Session: 623. Mantle Cell, Follicular, Waldenstrom’s, and Other Indolent B Cell Lymphomas: Clinical and Epidemiological: Poster I
Hematology Disease Topics & Pathways:
Research, Adult, Epidemiology, Lymphomas, Non-Hodgkin lymphoma, Elderly, Clinical Research, B Cell lymphoma, Diseases, Real-world evidence, Treatment Considerations, Lymphoid Malignancies, Registries, Study Population, Human
Mantle cell lymphoma (MCL) is more common in males, with a male to female ratio of approximately 3:1. However, it is unclear whether disease characteristics and survival outcomes differ by sex. Additionally, the impact of race and ethnicity in MCL is understudied due to underrepresentation of minorities in clinical studies and trials. In this study, we utilized the National Cancer Database (NCDB) to examine patient and disease characteristics and survival outcomes of MCL by sex, race and ethnicity.
Methods
Patients diagnosed with MCL in 2004-2020 were identified from NCDB. Patient and disease characteristics were compared between groups using Chi-squared tests. Overall survival (OS) analysis was performed using the Kaplan-Meier method and the Cox proportional hazards model.
Results
A total of 35,135 patients was included. The median follow-up was 83.0 months (95% CI 81.9-84.1). 24,980 (71.1%) patients were male and 10,155 (28.9%) were female. Females had more elderly (age ≥65: 65.9% vs 59.0%; p<0.001), lower Charlson-Deyo Score (CDS ≥2: 7.0% vs 8.6%; p<0.001) and fewer stage III-IV diagnoses (80.5% vs 82.6%; p<0.001). Females were less likely to receive upfront treatment (80.7% vs 85.3%; p<0.001), treatment at academic centers (36.8% vs 40.9%; p<0.001) or transplant (11.0% vs 13.7%; p<0.001). Compared to males, females were more likely to live in metropolitan areas (83.7% vs 81.6%; p<0.001), had similar incomes, had more Medicare (60.4% vs 53.1%) and fewer private insurance (33.2% vs 38.6%; p<0.001). Female patients had better OS, with a median OS of 76.0 (95% CI 72.4-79.6) vs 67.8 months (95% CI 65.9-69.6; p<0.001). In the multivariable Cox model adjusting for age, race, ethnicity, CDS, stage, upfront treatment (vs surveillance or no treatment), facility (academic vs nonacademic), transplant, residence (metropolitan vs urban or rural) and insurance, female sex remained associated with superior OS (HR 0.84, 95% CI 0.793-0.890; p<0.001).
For race, 32,399 (92.2%) patients were White, 1,465 (4.2%) were Black, 942 (2.7%) were others and 329 (0.9%) were unknown. Compared to White patients, Black patients had fewer elderly (52.9% vs 61.7%; p<0.001), higher CDS (≥2: 11.4% vs 7.9%; p<0.001), similar stage III-IV (80.7% vs 82.1%; p=0.276) and upfront treatment (84.7% vs 84.0%; p=0.074), were more likely to be treated at academic centers (50.6% vs 38.9%; p<0.001), were less likely to receive transplant (11.1% vs 13.0%; p=0.042), were more likely to live in metropolitan areas (91.0% vs 81.5%; p<0.001), had lower income, had more uninsured (4.4% vs 2.0%) and Medicaid (9.8% vs 3.7%) and fewer Medicare (47.4% vs 56.0%; p<0.001). Black and White patients had similar OS, with a median of 67.9 (95% CI 57.5-78.2) vs 69.6 months (95% CI 67.8 vs 71.3; p=0.697). In the multivariable Cox model, Black vs White race was not associated with OS (HR 1.086, 95% CI 0.952-1.240; p=0.219).
For ethnicity, 31,717 (90.3%) patients were non-Hispanic, 1,894 (5.4%) were Hispanic and 1,534 (4.3%) were unknown. Hispanics had fewer elderly (51.3% vs 61.5%; p<0.001), lower CDS (≥2: 6.4% vs 8.2%; p=0.018), similar stage III-IV (81.2% vs 82.1%; p=0.467), were more likely to receive upfront treatment (86.0% vs 83.9%; p<0.001), more likely to be treated at academic centers (49.9% vs 39.5%; p<0.001), equally likely to receive transplant (13.0% vs 13.1%; p=0.943), more likely to live in metropolitan areas (95.4% vs 81.6%; p<0.001), had lower income, had more uninsured (9.6% vs 1.8%) and Medicaid (15.2% vs 9.6%) and fewer Medicare (40.3% vs 55.9%; p<0.001). Hispanics had better OS, with a median OS of 84.4 (95% CI 71.7-97.1) vs 70.5 months (95% CI 68.7-72.2; p<0.001). However, in the multivariable Cox model, Hispanic ethnicity was not associated with OS (HR 0.952, 95% CI 0.839-1.080; p=0.448).
