Ability of STAR-CAP staging system to prognosticate risk of subsequent therapies after initial treatment of M0 prostate cancer.

Abstract

310 Background: Given lower mortality rates and life expectancy loss in prostate cancer, treatment regimens must consider long-term outcomes with quality of life. Aggressiveness of treatment impacts severity of side effects and depends on the highly heterogeneous staging of the disease at onset. Staging and risk-classification systems have been developed, including STAR-CAP staging system which informs prognosis and could help with treatment intensification decisions. Compared with existing models such as the AJCC, STAR-CAP had superior performance and prognostic power for disease mortality prediction. However the risk of requiring subsequent therapies (ie salvage radiation therapy or androgen deprivation therapies after initial treatment) has not been described in STAR-CAP cohorts. Quantifying risk of subsequent therapies after initial therapies is clinically useful to help patients decide between various management strategies and whether monotherapies or multi-modality therapies may be sufficient. Methods: Patients who could be stratified by STAR-CAP system and underwent surgery or radiation therapy were identified from an institutional observational registry. Patients treated before 2010 were gathered retrospectively (n=835) and prospectively thereafter (n=2588). The primary endpoint was progression to additional therapy after primary treatment (radiation, surgery, or systemic therapy). Risk of progression accounting for STAR-CAP group was estimated using the Fine and Gray Competing risk model, with death as the competing risk. P<0.05 was considered statistically significant. Results: 3424 men diagnosed with prostate cancer underwent curative-intent treatment with surgery or radiation therapy (RT) between 1995 – 2022. The median age at diagnosis was 64.9 years (IQR 59.4 to 70.0); median follow-up time was 5.4 years. Patients with STAR-CAP 1A-1C had a statistically similar risk of requiring additional therapies, whereas those with 2A to 3B disease had a significantly and incrementally higher risk of requiring additional therapies (by group, hazard ratios and 95% CI: 2A, 1.8 (1.2 to 2.5); 2B, 2.9 (2.1 to 4.2); 2C, 3.4 (2.4 to 4.9); 3A, 5.7 (3.9 to 8.3); 3B, 7.0 (4.4 to 11.1), all p<0.001). The 5-year risks of requiring additional therapy after surgery for a Stage 1A, 2A, and 3A patient is 9.7%, 16.2%, and 38%, respectively. The 5-year risks of requiring additional therapy after radiation with or without ADT for a Stage 1A, 2A, and 3A patient are 7.3%, 10.4% and 27.9%, respectively. Conclusions: The STAR-CAP grouping system can prognosticate risk of requiring additional therapies after primary treatment of localized prostate cancer. The lower risk of subsequent therapy seen in RT patients is likely due to use of ADT with RT. Using STAR-CAP to prognosticate risk of subsequent therapies after primary treatment can help guide treatment intensification decisions upfront.