Development of a novel risk model to predict CRPC progression following IMRT: Implications for tailoring treatment intensity

开发一种预测 IMRT 后 CRPC 进展的新型风险模型:对调整治疗强度的启示

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Abstract

OBJECTIVES: To develop a novel risk score (RS) model to predict the probability of progression to castration-resistant prostate cancer (PCa) (CRPC) after intensity-modulated radiation therapy (IMRT) for patients with high- and very high-risk PCa according to the National Comprehensive Cancer Network (NCCN) risk classification, since accurate prediction of the clinical outcome of definitive radiation therapy for patients with high- and very high-risk PCa remains challenging due to its heterogeneity. MATERIALS AND METHODS: We conducted a retrospective review of 600 patients with high- and very high-risk PCa treated with IMRT at our institution. They were randomly divided into discovery (n = 300) and validation (n = 300) cohorts. A predictive RS model was created using a dataset from the discovery cohort based on the following parameters: T-stage, Gleason score, prostate-specific antigen and age at initiation of IMRT. The model was internally validated using a dataset from the validation cohort. RS was calculated using multivariable Cox regression analysis, and patients were categorized into low-risk, intermediate-risk or high-risk based on the value. RESULTS: The median follow-up period of the 600 patients was 9.1 (IQR: 6.1-11.6) years. The 10-year CRPC-free rates for low-, intermediate- and high-risk categories were 100.0, 90.4 and 61.4% in the discovery cohort, respectively (p < 0.001). Such differences were reproduced in the validation cohort. Specifically, those rates for low-, intermediate- and high-risk categories were 96.4, 90.7 and 74.8% in the validation cohort, respectively (p < 0.001). Harrell's C-index for this model was 0.692, being higher than that of the NCCN risk classification (0.617). CONCLUSION: This RS model provided useful information to enable tailoring of the treatment intensity for this heterogeneous population.

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