Conclusion
This study is the first of its scale to demonstrate that female MCL patients have superior survival outcomes compared to males. It also demonstrated that neither Black race nor Hispanic ethnicity appears to be associated with worse survival outcomes. Despite its size, the NCDB is limited in the treatment information and disease characteristics it provides, including MIPI score, Ki-67, blastoid/pleomorphic morphology, and TP53 status. Thus, additional real-world dataset studies are needed to gain a deeper understanding of potential differences in sex, race and ethnicity with regards to disease characteristics and survival outcomes.
Disclosures: Tun: Gossamerbio: Research Funding; Curis: Consultancy. Munoz: Targeted Oncology, OncView, Curio, Genzyme, and Physicians' Education Resource: Honoraria; Pharmacyclics/Abbvie, Bayer, Gilead/Kite, Beigene, Pfizer, Janssen, Celgene/BMS, Kyowa, Alexion, Fosunkite, Seattle Genetics, Karyopharm, Aurobindo, Verastem, Genmab, Genzyme, Genentech/Roche, ADC Therapeutics, Epizyme, Beigene, Novartis, Morphosys/Incyte: Consultancy; Bayer, Gilead/Kite, Celgene, Merck, Portola, Incyte, Genentech, Pharmacyclics, Seattle Genetics, Janssen, Millennium, Novartis, BeiGene: Research Funding. Paludo: Biofourmis: Research Funding; AstraZeneca: Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Research Funding. Alhaj Moustafa: AbbVie: Consultancy. Diefenbach: FATE Therapeutics: Consultancy, Research Funding; Morphosys: Consultancy, Research Funding; Millenium: Research Funding; Merck: Consultancy, Research Funding; Gilead: Current equity holder in publicly-traded company, Research Funding; Genmab: Consultancy, Research Funding; Genentech/Roche: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Incyte: Consultancy, Research Funding; MEI Pharma: Consultancy, Research Funding; I MAB: Consultancy, Current equity holder in private company; NYU Grossman School of Medicine/Perlmutter Cancer Center at NYU Langone Health: Current Employment; OverT Therapeutics: Current equity holder in private company; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Seattle Genetics: Consultancy, Research Funding. Ruan: BMS: Honoraria, Research Funding; Janssen: Honoraria; Genentech: Research Funding; AstraZeneca: Honoraria, Research Funding. Martin: AbbVie, AstraZeneca, Beigene, Daiichi Sankyo, Genentech, Janssen, Merck, Pepromene: Consultancy. Habermann: Lilly: Other: Data Monitoring Committee. Nowakowski: Bristol-Myers Squibb: Consultancy, Research Funding; F. Hoffmann-La Roche Limited: Consultancy; MorphoSys AG: Consultancy, Research Funding; Karyopharm Therapeutics: Consultancy; Daiichi Sankyo: Consultancy; ADC Therapeutics: Consultancy; Genentech: Consultancy; Segen: Consultancy; Bantam Pharmaceutical, LLC: Consultancy; Blueprint Medicines Corporation: Consultancy; AbbVie Inc.: Consultancy; TG Therapeutics Inc: Consultancy; Constellation Pharmaceuticals: Consultancy; Zai Laboratory: Consultancy; Kymera Therapeutics: Consultancy; Debiopharm: Consultancy; Selvita Inc: Consultancy; Fate Therapeutics: Consultancy; Incyte Corporation: Consultancy; MEI Pharma: Consultancy; Ryvu Therapeutics: Consultancy; Celgene Corporation: Consultancy, Research Funding; Curis: Consultancy, Research Funding. Wang: InnoCare, AbbVie: Consultancy; Kite: Honoraria; Eli Lilly, LOXO Oncology, TG Therapeutics, Incyte, InnoCare, Kite, Jansen, BeiGene, AstraZeneca, Genmab, AbbVie: Other: Advisory Board; Incyte, InnoCare, LOXO Oncology, Eli Lilly, MorphoSys, Novartis, Genentech, Genmab, AbbVie, BeiGene, Merck: Research Funding.