Multimodal artificial intelligence prediction of abiraterone efficacy in two STAMPEDE phase III trials of nonmetastatic very high-risk prostate cancer.

BACKGROUND

Long-term androgen deprivation therapy (LT-ADT) with radiotherapy is standard-of-care for high-risk localized prostate cancer, with abiraterone added for clinically very high-risk disease. Given the potential toxicity and cost of abiraterone, a predictive biomarker to refine patient selection is needed. We evaluated a digital pathology multimodal artificial intelligence (MMAI) model, previously validated as a prognostic biomarker, for prediction of abiraterone benefit among nonmetastatic clinically very high-risk prostate cancer.

PATIENTS AND

METHODS

MMAI scores were generated for patients enrolled in two sequential abiraterone trials (no shared controls) in the STAMPEDE (Systemic Therapy in Advancing or Metastatic Prostate Cancer: Evaluation of Drug Efficacy) platform protocol (NCT00268476) using digital pathology images, prostate-specific antigen, tumor stage, and age. We applied the previously established 75th percentile threshold to classify patients as MMAI very high-risk or standard high-risk. The primary endpoint was metastasis-free survival (MFS). Treatment effects and risk estimates were obtained using Cox regression and Kaplan-Meier method, respectively. Prediction was assessed using a treatment-by-biomarker interaction Cox model.

RESULTS

In total, 1137 patients randomly assigned to LT-ADT (N = 583) or LT-ADT with abiraterone (N = 554) were included. The MMAI very high-risk group (N = 268) demonstrated significant MFS improvement from adding abiraterone [hazard ratio (HR) 0.47, 95% confidence interval (CI) 0.31-0.70], with 5-year MFS increasing from 62% (95% CI 54% to 70%) in LT-ADT to 81% (95% CI 74% to 88%) in LT-ADT with abiraterone. Limited abiraterone benefit was observed in the MMAI standard high-risk group (N = 869; HR 0.83, 95% CI 0.63-1.09), with a 5-year MFS of 82% (95% CI 78% to 85%) versus 84% (95% CI 80% to 87%, interaction P-value = 0.02). This differential effect was consistent in local node-negative and node-positive subgroups.

CONCLUSION

In this post hoc study of randomized clinical trial data, a locked digital pathology MMAI test displayed a strong prognostic association and predicted abiraterone efficacy in very high-risk, nonmetastatic prostate cancer. This biomarker could be implemented clinically to maximize benefit from treatment intensification while avoiding unnecessary toxicity.