Friesen, Melissa C.

Abstract Background: Epidemiologic and other studies have identified environmental, occupational, and genetic risk factors for lymphoid and myeloid malignancies, but most studies have been conducted in Western populations. Investigations in populations with differing exposure patterns, distributions of disease subtypes, and genetic architecture are needed to fully understand hematopoietic tumor etiology. Methods: We conducted a large, multicenter, hospital-based case-control study of lymphoid and myeloid neoplasms in East Asia (AsiaLymph), including 5,671 lymphoid cases, 1,879 myeloid cases, and 3,858 controls. Participants completed a computer-assisted personal interview and provided biospecimens. Cases underwent central pathology review and were coded into the WHO Classification. Herein, we describe the study methods in detail and report association results for education, body mass index, and family history. Results: Greater BMI at age 20 but not at age 40 was associated with odds of total lymphoid neoplasm (per 5 kg/m2 increase: OR [95% CI]: 1.18 [1.09-1.27]), total myeloid neoplasm (OR [95% CI]: 1.17 [1.05-1.29]), and several subtypes. Greater educational attainment was associated with increased odds of total lymphoid neoplasm (for college vs. less than primary education: OR [95% CI]: 1.41 [1.21-1.65]) but not myeloid neoplasm (OR [95% CI]: 1.17 [0.95-1.45]; p-heterogeneity=0.02). There were also positive associations between family history of hematologic cancer in first degree relatives and odds of lymphoid neoplasm (OR [95% CI]: 1.53 [1.15-2.03]) and myeloid neoplasm (OR [95% CI]: 1.65 [1.11-2.44]) and specific subtypes. None of the evaluated risk factors were associated with NK/T-cell lymphoma, which supports a distinct etiology for this subtype. Conclusion: The AsiaLymph Study is one of the largest molecular epidemiology studies of both lymphoid and myeloid neoplasms with standardized World Health Organization classification of histopathologic subtypes and will serve as a valuable resource for etiologic investigations into risk factors for these malignancies. Citation Format: Qing Lan, Lauren M. Hurwitz, John K. Chan, Tai Hing Lam, Kexin Chen, Yok Lam Kwong, Xu Caigang, Brian CH Chiu, Raymond Liang, Ip Dennis, Wei Hu, Bryan Bassig, Mark Purdue, Jun Xu, Sarah Locke, Sophia S. Wang, James R. Cerhan, Sonja Berndt, Jonathan N. Hofmann, Jianxin Shi, Kai Yu, Shahinaz Gadalla, Lisa J. McReynolds, Rena Jones, Hongji Dai, Zhangyan Lyu, Lugui Qiu, Wei Liu, Huilai Zhang, Xianhuo Wang, Lindsay M. Morton, Stephen Chanock, Martha Linet, Melissa C. Friesen, Roel Vermeulen, Nathaniel Rothman. A multi-center hospital-based case-control study of lymphoid and myeloid neoplasms (AsiaLymph): Study design and initial findings for education, body mass index, and family history [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 5051.

Objectives Growing evidence suggests that gender-blind assessment of exposure may introduce exposure misclassification, but few studies have characterised gender differences across occupations and industries. We pooled control responses to job-specific, industry-specific and exposure-specific questionnaires (modules) that asked detailed questions about work activities from three US population-based case–control studies to examine gender differences in work tasks and their frequencies. Methods We calculated the ratio of female-to-male controls that completed each module. For four job modules (assembly worker, machinist, health professional, janitor/cleaner) and for subgroups of jobs that completed those modules, we evaluated gender differences in task prevalence and frequency using χ2 and Mann–Whitney U tests, respectively. Results The 1360 female and 2245 male controls reported 6033 and 12 083 jobs, respectively. Gender differences in female:male module completion ratios were observed for 39 of 45 modules completed by ≥20 controls. Gender differences in task prevalence varied in direction and magnitude. For example, female janitors were significantly more likely to polish furniture (79% vs 44%), while male janitors were more likely to strip floors (73% vs 50%). Women usually reported more time spent on tasks than men. For example, the median hours per week spent degreasing for production workers in product manufacturing industries was 6.3 for women and 3.0 for men. Conclusions Observed gender differences may reflect actual differences in tasks performed or differences in recall, reporting or perception, all of which contribute to exposure misclassification and impact relative risk estimates. Our findings reinforce the need to capture subject-specific information on work tasks.