (32.6)  40 (30.3)  0.68 (0.45 to 1.02)    3977 (27.5)  43 (27.2)  0.94 (0.64 to 1.37)    Allergy||   No  2490 (64.9)  64 (70.3)  1.00 (referent)  .016  7082 (71.3)  64 (68.8)  1.00 (referent)  .760   Yes  1093 (28.5)  21 (23.1)  0.52 (0.30 to 0.90)    2231 (22.5)  23 (24.7)  1.09 (0.64 to 1.85)    Food allergy   No  3146 (82.0)  70 (76.9)  1.00 (referent)  .176  7140 (81.7)  57 (71.3)  1.00 (referent)  .989   Yes  274 (7.1)  4 (4.4)  0.50 (0.17 to 1.50)    586 (6.7)  5 (6.3)  0.99 (0.38 to 2.59)    Asthma   No  4865 (84.6)  109 (82.6)  1.00 (referent)  .015  12296 (85.1)  136 (86.1)  1.00 (referent)  .745   Yes  461 (8.0)  4 (3.0)  0.35 (0.13 to 0.95)    1061 (7.3)  13 (8.2)  1.11 (0.61 to 2.00)    Hay fever   No  2646 (62.9)  68 (62.4)  1.00 (referent)  .062  8543 (71.6)  98 (72.6)  1.00 (referent)  .228   Yes  909 (21.6)  23 (21.1)  0.60 (0.35 to 1.05)    1769 (14.8)  20 (14.8)  0.71 (0.41 to 1.25)    Eczema   No  3583 (83.7)  91 (84.3)  1.00 (referent)  .649  9868 (86.9)  122 (92.4)  1.00 (referent)  .684   Yes¶  516 (12.0)  12 (11.1)  1.16 (0.62 to 2.19)    912 (8.0)  8 (6.1)  0.86 (0.41 to 1.80)    Eczema without other atopic conditions   No eczema  3583 (83.7)  91 (84.3)  1.00 (referent)  .008  9868 (86.9)  122 (92.4)  1.00 (referent)  .805   Eczema without other atopic conditions#  176 (4.1)  9 (8.3)  2.82 (1.35 to 5.86)    402 (3.5)  4 (3.0)  1.06 (0.38 to 2.93)     Eczema with other atopic conditions  340 (7.9)  3 (2.8)  0.41 (0.13 to 1.32)    510 (4.5)  4 (3.0)  0.723 (0.26 to 2.02)    History of hepatitis C virus infection   No  1891 (59.3)  31 (56.4)  1.00 (referent)  .430  4453 (69.7)  30 (62.5)  1.00 (referent)  .066   Yes  42 (1.3)  0 (0.0)  —    109 (1.7)  3 (6.3)  4.10 (1.10 to 15.4)    Blood transfusion   No  3062 (89.8)  71 (86.6)  1.00 (referent)  .228  6091 (70.6)  78 (75.7)  1.00 (referent)  .054   Yes  232 (6.8)  8 (9.8)  1.64 (0.77 to 3.50)    1514 (17.5)  10 (9.7)  0.54 (0.27 to 1.06)    Total number of blood transfusions   No transfusion  3062 (89.8)  71 (86.6)  1.00 (referent)  .201  6091 (70.6)  78 (75.7)  1.00 (referent)  .267   1 transfusion  163 (4.8)  4 (4.9)  1.09 (0.39 to 3.08)    973 (11.3)  6 (5.8)  0.48 (0.21 to 1.13)     2 transfusions  39 (1.1)  1 (1.2)  1.61 (0.21 to 12.2)    292 (3.4)  2 (1.9)  0.74 (0.18 to 3.10)     ≥3 transfusions  23 (0.7)  3 (3.7)  6.46 (1.75 to 23.81)    189 (2.2)  2 (1.9)  0.79 (0.19 to 3.40)    Number of years from first blood transfusion   No transfusion  3062 (89.8)  71 (86.6)  1.00 (referent)  .194  6091 (70.6)  78 (75.7)  1.00 (referent)  .101   <20 years  134 (3.9)  6 (7.3)  2.22 (0.92 to 5.34)    657 (7.6)  3 (2.9)  0.36 (0.11 to 1.16)     20–39 years  85 (2.5)  1 (1.2)  0.51 (0.07 to 3.74)    557 (6.5)  6 (5.8)  0.92 (0.39 to 2.17)    Blood transfusion before 1990   No transfusion  3062 (89.8)  71 (86.6)  1.00 (referent)  .117  6091 (70.6)  78 (75.7)  1.00 (referent)  .068   Transfusion before 1990  158 (4.6)  7 (8.5)  2.22 (0.98 to 5.04)    1118 (13.0)  10 (9.7)  0.65 (0.33 to 1.28)     Transfusion year unknown  11 (0.3)  1 (1.2)  1.97 (0.21 to 18.0)    94 (1.1)  0 (0.0)  —    Family history of non-Hodgkin lymphoma   No  3057 (91.3)  68 (77.3)  1.00 (referent)  .517  9501 (91.8)  111 (91.0)  1.00 (referent)  .272   Yes  40 (1.2)  2 (2.3)  1.71 (0.37 to 7.91)    229 (2.2)  1 (0.8)  0.38 (0.05 to 2.83)    Family history of leukemia   No  3451 (91.6)  74 (80.4)  1.00 (referent)  .088  9409 (90.9)  107 (87.7)  1.00 (referent)  .644   Yes  65 (1.7)  0 (0.0)  —    321 (3.1)  5 (4.1)  1.26 (0.49 to 3.21)      <50 years  ≥50 years  Controls  Cases  OR (95% CI)‡  P  Controls  Cases  OR (95% CI)†  P  No. (%)†  No. (%)†  No. (%)†  No. (%)†  Medical history  Any atopic disorder§   No  3763 (65.4)  89 (67.4)  1.00 (referent)  .058  10156 (70.3)  114 (72.2)  1.00 (referent)  .736   Yes  1878 (32.6)  40 (30.3)  0.68 (0.45 to 1.02)    3977 (27.5)  43 (27.2)  0.94 (0.64 to 1.37)    Allergy||   No  2490 (64.9)  64 (70.3)  1.00 (referent)  .016  7082 (71.3)  64 (68.8)  1.00 (referent)  .760   Yes  1093 (28.5)  21 (23.1)  0.52 (0.30 to 0.90)    2231 (22.5)  23 (24.7)  1.09 (0.64 to 1.85)    Food allergy   No  3146 (82.0)  70 (76.9)  1.00 (referent)  .176  7140 (81.7)  57 (71.3)  1.00 (referent)  .989   Yes  274 (7.1)  4 (4.4)  0.50 (0.17 to 1.50)    586 (6.7)  5 (6.3)  0.99 (0.38 to 2.59)    Asthma   No  4865 (84.6)  109 (82.6)  1.00 (referent)  .015  12296 (85.1)  136 (86.1)  1.00 (referent)  .745   Yes  461 (8.0)  4 (3.0)  0.35 (0.13 to 0.95)    1061 (7.3)  13 (8.2)  1.11 (0.61 to 2.00)    Hay fever   No  2646 (62.9)  68 (62.4)  1.00 (referent)  .062  8543 (71.6)  98 (72.6)  1.00 (referent)  .228   Yes  909 (21.6)  23 (21.1)  0.60 (0.35 to 1.05)    1769 (14.8)  20 (14.8)  0.71 (0.41 to 1.25)    Eczema   No  3583 (83.7)  91 (84.3)  1.00 (referent)  .649  9868 (86.9)  122 (92.4)  1.00 (referent)  .684   Yes¶  516 (12.0)  12 (11.1)  1.16 (0.62 to 2.19)    912 (8.0)  8 (6.1)  0.86 (0.41 to 1.80)    Eczema without other atopic conditions   No eczema  3583 (83.7)  91 (84.3)  1.00 (referent)  .008  9868 (86.9)  122 (92.4)  1.00 (referent)  .805   Eczema without other atopic conditions#  176 (4.1)  9 (8.3)  2.82 (1.35 to 5.86)    402 (3.5)  4 (3.0)  1.06 (0.38 to 2.93)     Eczema with other atopic