Cancer-attributable costs in older adults: SEER-Medicare analysis of variation by site, stage, and race
Menée à partir de données portant sur des patients atteints d'un cancer dignostiqué entre 2008 et 2019 (âge : au moins 66 ans), cette étude estime les coûts associés à la maladie en fonction de sa localisation, du stade et de l'origine ethnique
Background: Advances in cancer treatment and increased survivorship have altered the economic burden of cancer care. Updated patient-level estimates of cancer-attributable costs, based on clinical and socioeconomic factors, are required.
Methods: Using the Surveillance, Epidemiology, and End Results (SEER)-Medicare linked data, we identified individuals aged ≥66 years who were diagnosed with cancer during 2008-2019 and matched controls without a cancer history based on demographic characteristics, comorbidity burden, and area-level socioeconomic status. Cancer-attributable costs were estimated for 2013-2019 according to cancer site, stage, age, sex, race, and calendar year. Phases of care were defined as initial (first 12 months after diagnosis), continuing, and end-of-life (EOL; final 12 months before death from cancer). Net annualized cancer-attributable costs were calculated as the difference between cases and matched controls and are reported in USD 2023.
Results: Net annualized cancer-attributable medical service costs were highest in the EOL phase ($121 746), followed by the initial ($45 063), and continuing ($7141) phases. Oral prescription drug costs increased over time across all phases, particularly in EOL (from $4823 in 2013 to $11 620 in 2019), whereas medical service and hospitalization costs remained relatively stable after adjustment for inflation. Acute leukemia and distant-stage cancers incurred the highest cost. Cancer-attributable costs were higher among Black individuals and individuals of other races than among White individuals.
Conclusion(s): Cancer-attributable costs vary substantially according to the care phase, cancer type, stage at diagnosis, and race. Rising costs, particularly for EOL care and prescription drugs, highlight the importance of aligning treatment intensity with patient goals and providing critical inputs for simulation and cost-effectiveness analyses of cancer-control interventions.
Journal of the National Cancer Institute , résumé, 2026