Effective prognostication improves selection of patients with prostate cancer for treatment combinations. We aimed to evaluate whether a previously developed multimodal artificial intelligence (MMAI) algorithm was prognostic in very advanced prostate cancer using data from four phase 3 trials of the STAMPEDE platform protocol.
We included patients starting androgen-deprivation therapy in the docetaxel, docetaxel plus zoledronic acid, abiraterone, or abiraterone plus enzalutamide trials. Patients were recruited at 112 sites. We combined all standard-of-care control patients (including those allocated to standard of care [SOC-ADT] consisting of testosterone suppression with luteinising hormone-releasing hormone agonists or antagonists, and radiotherapy when indicated), and we combined the rest of the patients into docetaxel-treated or abiraterone-treated groups. Patients had either metastatic disease or were at very high-risk of metastatic disease, determined by node-positivity or, if node-negative, by T stage, serum prostate-specific antigen (PSA) level, and Gleason score. We used the locked ArteraAI Prostate MMAI algorithm that combined these clinical variables, age, and digitised prostate biopsy pathology images. We performed Fine-Gray and Cox regression adjusted for treatment allocation and cumulative incidence analyses at 5 years to evaluate associations with prostate cancer-specific mortality (PCSM) for continuous (per SD increase) and categorical (quartile-Q) scores. The STAMPEDE platform protocol is registered with ClinicalTrials.gov, NCT00268476.
Of 5213 eligible patients recruited from Oct 5, 2005, to March 31, 2016, 3167 were included in this analysis (1575 [49·7%] with non-metastatic disease, 1592 [50·3%] with metastatic disease; median follow-up 6·9 years [IQR 5·9-8·0]) with all datapoints available for score generation. The MMAI algorithm (per SD increase) was strongly associated with PCSM (hazard ratio [HR] 1·40, 95% CI 1·30-1·51, p<0·0001). On ad-hoc inspection, the highest scoring quartile of patients in each disease and treatment allocation group (MMAI Q4; vs the bottom three quartiles, Q1-3) had the highest PCSM risk in both patients with non-metastatic disease (HR 2·12, 1·61-2·81, p<0·0001) and those with metastatic disease (HR 1·62, 1·39-1·88, p<0·0001). MMAI quartile stratification split patients categorised by disease burden into groups with notably different risks of 5-year PCSM: patients with non-metastatic disease that were node-negative could be further stratified by MMAI score quartile Q1-3 (3%, 2-4) versus Q4 (11%, 7-15), those with non-metastatic disease that were node-positive could be stratified by Q1-3 (11%, 8-14) versus Q4 (20%, 13-26), those with metastatic disease with low-volume could be stratified by Q1-3 (27%, 23-31) versus Q4 (43%, 36-51), and those with metastatic disease with high-volume could be stratified by Q1-3 (48%, 44-52) versus Q4 (68%, 62-75).
Diagnostic prostate biopsy samples contain prognostic information in patients with, or at high-risk of, radiologically overt metastatic prostate cancer. MMAI algorithm combined with disease burden improves prognostication of advanced prostate cancer.
Prostate Cancer UK, UK Medical Research Council, Cancer Research UK, John Black Charitable Foundation, Prostate Cancer Foundation, Sanofi Aventis, Janssen, Astellas, Novartis, Artera.
The Lancet. Digital health. 2025 Jun 03 [Epub ahead of print]
Charles T A Parker, Larissa Mendes, Vinnie Y T Liu, Emily Grist, Songwan Joun, Rikiya Yamashita, Akinori Mitani, Emmalyn Chen, Marina A Parry, Ashwin Sachdeva, Laura Murphy, Huei-Chung Huang, Jacqueline Griffin, Douwe van der Wal, Tamara Todorovic, Sharanpreet Lall, Sara Santos Vidal, Miriam Goncalves, Suparna Thakali, Anna Wingate, Leila Zakka, Mick Brown, Daniel Wetterskog, Claire L Amos, Nafisah B Atako, Robert J Jones, William R Cross, Silke Gillessen, Chris C Parker, STAMPEDE collaborators , Daniel M Berney, Phuoc T Tran, Daniel E Spratt, Matthew R Sydes, Mahesh K B Parmar, Noel W Clarke, Louise C Brown, Felix Y Feng, Andre Esteva, Nicholas D James, Gerhardt Attard
Cancer Institute, University College London, London, UK., Artera Inc, Los Altos, CA, USA., Departments of Surgery and Urology, The Christie and Salford Royal Hospitals; Manchester, UK; Genitourinary Cancer Research Group, Division of Cancer Sciences, Manchester Cancer Research Centre, The University of Manchester, Manchester, UK., MRC Clinical Trials Unit at University College London, Institute of Clinical Trials and Methodology, University College London, London, UK., University of Glasgow, Beatson West of Scotland Cancer Centre, Glasgow, UK., St James's University Hospital, Leeds, UK., Istituto Oncologico della Svizzera Italiana, Ente Ospedaliero Cantonale, Bellinzona, Switzerland; Università della Svizzera Italiana, Lugano, Switzerland., Royal Marsden NHS Foundation Trust and Institute of Cancer Research, London, UK., Barts Cancer Institute, Queen Mary University of London, London, UK., University of Maryland, Baltimore, MD, USA., UH Seidman Cancer Center, Case Western Reserve University, Cleveland, OH, USA., University of California San Francisco, San Francisco, CA, USA., Cancer Institute, University College London, London, UK. Electronic address: .