conditions  340 (7.9)  3 (2.8)  0.41 (0.13 to 1.32)    510 (4.5)  4 (3.0)  0.723 (0.26 to 2.02)    History of hepatitis C virus infection   No  1891 (59.3)  31 (56.4)  1.00 (referent)  .430  4453 (69.7)  30 (62.5)  1.00 (referent)  .066   Yes  42 (1.3)  0 (0.0)  —    109 (1.7)  3 (6.3)  4.10 (1.10 to 15.4)    Blood transfusion   No  3062 (89.8)  71 (86.6)  1.00 (referent)  .228  6091 (70.6)  78 (75.7)  1.00 (referent)  .054   Yes  232 (6.8)  8 (9.8)  1.64 (0.77 to 3.50)    1514 (17.5)  10 (9.7)  0.54 (0.27 to 1.06)    Total number of blood transfusions   No transfusion  3062 (89.8)  71 (86.6)  1.00 (referent)  .201  6091 (70.6)  78 (75.7)  1.00 (referent)  .267   1 transfusion  163 (4.8)  4 (4.9)  1.09 (0.39 to 3.08)    973 (11.3)  6 (5.8)  0.48 (0.21 to 1.13)     2 transfusions  39 (1.1)  1 (1.2)  1.61 (0.21 to 12.2)    292 (3.4)  2 (1.9)  0.74 (0.18 to 3.10)     ≥3 transfusions  23 (0.7)  3 (3.7)  6.46 (1.75 to 23.81)    189 (2.2)  2 (1.9)  0.79 (0.19 to 3.40)    Number of years from first blood transfusion   No transfusion  3062 (89.8)  71 (86.6)  1.00 (referent)  .194  6091 (70.6)  78 (75.7)  1.00 (referent)  .101   <20 years  134 (3.9)  6 (7.3)  2.22 (0.92 to 5.34)    657 (7.6)  3 (2.9)  0.36 (0.11 to 1.16)     20–39 years  85 (2.5)  1 (1.2)  0.51 (0.07 to 3.74)    557 (6.5)  6 (5.8)  0.92 (0.39 to 2.17)    Blood transfusion before 1990   No transfusion  3062 (89.8)  71 (86.6)  1.00 (referent)  .117  6091 (70.6)  78 (75.7)  1.00 (referent)  .068   Transfusion before 1990  158 (4.6)  7 (8.5)  2.22 (0.98 to 5.04)    1118 (13.0)  10 (9.7)  0.65 (0.33 to 1.28)     Transfusion year unknown  11 (0.3)  1 (1.2)  1.97 (0.21 to 18.0)    94 (1.1)  0 (0.0)  —    Family history of non-Hodgkin lymphoma   No  3057 (91.3)  68 (77.3)  1.00 (referent)  .517  9501 (91.8)  111 (91.0)  1.00 (referent)  .272   Yes  40 (1.2)  2 (2.3)  1.71 (0.37 to 7.91)    229 (2.2)  1 (0.8)  0.38 (0.05 to 2.83)    Family history of leukemia   No  3451 (91.6)  74 (80.4)  1.00 (referent)  .088  9409 (90.9)  107 (87.7)  1.00 (referent)  .644   Yes  65 (1.7)  0 (0.0)  —    321 (3.1)  5 (4.1)  1.26 (0.49 to 3.21)    * CI = confidence interval; NHL = non-Hodgkin lymphoma; OR = odds ratio. † The counts do not add up to the total number of cases/controls due to data missing by design or report. ‡ Adjusted for age, sex, race/ethnicity, and study. § Atopic disorders include asthma, eczema, hay fever, or other allergies, excluding drug allergies. || History of allergy included plant, food, animal, dust, insect, or mold allergy. ¶ Eczema, with or without other atopic conditions. # Eczema alone, excluding participants who reported eczema and other atopic conditions. View Large We observed an elevated risk of BL among older participants who reported of a history of hepatitis C virus (HCV) seropositivity (OR = 4.1; 95% CI = 1.10 to 15.4), based on three exposed cases in the six studies that reported HCV serostatus (Table 2). The relationship between BL and HCV seropositivity in younger participants was indeterminate because none of the 31 younger cases reported a seropositive history. A history of prior blood transfusion (yes vs no) was unrelated to BL in younger participants but was inversely associated with BL risk in older participants. Younger participants who reported receiving three or more transfusions had an elevated risk of BL in (OR = 6.46; 95% CI = 1.75 to 23.8), but this result was based on only three exposed cases and the risk was not increased in the older participants with higher numbers of transfusions (Table 2). Peptic ulcer and hormone use were not associated with BL in younger or older participants (data not shown). The risk of BL in younger or older participants was not associated with a history of NHL or leukemia among first-degree relatives, but the number of cases was small in both groups (Table 2). With respect to anthropometric factors, the risk of BL doubled in the tallest participants (quartile 4) compared with the shortest ones (quartile 1), both in the younger (OR = 2.14; 95% CI = 1.07 to 4.25) and the older (OR = 1.79; 95% CI = 0.92 to 3.49) age groups (Table 3). BL was not associated with usual weight or body mass index in younger participants, but a non-significant inverse association was observed between BL and body mass index in older participants (Ptrend = .07). With respect to lifestyle factors, the risks for both younger and older BL were inversely associated with alcohol consumption (Table 3), particularly among older participants. A history of cigarette smoking was not associated with BL in either younger or older participants (Table 3). We observed a non-significantly elevated risk of BL among younger participants who reported the use of light-colored hair dye compared with never use (OR = 3.0; 95% CI = 0.91 to 9.9), but the association with BL among older participants was indeterminate because only one older case was exposed. BL among older participants was not associated with the use of dark hair dyes (OR = 1.29; 95% CI = 0.46 to 3.63) based on nine exposed cases, and among younger participants, only two cases were exposed. BL was not associated with recreational sun exposure in either younger or older participants (Table 3). Table 3. Association of