Multimodal Artificial Intelligence Prediction of Abiraterone Efficacy in Two STAMPEDE Phase 3 Trials of Non-Metastatic Very High-Risk Prostate Cancer
Menée sur 1 137 patients atteints d'un cancer de la prostate non métastatique à haut risque de récidive et inclus dans des essais de phase III évaluant l'abiratérone, cette étude évalue la performance d'un modèle d'intelligence artificielle, utilisant des images numériques de lames histologiques, le niveau sérique du PSA, le stade tumoral et l'âge, pour prédire l'efficacité du traitement
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 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 amongst non-metastatic 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 platform protocol (NCT00268476) using digital pathology images, prostate specific antigen (PSA), 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 randomized 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 (HR 0.47; 95% CI 0.31-0.70), with 5-year MFS increasing from 62% (95% CI 53-70%) in LT-ADT to 81% (95% CI 74-87%) 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 78-85%) versus 84% (95% CI 80-87%, interaction p-value=0.02). This differential effect was consistent in local node-negative and node-positive subgroups.
Conclusions : 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, non-metastatic prostate cancer. This biomarker could be implemented clinically to maximize benefit from treatment intensification whilst avoiding unnecessary toxicity.
Annals of Oncology , article en libre accès, 2026