Nookala, Vinod

11186 Background: Cancer survival is shaped by tumor biology, treatment access, and socioeconomic context, yet population-level quantification of long-term survival disparities related to chemotherapy use and income is limited. We assessed five-year cancer-specific survival across demographic, treatment, and socioeconomic strata in a national registry. Methods: We performed a retrospective, population-based survival analysis using the Surveillance, Epidemiology, and End Results (SEER) database. Cancer-specific survival was evaluated at 12, 24, 36, 48, and 60 months after diagnosis. Outcomes were stratified by sex, race, chemotherapy receipt, and area-level median household income categories. Survival estimates were summarized descriptively and visualized using time-to-event curves. Results: Overall cancer-specific survival declined progressively over five years, from ~84% at 12 months to ~58% at 60 months. Sex differences were minimal, with similar five-year survival among males and females (~57–58%). Racial disparities were substantial: Asian/Pacific Islander patients demonstrated the highest survival across follow-up, while Black and American Indian/Alaska Native patients had lower early survival and persistent gaps at five years. Patients with recorded chemotherapy use had improved survival compared with those without or with unknown chemotherapy status; 12-month survival was ~88% versus ~80%, and five-year survival was ~65% versus ~57%, respectively. A pronounced socioeconomic gradient was observed: individuals in areas with median household income ≥$120,000 had higher five-year survival (~67%), whereas those in areas with income < $40,000 had markedly lower survival (~52%). Conclusions: In this national registry analysis, both chemotherapy utilization and higher socioeconomic status were strongly associated with improved long-term cancer survival, whereas persistent racial and income-related disparities remained evident. These findings highlight ongoing inequities in access to oncologic care and support the need for targeted policy interventions and equity-focused treatment delivery models. Interpretation should account for limitations inherent to observational registry data and potential residual confounding.