anthropometry and lifestyle factors with sporadic Burkitt lymphoma in the InterLymph NHL Subtypes Project from the basic model, stratified by age*   <50 years  ≥50 years  Controls  Cases  OR (95% CI)‡  P  Controls  Cases  OR (95% CI)‡  P  N (%)†  N (%)†  N (%)†  N (%)†  Usual adult height§   Quartile 1 (low)  816 (17.1)  12 (12.0)   1.00 (referent)  .029  3039 (26.7)  19 (20.9)   1.00 (referent)  .301   Quartile 2  979 (20.5)  14 (14.0)   1.03 (0.46 to 2.28)    2693 (23.7)  22 (24.2)   1.57 (0.83 to 2.97)     Quartile 3  1174 (24.6)  21 (21.0)   1.27 (0.60 to 2.70)    2703 (23.8)  24 (26.4)   1.66 (0.87 to 3.15)     Quartile 4 (high)  1612 (33.8)  47 (47.0)   2.14 (1.07 to 4.25)    2528 (22.2)  24 (26.4)   1.79 (0.92 to 3.49)    Usual adult weight||   Quartile 1 (low)  1342 (28.2)  22 (22.0)   1.00 (referent)  .294  2452 (21.6)  24 (26.4)   1.00 (referent)  .636   Quartile 2  1122 (23.6)  23 (23.0)   1.26 (0.68 to 2.33)    2555 (22.5)  22 (24.2)   0.93 (0.51 to 1.68)     Quartile 3  1102 (23.1)  29 (29.0)   1.67 (0.93 to 3.00)    3032 (26.7)  19 (20.9)   0.68 (0.37 to 1.27)     Quartile 4 (high)  1015 (21.3)  20 (20.0)   1.05 (0.54 to 2.02)    2924 (25.7)  24 (26.4)   0.80 (0.43 to 1.46)    Usual adult body mass index (kg/m2)   15–<18.5  105 (2.2)  1 (1.0)   0.49 (0.07 to 3.77)    146 (1.3)  3 (3.3)   1.94 (0.55 to 6.89)     18.5–<22.5  1320 (27.7)  24 (24.0)   1.00 (referent)  .71  1879 (16.5)  19 (20.9)   1.00 (referent)  .07   22.5–<25  1250 (26.2)  31 (31.0)   1.31 (0.75 to 2.29)    2724 (24.0)  20 (22.0)   0.68 (0.36 to 1.29)     25–<30  1434 (30.1)  27 (27.0)   0.91 (0.50 to 1.65)    4415 (38.8)  28 (30.8)   0.52 (0.28 to 0.96)     30–<35  345 (7.2)  9 (9.0)   1.11 (0.49 to 2.56)    1344 (11.8)  17 (18.7)   1.08 (0.54 to 2.14)     35–50  127 (2.7)  2 (2.0)   0.73 (0.16 to 3.24)    455 (4.0)  2 (2.2)   0.37 (0.08 to 1.66)    Alcohol consumption status 2 years prior to diagnosis/interview   Non-drinker  1065 (23.4)  32 (29.9)   1.00 (referent)  .211  3103 (23.4)  54 (36.0)   1.00 (referent)  .05   Former drinker  96 (2.1)  0 (0.0)  —    468 (3.5)  2 (1.3)   0.48 (0.10 to 2.25)     Current drinker  1394 (30.7)  22 (20.6)   0.75 (0.36 to 1.57)    3335 (25.1)  21 (14.0)   0.44 (0.21 to 0.91)     Drinker, status unknown  1480 (32.6)  38 (35.5)   0.68 (0.39 to 1.20)    3240 (24.4)  53 (35.3)   0.65 (0.41 to 1.03)    Age at first alcohol consumption   Non-drinker  1065 (23.4)  32 (29.9)   1.00 (referent)  .192  3103 (23.4)  54 (36.0)   1.00 (referent)  .07   <20 years  662 (14.6)  13 (12.1)   1.26 (0.51 to 3.12)    1478 (11.1)  7 (4.7)   0.38 (0.15 to 0.98)     20–29 years  1045 (23.0)  11 (10.3)   0.48 (0.19 to 1.19)    1801 (13.6)  15 (10.0)   0.58 (0.28 to 1.19)     ≥30 years  102 (2.2)  2 (1.9)   1.10 (0.24 to 5.14)    654 (4.9)  3 (2.0)   0.36 (0.10 to 1.23)     Drinker, age start unknown  1161 (25.6)  34 (31.8)   0.63 (0.35 to 1.16)    3110 (23.4)  51 (34.0)   0.65 (0.41 to 1.05)    Duration of alcohol consumption¶  6048 (100.0)  133 (100.0)   0.98 (0.94 to 1.02)  .353  15086 (100.0)  159 (100.0)   0.98 (0.96 to 1.00)  .047  Ethanol per week as an adult, consumed from any type of alcoholic beverage#   Non-drinker  1065 (23.4)  32 (29.9)   1.00 (referent)  .409  3103 (23.4)  54 (36.0)   1.00 (referent)  .043   Q1 (low)  730 (16.1)  22 (20.6)   0.81 (0.45 to 1.45)    1508 (11.4)  24 (16.0)   0.75 (0.45 to 1.27)     Q2  676 (14.9)  17 (15.9)   0.83 (0.44 to 1.58)    1532 (11.5)  13 (8.7)   0.42 (0.22 to 0.80)     Q3  670 (14.8)  10 (9.3)   0.56 (0.26 to 1.18)    1548 (11.7)  21 (14.0)   0.69 (0.40 to 1.20)     Q4 (high)  683 (15.0)  10 (9.3)   0.57 (0.26 to 1.25)    1682 (12.7)  17 (11.3)   0.51 (0.27 to 0.94)     Drinker, grams unknown  211 (4.6)  1 (0.9)   0.19 (0.02 to 2.42)    773 (5.8)  1 (0.7)   0.16 (0.01 to 2.26)    Lifetime alcohol consumed   Non-drinker  1065 (23.4)  32 (29.9)  1.00 (referent)  .604  3103 (23.4)  54 (36.0)   1.00 (referent)  .025   1–100 kg  581 (12.8)  10 (9.3)  1.02 (0.40 to 2.55)    765 (5.8)  8 (5.3)   0.90 (0.36 to 2.24)     101–200 kg  226 (5.0)  2 (1.9)  0.56 (0.12 to 2.68)    404 (3.0)  2 (1.3)   0.37 (0.08 to 1.67)     201–400 kg  150 (3.3)  2 (1.9)  0.83 (0.17 to 4.01)    497 (3.7)  2 (1.3)   0.23 (0.05 to 1.06)     >400 kg  116 (2.6)  2 (1.9)  1.10 (0.23 to 5.28)    640 (4.8)  3 (2.0)   0.22 (0.06 to 0.86)     Drinker, consumption unknown  1897 (41.8)  44 (41.1)  0.63 (0.37 to 1.06)    4737 (35.7)  61 (40.7)   0.63 (0.40 to 0.98)    Cigarette smoking status 2 years prior to diagnosis/interview   Non-smoker  2511 (43.2)  68 (53.1)  1.00 (referent)  .552  5760 (39.8)  58 (37.7)  1.00 (referent)  .912   Former smoker  1075 (18.5)  19 (14.8)  0.85 (0.5 to 1.47)    4777 (33.0)  55 (35.7)  0.92 (0.62 to 1.34)     Current smoker  1774 (30.5)  29 (22.7)  0.72 (0.45 to 1.14)    2645 (18.3)  29 (18.8)  0.88 (0.54 to 1.42)     Smoker, status unknown  125 (2.2)  2 (1.6)  0.73 (0.16 to 3.37)    399 (2.8)  5 (3.2)  1.21 (0.41 to 3.56)    Color of hair dye used   Never hair dye  426 (13.3)  6 (9.7)  1.00 (referent)  .007  1318 (17.5)  7 (12.7)   1.00 (referent)  .291   Light  189 (5.9)  8 (12.9)  2.99 (0.91 to 9.88)    690 (9.2)  1 (1.8)   0.26 (0.03 to 2.16)     Dark  407 (12.7)  2 (3.2)  0.35 (0.06 to 1.92)    1319 (17.5)  