25gmds150 10.3205/25gmds150 urn:nbn:de:0183-25gmds1502 Meeting Abstract Görlich Görlich Dennis D

Universität Münster, Institut für Biometrie und Klinische Forschung, Münster, Germany

author Lanwer Lanwer Leonas L

Universität Münster, Institut für Biometrie und Klinische Forschung, Münster, Germany Universität Bremen, Bremen, Germany

author Sauerland Sauerland Cristina C

Universität Münster, Institut für Biometrie und Klinische Forschung, Münster, Germany

author Faldum Faldum Andreas A

Universität Münster, Institut für Biometrie und Klinische Forschung, Münster, Germany

author German Medical Science GMS Publishing House

Düsseldorf

610 competing risk analysis acute myeloid leukemia trends in overall survival retrospective analysis 20251103 engl This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License. Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). M0631 150 Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie 70. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS) PS 8: Medizinische Biometrie Jena 20250907 20250911 Abstr. 38 TextBackground: The analysis of trends in overall survival after leukemia is an ongoing research field , , , . We characterized the improvement in overall survival after acute myeloid leukemia (AML) over 46 years based on US registry data.Methods: We accessed unique patient data covering the years 1975 to 2021 from the US Surveillance, Epidemiology, and End Results Program (SEER) , . Overall survival (OS) was analyzed by Kaplan-Meier estimates and Cox-proportional-hazard models showing hazard ratios (HROS) per diagnosis year (reference 1975) by age (≤60 vs. 60+ years(y)), sex, and chemotherapy treatment (yes vs. no/unknown). An interaction term between cofactor and diagnosis year estimated group specific HRs for each year. A competing risk analysis (CRA) was performed with the Fine-Gray model , considering two competing events: “AML-related death” and “non-AML causes of death”. The CRA facilitated also an interaction-term to estimate sub-distribution HRs for the competing events (HRAML and HRother) by covariables.Data was extracted using the SEER*Stat software . Further data preparation and data analysis was performed within SAS software (Version 9.4 for Windows, SAS Institute Inc., Cary, NC, USA).Results: From the current SEER data (4,633,916 oncologic cases) information of 37,615 unique patients (excluding patients under 18y or with missing survival times) were extracted and analyzed. 45.5% of patients were female, and the median age was 68y (range: 18-90y). 5-year OS rates improved monotonously over time (1975-1979: 4.5%, 2010-2019: 20.8%, p<0.0001). In the CRA we could attribute this trend to the AML-related mortality (HRAML). HRother showed no progress, also with respect to all analyzed covariables. Patients ≤60y displayed an overall improvement in HRAML (HRAML;1976: 1.186 (95%CI: 0.977, 1.441); HRAML;2021: 0.276 (95%CI: 0.203, 0.375)). Older patients (60y+) had no benefit until the mid-2000s, thereafter a noticeable decrease in HRAML can be found, i.e. HRAML;2011 being the first showing a significant effect (HR: 0.790 (95%CI: 0.687, 0.908)). Treated patients showed a continuous reduction in risk (HRAML;1976: 1.083 (95% CI: 0.934, 1.257) to HRAML;2021: 0.384 (95%CI :0.327, 0.452)). Untreated patients displayed no such trends in HRAML.Conclusions & discussion: We hypothesize that the improved HROS in AML patients as well as the more specifically characterized improvement of HRAML can be attributed to advancements in therapy specificity and efficiency . The substantial change in HRAML trend for older patients (60y+) in the mid-2000s could be related to a changing treatment paradigm in this cohort , , . Our approach has several limitations, including insufficient information on patient characteristics, as well as a potential time-dependence in the age and chemotherapy covariates. These issues should be tackled in future research.The authors declare that they have no competing interests.The authors declare that an ethics committee vote is not required.The contribution has already been published: Pulte D Gondos A Brenner H Improvements in survival of adults diagnosed with acute myeloblastic leukemia in the early 21st century 2008 Haematologica 594-600 Pulte D, Gondos A, Brenner H. Improvements in survival of adults diagnosed with acute myeloblastic leukemia in the early 21st century. Haematologica. 