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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.

Publication ,  Journal Article
Armstrong, AJ; Liu, VYT; Selvaraju, RR; Chen, E; Simko, JP; DeVries, S; Sartor, O; Sandler, HM; Mohamad, O; Huang, H-C; Griffin, J; Esteva, A ...
Published in: J Clin Oncol
November 10, 2025

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.

Duke Scholars

Published In

J Clin Oncol

DOI

EISSN

1527-7755

Publication Date

November 10, 2025

Volume

43

Issue

32

Start / End Page

3494 / 3504

Location

United States

Related Subject Headings

  • Randomized Controlled Trials as Topic
  • Prostatic Neoplasms
  • Oncology & Carcinogenesis
  • Middle Aged
  • Male
  • Humans
  • Clinical Trials, Phase III as Topic
  • Biomarkers, Tumor
  • Artificial Intelligence
  • Androgen Antagonists
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Armstrong, A. J., Liu, V. Y. T., Selvaraju, R. R., Chen, E., Simko, J. P., DeVries, S., … Nguyen, P. L. (2025). 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. J Clin Oncol, 43(32), 3494–3504. https://doi.org/10.1200/JCO.24.00365
Armstrong, Andrew J., Vinnie Y. T. Liu, Ramprasaath R. Selvaraju, Emmalyn Chen, Jeffry P. Simko, Sandy DeVries, Oliver Sartor, et al. “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.J Clin Oncol 43, no. 32 (November 10, 2025): 3494–3504. https://doi.org/10.1200/JCO.24.00365.
Armstrong AJ, Liu VYT, Selvaraju RR, Chen E, Simko JP, DeVries S, Sartor O, Sandler HM, Mohamad O, Huang H-C, Griffin J, Yamashita R, Esteva A, Tran PT, Spratt DE, Carson JH, Peters C, Gore E, Lee SP, Monson JM, Augspurger ME, El-Gayed A, Rodgers JP, McKay R, Morgan T, Feng FY, Nguyen PL. 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. J Clin Oncol. 2025 Nov 10;43(32):3494–3504.

Published In

J Clin Oncol

DOI

EISSN

1527-7755

Publication Date

November 10, 2025

Volume

43

Issue

32

Start / End Page

3494 / 3504

Location

United States

Related Subject Headings

  • Randomized Controlled Trials as Topic
  • Prostatic Neoplasms
  • Oncology & Carcinogenesis
  • Middle Aged
  • Male
  • Humans
  • Clinical Trials, Phase III as Topic
  • Biomarkers, Tumor
  • Artificial Intelligence
  • Androgen Antagonists