9 (16.4)   1.29 (0.46 to 3.63)     Ever hair dye, color unknown  116 (3.6)  1 (1.6)  0.15 (0.01 to 1.89)    310 (4.1)  2 (3.6)   0.57 (0.07 to 4.98)     Male**  1995 (62.1)  44 (71.0)  —    3716 (49.4)  35 (63.6)  —    Recreational sun exposure††   Quartile 1 (low)  409 (16.1)  7 (13.7)  1.00 (referent)  .930  1425 (22.0)  12 (28.6)  1.00 (referent)  .725   Quartile 2  654 (25.7)  13 (25.5)  1.16 (0.44 to 3.00)    1324 (20.5)  7 (16.7)  0.61 (0.24 to 1.56)     Quartile 3  445 (17.5)  10 (19.6)  1.17 (0.43 to 3.19)    1190 (18.4)  8 (19)  0.80 (0.32 to 2.00)     Quartile 4 (high)  726 (28.5)  13 (25.5)  0.92 (0.36 to 2.39)    1729 (26.7)  10 (23.8)  0.66 (0.28 to 1.57)      <50 years  ≥50 years  Controls  Cases  OR (95% CI)‡  P  Controls  Cases  OR (95% CI)‡  P  N (%)†  N (%)†  N (%)†  N (%)†  Usual adult height§   Quartile 1 (low)  816 (17.1)  12 (12.0)   1.00 (referent)  .029  3039 (26.7)  19 (20.9)   1.00 (referent)  .301   Quartile 2  979 (20.5)  14 (14.0)   1.03 (0.46 to 2.28)    2693 (23.7)  22 (24.2)   1.57 (0.83 to 2.97)     Quartile 3  1174 (24.6)  21 (21.0)   1.27 (0.60 to 2.70)    2703 (23.8)  24 (26.4)   1.66 (0.87 to 3.15)     Quartile 4 (high)  1612 (33.8)  47 (47.0)   2.14 (1.07 to 4.25)    2528 (22.2)  24 (26.4)   1.79 (0.92 to 3.49)    Usual adult weight||   Quartile 1 (low)  1342 (28.2)  22 (22.0)   1.00 (referent)  .294  2452 (21.6)  24 (26.4)   1.00 (referent)  .636   Quartile 2  1122 (23.6)  23 (23.0)   1.26 (0.68 to 2.33)    2555 (22.5)  22 (24.2)   0.93 (0.51 to 1.68)     Quartile 3  1102 (23.1)  29 (29.0)   1.67 (0.93 to 3.00)    3032 (26.7)  19 (20.9)   0.68 (0.37 to 1.27)     Quartile 4 (high)  1015 (21.3)  20 (20.0)   1.05 (0.54 to 2.02)    2924 (25.7)  24 (26.4)   0.80 (0.43 to 1.46)    Usual adult body mass index (kg/m2)   15–<18.5  105 (2.2)  1 (1.0)   0.49 (0.07 to 3.77)    146 (1.3)  3 (3.3)   1.94 (0.55 to 6.89)     18.5–<22.5  1320 (27.7)  24 (24.0)   1.00 (referent)  .71  1879 (16.5)  19 (20.9)   1.00 (referent)  .07   22.5–<25  1250 (26.2)  31 (31.0)   1.31 (0.75 to 2.29)    2724 (24.0)  20 (22.0)   0.68 (0.36 to 1.29)     25–<30  1434 (30.1)  27 (27.0)   0.91 (0.50 to 1.65)    4415 (38.8)  28 (30.8)   0.52 (0.28 to 0.96)     30–<35  345 (7.2)  9 (9.0)   1.11 (0.49 to 2.56)    1344 (11.8)  17 (18.7)   1.08 (0.54 to 2.14)     35–50  127 (2.7)  2 (2.0)   0.73 (0.16 to 3.24)    455 (4.0)  2 (2.2)   0.37 (0.08 to 1.66)    Alcohol consumption status 2 years prior to diagnosis/interview   Non-drinker  1065 (23.4)  32 (29.9)   1.00 (referent)  .211  3103 (23.4)  54 (36.0)   1.00 (referent)  .05   Former drinker  96 (2.1)  0 (0.0)  —    468 (3.5)  2 (1.3)   0.48 (0.10 to 2.25)     Current drinker  1394 (30.7)  22 (20.6)   0.75 (0.36 to 1.57)    3335 (25.1)  21 (14.0)   0.44 (0.21 to 0.91)     Drinker, status unknown  1480 (32.6)  38 (35.5)   0.68 (0.39 to 1.20)    3240 (24.4)  53 (35.3)   0.65 (0.41 to 1.03)    Age at first alcohol consumption   Non-drinker  1065 (23.4)  32 (29.9)   1.00 (referent)  .192  3103 (23.4)  54 (36.0)   1.00 (referent)  .07   <20 years  662 (14.6)  13 (12.1)   1.26 (0.51 to 3.12)    1478 (11.1)  7 (4.7)   0.38 (0.15 to 0.98)     20–29 years  1045 (23.0)  11 (10.3)   0.48 (0.19 to 1.19)    1801 (13.6)  15 (10.0)   0.58 (0.28 to 1.19)     ≥30 years  102 (2.2)  2 (1.9)   1.10 (0.24 to 5.14)    654 (4.9)  3 (2.0)   0.36 (0.10 to 1.23)     Drinker, age start unknown  1161 (25.6)  34 (31.8)   0.63 (0.35 to 1.16)    3110 (23.4)  51 (34.0)   0.65 (0.41 to 1.05)    Duration of alcohol consumption¶  6048 (100.0)  133 (100.0)   0.98 (0.94 to 1.02)  .353  15086 (100.0)  159 (100.0)   0.98 (0.96 to 1.00)  .047  Ethanol per week as an adult, consumed from any type of alcoholic beverage#   Non-drinker  1065 (23.4)  32 (29.9)   1.00 (referent)  .409  3103 (23.4)  54 (36.0)   1.00 (referent)  .043   Q1 (low)  730 (16.1)  22 (20.6)   0.81 (0.45 to 1.45)    1508 (11.4)  24 (16.0)   0.75 (0.45 to 1.27)     Q2  676 (14.9)  17 (15.9)   0.83 (0.44 to 1.58)    1532 (11.5)  13 (8.7)   0.42 (0.22 to 0.80)     Q3  670 (14.8)  10 (9.3)   0.56 (0.26 to 1.18)    1548 (11.7)  21 (14.0)   0.69 (0.40 to 1.20)     Q4 (high)  683 (15.0)  10 (9.3)   0.57 (0.26 to 1.25)    1682 (12.7)  17 (11.3)   0.51 (0.27 to 0.94)     Drinker, grams unknown  211 (4.6)  1 (0.9)   0.19 (0.02 to 2.42)    773 (5.8)  1 (0.7)   0.16 (0.01 to 2.26)    Lifetime alcohol consumed   Non-drinker  1065 (23.4)  32 (29.9)  1.00 (referent)  .604  3103 (23.4)  54 (36.0)   1.00 (referent)  .025   1–100 kg  581 (12.8)  10 (9.3)  1.02 (0.40 to 2.55)    765 (5.8)  8 (5.3)   0.90 (0.36 to 2.24)     101–200 kg  226 (5.0)  2 (1.9)  0.56 (0.12 to 2.68)    404 (3.0)  2 (1.3)   0.37 (0.08 to 1.67)     201–400 kg  150 (3.3)  2 (1.9)  0.83 (0.17 to 4.01)    497 (3.7)  2 (1.3)   0.23 (0.05 to 1.06)     >400 kg  116 (2.6)  2 (1.9)  1.10 (0.23 to 5.28)    640 (4.8)  3 (2.0)   0.22 (0.06 to 0.86)     Drinker, consumption unknown  1897 (41.8)  44 (41.1)  0.63 (0.37 to 1.06)    4737 (35.7)  61 (40.7)   0.63 (0.40 to 0.98)    Cigarette smoking status 2 years prior to diagnosis/interview   Non-smoker  2511 (43.2)  68 (53.1)  1.00 (referent)  .552  5760 (39.8)  58 (37.7)  1.00 (referent)  .912   Former smoker  1075 (18.5)  19 (14.8)  0.85 (0.5 to 1.47)    4777 (33.0)  55 (35.7)  