2008;93(4):594-600. Thein MS Ershler WB Jemal A Yates JW Baer MR Outcome of older patients with acute myeloid leukemia: an analysis of SEER data over 3 decades 2013 Cancer 2720-2727 Thein MS, Ershler WB, Jemal A, Yates JW, Baer MR. Outcome of older patients with acute myeloid leukemia: an analysis of SEER data over 3 decades. Cancer. 2013;119(15):2720-2727. Bertoli S Tavitian S Huynh A Improved outcome for AML patients over the years 2000-2014 2017 Blood Cancer J 635 Bertoli S, Tavitian S, Huynh A, et al. Improved outcome for AML patients over the years 2000-2014. Blood Cancer J. 2017;7(12):635. Yang X Chen H Man J Secular trends in the incidence and survival of all leukemia types in the United States from 1975 to 2017 2021 J Cancer 2326-2335 Yang X, Chen H, Man J, et al. Secular trends in the incidence and survival of all leukemia types in the United States from 1975 to 2017. J Cancer. 2021;12(8):2326-2335. Anonym Surveillance, Epidemiology, and End Results (SEER) Program. SEER*Stat Database: Incidence - SEER Research Data, 8 Registries, Nov 2023 Sub (1975-2021) - Linked To County Attributes - Time Dependent (1990-2022) Income/Rurality, 1969-2022 Counties, National Cancer Institute, DCCPS, Surveillance Research Program, released April 2024, based on the November 2023 submission. Surveillance, Epidemiology, and End Results (SEER) Program. SEER*Stat Database: Incidence - SEER Research Data, 8 Registries, Nov 2023 Sub (1975-2021) - Linked To County Attributes - Time Dependent (1990-2022) Income/Rurality, 1969-2022 Counties, National Cancer Institute, DCCPS, Surveillance Research Program, released April 2024, based on the November 2023 submission. Anonym SEER*Stat software SEER*Stat software. Version 8.4.3. Cox DR Regression Models and Life-Tables 1972 J R Stat Soc Series B Stat Methodol 187–220 Cox DR.  Regression Models and Life-Tables. J R Stat Soc Series B Stat Methodol. 1972;34(2):187–220. Fine JP Gray RJ A Proportional Hazards Model for the Subdistribution of a Competing Risk 1999 Journal of the American Statistical Association 496-509 Fine JP, Gray RJ. A Proportional Hazards Model for the Subdistribution of a Competing Risk. Journal of the American Statistical Association. 1999;94(446):496-509. Kantarjian HM Short NJ Fathi AT Acute Myeloid Leukemia: Historical Perspective and Progress in Research and Therapy Over 5 Decades 2021 Clin Lymphoma Myeloma Leuk 580-597 Kantarjian HM, Short NJ, Fathi AT, et al. Acute Myeloid Leukemia: Historical Perspective and Progress in Research and Therapy Over 5 Decades. Clin Lymphoma Myeloma Leuk. 2021;21(9):580-597. Muffly L Pasquini MC Martens M Increasing use of allogeneic hematopoietic cell transplantation in patients aged 70 years and older in the United States 2017 Blood 1156-1164 Muffly L, Pasquini MC, Martens M, et al. Increasing use of allogeneic hematopoietic cell transplantation in patients aged 70 years and older in the United States. Blood. 2017;130(9):1156-1164. Dombret H Seymour JF Butrym A International phase 3 study of azacitidine vs conventional care regimens in older patients with newly diagnosed AML with >30% blasts 2015 Blood 291-299 Dombret H, Seymour JF, Butrym A, et al. International phase 3 study of azacitidine vs conventional care regimens in older patients with newly diagnosed AML with >30% blasts. Blood. 2015;126(3):291-299. DiNardo CD Jonas BA Pullarkat V Azacitidine and Venetoclax in Previously Untreated Acute Myeloid Leukemia 2020 N Engl J Med 617-629 DiNardo CD, Jonas BA, Pullarkat V, et al. Azacitidine and Venetoclax in Previously Untreated Acute Myeloid Leukemia. N Engl J Med. 2020;383(7):617-629. Görlich D Lanwer L Sauerland C Faldum A P010 - Characterizing overall survival in AML patients: A competing risk analysis of SEER data covering 46 years 2025 Annals of Hematology 1-68 Görlich D, Lanwer L, Sauerland C, Faldum A. P010 - Characterizing overall survival in AML patients: A competing risk analysis of SEER data covering 46 years [Symposium Proceedings of the international symposium ACUTE LEUKEMIAS XIX (ISALXIX), Munich March 16–19, 2025]. Annals of Hematology. 2025;104:1-68. DOI: 10.1007/s00277-024-06139-3 https://doi.org/10.1007/s00277-024-06139-3 0 0 0 0