Citations 1
Development and Validation of an Artificial Intelligence Digital Pathology Biomarker to Predict Benefit of Long-Term Hormonal Therapy and Radiotherapy in Men With High-Risk Prostate Cancer Across Multiple Phase III Trials
Armstrong, Andrew J. , Liu, Vinnie Y.T. , Selvaraju, Ramprasaath R., Chen, Emmalyn , Simko, Jeffry, DeVries, Sandy, Sartor, Oliver , Sandler, Howard M. , Mohamad, Osama , Huang, Huei–Chung, Griffin, Jacqueline , Esteva, Andre , Carson, John H., Peters, Christopher A., Gore, Elizabeth , Monson, Jedidiah M., Augspurger, Mark E., El‐Gayed, Ali , Rodgers, Joseph P., McKay, Rana R. , Morgan, Todd M. , Feng, Felix Y. , Nguyen, Paul L. , Tran, Phuoc T , Spratt, Daniel E , Lee, Steve P , El-Gayed, Ali , McKay, Rana R , Morgan, Todd M , Feng, Felix Y , Sartor, A Oliver , Sandler, Howard M , Armstrong, Andrew J , Yamashita, Rikiya , Spratt, Daniel E. , Carson, John Hi
Journal of Clinical Oncology | April 16, 2025 | Volume: 43 | Issue: 32 | Pages: 3494-3504
PURPOSE Long-term androgen deprivation therapy (ADT) improves survival in men with high-risk localized prostate cancer (PCa) receiving radiotherapy (RT). Predictive biomarkers are needed to guide ADT duration. METHODS A multimodal artificial intelligence (MMAI)–derived predictive biomarker was trained for long-term (LT) versus short-term (ST) ADT using pretreatment digital prostate biopsy images and clinical data (age, prostate-specific antigen, Gleason, and T stage) from six NRG Oncology phase III randomized radiotherapy trials. The novel MMAI-derived biomarker was developed to predict the differential benefit of LT-ADT on the primary end point, distant metastasis (DM). MMAI predictive utility was validated on a seventh randomized trial, RTOG 9202 (N = 1,192), which randomly assigned men to RT + ST-ADT (4 months) versus RT + LT-ADT (28 months). Fine-Gray and cumulative incidence analyses for DM, and secondarily, death with DM, were performed. Deaths without DM were treated as competing risks. RESULTS In the validation cohort (median follow-up, 17.2 years), LT-ADT significantly improved DM from 26% to 17% (subdistribution hazard ratio [sHR], 0.64 [95% CI, 0.50 to 0.82], P < .001). A significant biomarker-treatment predictive interaction was observed ( P = .04) for DM, whereby MMAI biomarker–positive men (n = 785, 66%) had reduced DM with LT-ADT versus ST-ADT (sHR, 0.55 [95% CI, 0.41 to 0.73], P < .001), whereas no treatment benefit was observed for MMAI biomarker–negative men (n = 407; sHR, 1.06 [95% CI, 0.61 to 1.84], P = .84). The estimated 15-year DM risk difference between RT + LT-ADT and RT + ST-ADT was 14% in MMAI biomarker–positive men and 0% in MMAI biomarker–negative men. The MMAI biomarker was also prognostic for DM, irrespective of treatment (sHR, 2.35 [95% CI, 1.72 to 3.19], P < .001). CONCLUSION To our knowledge, the MMAI model is the first validated predictive biomarker to guide ADT duration with RT in localized/locally advanced PCa. Approximately one third of men with high-risk PCa could safely be spared the additional 24 months of ADT and the associated morbidity.