0.92 (0.62 to 1.34)     Current smoker  1774 (30.5)  29 (22.7)  0.72 (0.45 to 1.14)    2645 (18.3)  29 (18.8)  0.88 (0.54 to 1.42)     Smoker, status unknown  125 (2.2)  2 (1.6)  0.73 (0.16 to 3.37)    399 (2.8)  5 (3.2)  1.21 (0.41 to 3.56)    Color of hair dye used   Never hair dye  426 (13.3)  6 (9.7)  1.00 (referent)  .007  1318 (17.5)  7 (12.7)   1.00 (referent)  .291   Light  189 (5.9)  8 (12.9)  2.99 (0.91 to 9.88)    690 (9.2)  1 (1.8)   0.26 (0.03 to 2.16)     Dark  407 (12.7)  2 (3.2)  0.35 (0.06 to 1.92)    1319 (17.5)  9 (16.4)   1.29 (0.46 to 3.63)     Ever hair dye, color unknown  116 (3.6)  1 (1.6)  0.15 (0.01 to 1.89)    310 (4.1)  2 (3.6)   0.57 (0.07 to 4.98)     Male**  1995 (62.1)  44 (71.0)  —    3716 (49.4)  35 (63.6)  —    Recreational sun exposure††   Quartile 1 (low)  409 (16.1)  7 (13.7)  1.00 (referent)  .930  1425 (22.0)  12 (28.6)  1.00 (referent)  .725   Quartile 2  654 (25.7)  13 (25.5)  1.16 (0.44 to 3.00)    1324 (20.5)  7 (16.7)  0.61 (0.24 to 1.56)     Quartile 3  445 (17.5)  10 (19.6)  1.17 (0.43 to 3.19)    1190 (18.4)  8 (19)  0.80 (0.32 to 2.00)     Quartile 4 (high)  726 (28.5)  13 (25.5)  0.92 (0.36 to 2.39)    1729 (26.7)  10 (23.8)  0.66 (0.28 to 1.57)    * CI = confidence interval; NHL = non-Hodgkin lymphoma; OR = odds ratio. † The counts do not add up to the total number of cases/controls due to data missing by design or report. ‡ Adjusted for age, sex, race/ethnicity, and study. § Height quartile cutoffs are: 172, 177.8, and 182cm for Q1-2, Q2-3, and Q3-4, respectively, for males, and 159, 163.0, and 168cm, respectively, for females. || Weight quartile cutoffs are: 72.6, 80, and 89kg for Q1-2, Q2-3, and Q3-4, respectively, for males, and 58.1, 65, and 74.8, respectively, for females. ¶ Adjusted for age, sex, race/ethnicity, and study. # Alcohol quartile cutoff points: 44.4, 110.7, and 252g, respectively, for Q1-2, Q2-3, and Q3-4, respectively. ** Males were not included in the analysis of use of hair dye. †† Recreational sun exposure (hours per week, study-specific quartiles available upon request). View Large Among 31 occupations evaluated, we observed an increased risk of BL among younger participants who reported employment as a cleaner (OR = 2.6; 95% CI = 1.01 to 6.83), especially a char worker cleaner (OR = 3.8; 95% CI = 1.26 to 11.3) based on four exposed cases (Table 4). A char worker cleaner is a person employed to clean and maintain the interiors of buildings. Occupation as a cleaner was not associated with BL among older participants nor was any other occupation associated with BL in younger or older participants (data not shown). Table 4. Association of cleaning-related occupations with sporadic Burkitt lymphoma in the InterLymph NHL Subtypes Project from the basic model, stratified by age*   <50 years  ≥50 years    Controls  Cases      Controls  Cases        N (%)†  N (%)†  OR (95% CI)‡  P  N (%)†  N (%)†  OR (95% CI)‡  P  Cleaners   No  3026 (88.5)  59 (85.5)  1.00 (referent)  .077  6721 (94.5)  54 (96.4)  1.00 (referent)  .863   Yes  137 (4.0)  5 (7.2)  2.62 (1.01 to 6.83)    337 (4.7)  2 (3.6)  0.88 (0.21 to 3.70)    Duration of employment as cleaner   Never  3026 (88.5)  59 (85.5)  1.00 (referent)  .158  6721 (94.5)  54 (96.4)  1.00 (referent)  .051   1–10 years  109 (3.2)  5 (7.2)  3.27 (1.24 to 8.60)    188 (2.6)  0 (0.0)  —     >10 years  23 (0.7)  0 (0.0)  —    143 (2.0)  1 (1.8)  1.14 (0.15 to 8.48)     Yes, missing duration  5 (0.1)  0 (0.0)  —    6 (0.1)  1 (1.8)  – (3.69 to infinity)    Charworker cleaner or related work§   No  3071 (89.8)  60 (87.0)  1.00 (referent)  .040  6473 (96.2)  52 (100.0)  1.00 (referent)  .124   Yes  86 (2.5)  4 (5.8)  3.76 (1.26 to 11.3)    203 (3.0)  0 (0.0)  —    Duration of employment as charworker cleaner   Never  3071 (89.8)  60 (87.0)  1.00 (referent)  .095  6473 (96.2)  52 (100.0)  1.00 (referent)  .500   1–10 years  64 (1.9)  4 (5.8)  5.00 (1.65 to 15.21)    103 (1.5)  0 (0.0)  —     >10 years  18 (0.5)  0 (0.0)  —    99 (1.5)  0 (0.0)  —     Yes, missing duration  4 (0.1)  0 (0.0)  —    1 (0.0)  0 (0.0)  —      <50 years  ≥50 years    Controls  Cases      Controls  Cases        N (%)†  N (%)†  OR (95% CI)‡  P  N (%)†  N (%)†  OR (95% CI)‡  P  Cleaners   No  3026 (88.5)  59 (85.5)  1.00 (referent)  .077  6721 (94.5)  54 (96.4)  1.00 (referent)  .863   Yes  137 (4.0)  5 (7.2)  2.62 (1.01 to 6.83)    337 (4.7)  2 (3.6)  0.88 (0.21 to 3.70)    Duration of employment as cleaner   Never  3026 (88.5)  59 (85.5)  1.00 (referent)  .158  6721 (94.5)  54 (96.4)  1.00 (referent)  .051   1–10 years  109 (3.2)  5 (7.2)  3.27 (1.24 to 8.60)    188 (2.6)  0 (0.0)  —     >10 years  23 (0.7)  0 (0.0)  —    143 (2.0)  1 (1.8)  1.14 (0.15 to 8.48)     Yes, missing duration  5 (0.1)  0 (0.0)  —    6 (0.1)  1 (1.8)  – (3.69 to infinity)    Charworker cleaner or related work§   No  3071 (89.8)  60 (87.0)  1.00 (referent)  .040  6473 (96.2)  52 (100.0)  1.00 (referent)  .124   Yes  86 (2.5)  4 (5.8)  3.76 (1.26 to 11.3)    203 (3.0)  0 (0.0)  —    Duration of employment as charworker cleaner   Never  3071 (89.8)  60 (87.0)  1.00 (referent)  .095  6473 (96.2)  52 (100.0)  1.00 (referent)  .500   1–10 years  64 (1.9)  4 (5.8)  5.00 (1.65 to 15.21)    103 (1.5)  0 (0.0)  —     >10 years  18 (0.5)  0 (0.0)  —    99 (1.5)  0 (0.0)  —     Yes, missing duration  4 (0.1)  0 (0.0)  —    1 (0.0)  0 (0.0)  —    * CI = confidence interval; NHL = non-Hodgkin lymphoma; OR = odds ratio. † The counts do not add up to the total number of cases/controls due to data missing by design or report. ‡ OR (95% CI): adjusted for age, sex, race/ethnicity, and study. § Charworker cleaner is a person who is employed to clean and maintain the interiors of buildings. View Large In the final model, BL in younger participants was associated with a history of allergy (OR = 0.58; 95% CI = 0.32 to 1.05), eczema without other atopic conditions (OR = 2.54; 95% CI = 1.20 to 5.40), taller height (OR = 2.17; 95% CI = 1.08 to 4.36), the use of light-colored hair dye (OR = 2.89; 95% CI = 0.84 to 9.94), and working in a cleaning occupation (OR = 3.49; 95% CI = 1.13 to 10.7) (Table 5). BL in older participants was independently associated with a history of HCV infection (OR = 4.19; 95% CI = 1.05 to 16.6), usual adult body mass index (Ptrend = .049), and consumption of at least one drink of alcohol per month (OR = 0.63; 95% CI = 0.40 to 0.98). Table 5. Independent risk factors for younger and older sporadic Burkitt lymphoma in the InterLymph NHL Subtypes Project from the final model*    OR (95% CI)  P  <50 years   Allergy†   No  1.00 (referent)  .065   Yes  0.58 (0.32 to 10.5)     Eczema without other atopic conditions   No eczema  1.00     Eczema with no other atopic conditions  2.54 (1.20 to 5.40)     Eczema with other atopic conditions  0.51 (0.15 to 1.74)  .041   Usual adult height‡   Quartile 1 (low)  1.00 (referent)  .028   Quartile 2  1.03 (0.46 to 2.30)     Quartile 3  1.31 (0.62 to 2.80)     Quartile 4  2.17 (1.08 to 4.36)     Color of hair dye used   Never hair dye  1.00 (referent)  .014   Light  2.89 (0.84 to 9.94)     Dark  0.37 (0.06 to 2.06)     Charworker cleaner or related work§   No  1.00 (referent)  .054   Yes  3.49 (1.13 to 10.7)    ≥50 years   Hepatitis C virus infection   Negative  1.00 (referent)  .070   Positive  4.19 (1.05 to 16.61)     Usual adult body mass index (kg/m2)   15–<18.5  1.00 (referent)  .049   18.5–<22.5  0.55 (0.15 to 1.97)     22.5–<25  0.37 (0.10 to 1.32)     25–<30  0.27 (0.08 to 0.98)     30–<35  0.56 (0.15 to 2.08)     35–50  0.16 (0.02 to 1.05)     History of alcohol consumption   Non-drinker  1.00 (referent)  .001   Drinker (at least 1 drink per month)  0.63 (0.40 to 0.98)       OR (95% CI)  P  <50 years   Allergy†   No  1.00 (referent)  .065   Yes  0.58 (0.32 to 10.5)     Eczema without other atopic conditions   No eczema  1.00     Eczema with no other atopic conditions  2.54 (1.20 to 5.40)     Eczema with other atopic conditions  0.51 (0.15 to 1.74)  .041   Usual adult height‡   Quartile 1 (low)  1.00 (referent)  .028   Quartile 2  1.03 (0.46 to 2.30)     Quartile 3  1.31 (0.62 to 2.80)     Quartile 4  2.17 (1.08 to 4.36)     Color of hair dye used   Never hair dye  1.00 (referent)  .014   Light  2.89 (0.84 to 9.94)     Dark  0.37 (0.06 to 2.06)     Charworker cleaner or related work§   No  1.00 (referent)  .054   Yes  3.49 (1.13 to 10.7)    ≥50 years   Hepatitis C virus infection   Negative  1.00 (referent)  .070   Positive  4.19 (1.05 to 16.61)     Usual adult body mass index (kg/m2)   15–<18.5  1.00 (referent)  .049   18.5–<22.5  0.55 (0.15 to 1.97)     22.5–<25  0.37 (0.10 to 1.32)     25–<30  0.27 (0.08 to 0.98)     30–<35  0.56 (0.15 to 2.08)     35–50  0.16 (0.02 to 1.05)     History of alcohol consumption   Non-drinker  1.00 (referent)  .001   Drinker (at least 1 drink per month)  0.63 (0.40 to 0.98)    * Table reports results from the final stepwise regression analysis models. CI = confidence interval; NHL = non-Hodgkin lymphoma; OR = odds ratio. † History of allergy includes participants who reported eczema plus other atopic conditions. ‡ Height quartile cutoffs are: 172, 177.8, and 182cm for Q1-2, Q2-3, and Q3-4, respectively, for males, and 159, 163.0, and 168cm, respectively, for females. § Charworker cleaner is a person who is employed to clean and maintain the interior of buildings. View Large The associations with BL found in the age-specific analyses were attenuated or became statistically non-significant when the histological subtypes of BL and BLL were analyzed individually or with the younger and older cases combined (data not shown). There was no evidence of significant interstudy heterogeneity across the studies for the associations found in this study (data not shown). Discussion Our study, which is the first to evaluate a broad range of noninfectious risk factors for BL, showed some differences and similarities between BL in younger and older participants. Specifically, we observed significant inverse associations between BL in younger participants and a history of allergy, and significant positive associations with a history of eczema alone and working in a cleaning occupation, especially as a char worker cleaner. Conversely, among older participants, we observed a positive association with a history of HCV infection based on three exposed cases. Among both younger and older participants, BL was positively associated with height and inversely associated with alcohol consumption. These