MON-496 Development and validation of a novel prognostic model for overall survival in patients with adrenocortical carcinoma

Abstract Disclosure: L.N. Diamantopoulos: None. M. Tsikala-Vafea: None. D. Makrakis: None. E. Fisher: None. N. Profaizer: None. D. Korentzelos: None. M. Alevizakos: None. V. Bountziouka: None. K. Vadikolias: None. M. Lambropoulou: None. D. Matthaios: None. G. Tripsianis: None. Introduction: Adrenocortical carcinoma (ACC) is a rare entity with limited prognostic data in the literature. We hereby present a novel prognostic model for overall survival (OS), for patients with ACC, derived from the Surveillance, Epidemiology and End Results (SEER) database. Materials and Methods: The SEER database (18 registries/November 2020) was queried with the case listing method by using the ICD-10 topography codes C74.0-9 (adrenal gland), and the morphologic code 8370 (ACC). Patients were randomly divided into a training (TC) and a validation cohort (VC) (7:3 ratio). Variables significantly associated with OS were identified with multivariate Cox regression and backwards stepwise conditional approach; Each variable received “points” according to its beta coefficient, based on the formula: Probability of an event at time t=S0(t)exp(β1x1, β2x2⋯), (β = regression coefficients, x = observed covariate values, S0(t) = survival function). Cumulative risk points were assigned to each patient to calculate a risk score and four distinct risk categories for OS were constructed. Harrel’s optimism-corrected C-statistic with bootstrap resampling was used for internal (TC) and external (VC) validation. Discriminatory performance of the model was compared to the AJCC staging system with the likelihood ratio test (LRT). Results: 1388 patients were included in the study (992 TC, 396 VC). No statistically significant differences in baseline characteristics and survival outcomes were identified between TC and VC. Age, race, AJCC stage, adrenalectomy, radiation and chemotherapy were significant variables inserted in the multivariate model. Based on their risk score patients were stratified to four risk groups (low; score 0-49, intermediate; score 50-99, high; score 100-149, very high; score 150+). Median OS was 106 (95%CI; 59-153), 33 (95% CI; 25-41), 16 (95% CI; 12-20) and 4 months (95% CI; 3-5) for the low, intermediate, high and very high-risk categories respectively (log-rank p<.001). Optimism-corrected C-statistic for the prognostic score was 0.75 (95%CI;0.73-0.77) in the TC and 0.74 (95%CI; 0.72-0.76) in the VC. In comparison C-statistic for AJCC was 0.70 (95% CI; 0.68-0.72) and 0.69 (95% CI; 0.66 to 0.72) in the TC and VC respectively. The LRT demonstrated superior discriminatory performance of our prognostic model compared to AJCC (p<.001). Conclusion: We present a novel prognostic model for OS of patients with ACC composed of clinicopathologic and treatment variables. Our model had superior performance to the AJCC system and may serve as a useful tool for individualized risk assessment in patients with ACC. Presentation: Monday, July 14, 2025