associations were attenuated or not statistically significant when the histological subtypes of typical BL and BLL were analyzed individually or when younger and older cases were combined. Our results provide epidemiological support for the hypothesis that younger and older adult sporadic BL may be distinct biologically or etiologically (11,12). Our results agree with recent epidemiologic and clinical studies that reported multiple incidence peaks and different outcomes by age (6,10–13,15,21), all suggesting the possibility of etiologically and clinically distinct BL entities at different ages. Because no single parameter is a gold standard for BL diagnosis, and because the diagnosis of BL may be difficult, particularly in older patients (22), diagnostic uncertainty may be a factor in our results. Expert hematopathologists agree on the diagnosis of BL in 80%–90% of pediatric cases, but in only 26%–48% of adult cases (22), in part because the classification of older adult BL has been in some flux during the period of the study (1). Thus, some cases previously diagnosed as BLL might now be reclassified as BL or as a gray-zone lymphoma with features intermediate between BL and diffuse large B-cell lymphoma (4). Gray-zone lymphoma, which is characterized by a pleomorphic tumor cell morphology and complex cytogenetics, sometimes including a combination of c-MYC and BCL2 or BCL6 gene rearrangements (referred to as “double hit” lymphoma) (23), is overrepresented in older patients and has an extremely poor prognosis with standard treatment (24). Further studies are needed to confirm the age-related BL entities and to elucidate their molecular abnormalities. The significant inverse association between younger BL and a history of allergy mirrors the associations that have been reported for diffuse large B-cell lymphoma and follicular lymphoma (25). Allergic diseases appear to be protective against certain NHL subtypes, but the mechanism is unknown. Assuming these results are valid, protective effects could be mediated via immunological hypersensitivity (26) or antitumor cytotoxicity (27). We found a significant positive association between a history of HCV infection and BL only in older participants, based on three cases of BL with HCV infection. This result agrees with the fivefold risk for BL reported among elderly patients in US Medicare data who had two or more insurance claims for HCV infection (28). Although HCV and HIV coinfection are common, particularly in intravenous drug users, coinfection with HIV is unlikely to explain our results because serologically confirmed HIV-positive cases were excluded in the cases in our study. Because HCV infection may increase risk for some NHL subtypes (29), perhaps by inducing chronic immune activation (30), further studies are needed to investigate the potential role of HCV infection in older adult BL. BL in both younger and older participants was positively associated with height. This association has also been reported for other cancers (31,32) and might be indicative of the role of early-life exposures that influence height and also impact risk for cancer, such as insulin-like growth factors. Insulin-like growth factors are correlated with adult height and are thought to modulate cell proliferation and/or turnover (33,34). Our finding that the risk for BL was decreased in both younger and older participants who consumed alcohol is in accord with a previous report using much of the same data (35), but it is unexplained. In contrast to the previous reports of a positive association between use of dark hair dye and NHL risk (36–40), we found a positive association between the use of light-colored hair dye and BL only in younger participants. These results are conflicting and highlight the difficulty of evaluating hair dye use in rare cancers such as BL. A history of working in cleaning occupations, especially as a char worker cleaner, was positively associated with BL in younger participants. This result is similar to the associations reported for all NHL (41) and may point to a role for chemicals that are found in products used for cleaning. The strengths of our pooled analysis include having relatively large case numbers from geographically diverse areas and centrally harmonized data classification and analysis procedures. Because up to one-third of BL cases may be HIV-associated, exclusion of HIV infected cases enabled us to focus our interpretation on adult sporadic BL. The limitations include possible selection and recall biases common to case–control studies, and possible diagnostic errors related to the use of older lymphoma classification systems such as the Working Formulation (16,17) and the 2001 WHO classification for hematologic malignancies (42). Lack of access to archival tissues and slides precluded a central pathology review to confirm and update the diagnoses (1). Lack of tumor Epstein–Barr virus status or molecular characterization also precluded us from evaluating whether Epstein–Barr virus or molecular abnormalities are correlated with the epidemiological clues for distinct BL biology and/or etiology (43). Other limitations include multiple significance tests, which increases the number of expected false-positive findings, and missing data, for example, for HCV infection status, which could have reduced the power to detect weak associations. To summarize, we found both similar and contrasting age-specific patterns of associations for BL with medical history, anthropometric, lifestyle, and occupational risk factors in younger and older participants. These results support the hypothesis that BL in younger and older patients may be etiologically distinct. Funding This pooled analysis was supported by the Intramural Research Program of the National Cancer Institute/National Institutes of Health and National Cancer Institute/National Institutes of Health (R01 CA14690, U01 CA118444, and R01 CA92153-S1). InterLymph annual meetings during 2010–2013 were supported by the Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute/National Institutes of Health (2010–2013); Lymphoma Coalition (2010–2013); National Institutes of Health Office of Rare Diseases Research (2010); National Cancer Institute/National Institutes of Health (R13 CA159842 01) (2011); University of Cagliari, Provincial Administration of Cagliari, Banca di Credito Sardo, and Consorzio Industriale Sardo, Italy (2011); Intramural Research Program of the National Cancer Institute/National Institutes of Health (2012); and Faculté de Médecine de Dijon, Institut de Veille Sanitaire, Registre des hémopathies malignes de Côte d’Or, INSERM, Institut National du Cancer, Université de Bourgogne, Groupe Ouest Est d’Etude des Leucémies et Autres Maladies du Sang (GOELAMS), l’Institut Bergonié, The Lymphoma Study Association (LYSA), Registre Régional des Hémopathies de Basse Normandie, and the City of Dijon, France (2013). Meeting space at the 2013 Annual Meeting of the American Association for Cancer Research (AACR) was provided by the Molecular Epidemiology Group (MEG) of the AACR. Individual studies were supported by: the Canadian Institutes for Health Research (CIHR), Canadian Cancer Society, and Michael Smith Foundation for Health Research (British Columbia); Intramural Research Program of the National Cancer Institute/National Institutes of Health (Iowa/Minnesota); National Cancer Institute/National Institutes of Health (N01-CP-ES-11027) (Kansas); National Cancer Institute/National Institutes of Health (R01 CA50850) (Los Angeles); National Cancer Institute/National Institutes of Health (R01 CA92153 and P50 CA97274), Lymphoma Research Foundation (164738), and the Henry J. Predolin Foundation (Mayo Clinic); Intramural Research Program of the National Cancer Institute/National Institutes of Health and Public Health Service (contracts N01-PC-65064, N01-PC-67008, N01-PC-67009, N01-PC-67010, and N02-PC-71105) (NCI-SEER); National Cancer Institute/National Institutes of Health (R01CA100555 and R03CA132153) and American Institute for Cancer Research (99B083) (Nebraska [newer]); National Cancer Institute/National Institutes of Health (N01-CP-95618) and State of Nebraska Department of Health (LB-506) (Nebraska [older]); National Cancer Institute/National Institutes of Health (R01CA45614, RO1CA154643-01A1, and R01CA104682) (UCSF1); National Cancer Institute/National Institutes of Health (CA143947, CA150037, R01CA087014, R01CA104682, RO1CA122663, and RO1CA154643-01A1) (UCSF2); National Heart Lung and Blood Institute/National Institutes of Health (hematology training grant award T32 HL007152), National Center for Research Resources/National Institutes of Health (UL 1 RR024160), and National Cancer Institute/National Institutes of Health (K23 CA102216 and P50 CA130805) (University of Rochester); National Cancer Institute/National Institutes of Health (CA62006 and CA165923) (Yale); Association pour la Recherche contre le Cancer, Fondation de France, AFSSET, and a donation from Faberge employees (Engela); European Commission (QLK4-CT-2000-00422 and FOOD-CT-2006-023103), Spanish Ministry of Health (CIBERESP, PI11/01810, 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, 2009SGR1026), 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, Cancer Research, Ireland, and Czech Republic MH CZ - DRO (MMCI, 00209805) (EpiLymph); National Cancer Institute/National Institutes of Health (CA51086), European Community (Europe Against Cancer Programme), and Italian Alliance Against Cancer (Lega Italiana per la Lotta contro i Tumori) (Italy, multicenter); Italian Association for Cancer Research (Italy, Aviano-Milan); Italian Association for Cancer Research (Italy, Aviano-Naples); Swedish Cancer Society (2009/659), Stockholm County Council (20110209), Strategic Research Program in Epidemiology at Karolinska Institut, Swedish Cancer Society (02 6661), Danish Cancer Research Foundation, Lundbeck Foundation (R19-A2364), Danish Cancer Society (DP 08-155), National Cancer Institute/National Institutes of Health (5R01 CA69669-02), and Plan Denmark (SCALE); Leukaemia & Lymphoma Research, UK; and Australian National Health and Medical Research Council (ID990920), Cancer Council NSW, and University of Sydney Faculty of Medicine (New South Wales). 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JNCI Monographs – Oxford University Press

Published: Aug 30, 2014

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