Digital Pathology–Based Multimodal Artificial Intelligence Scores and Outcomes in a Randomized Phase III Trial in Men With Nonmetastatic Castration-Resistant Prostate Cancer

组织病理学 危险系数 比例危险模型 医学 前列腺癌 内科学 肿瘤科 泌尿科 临床试验 置信区间 癌症 病理
作者
Felix Y. Feng,Matthew R. Smith,Fred Saad,Pooya Mobadersany,Shaozhou K. Tian,Stephen Yip,Joel Greshock,Najat Khan,Margaret K. Yu,Sharon McCarthy,Sabine Brookman‐May,Ariel B. Bourla,Tamara R. Todorović,Rikiya Yamashita,Huei–Chung Huang,Trevor J. Royce,Timothy N. Showalter,Jacqueline Griffin,Akinori Mitani,Andre Esteva
出处
期刊:JCO precision oncology [Lippincott Williams & Wilkins]
卷期号:9 (9): e2400653-e2400653 被引量:6
标识
DOI:10.1200/po-24-00653
摘要

PURPOSE The SPARTAN trial demonstrated that the addition of apalutamide to androgen deprivation therapy improves outcomes among patients with nonmetastatic castration-resistant prostate cancer (nmCRPC). We applied a previously reported digital histopathology–based multimodal artificial intelligence (MMAI) algorithm to estimate clinical outcomes in SPARTAN. METHODS Patients with available hematoxylin and eosin-stained slides from the primary tumor were included. Histopathology slides were digitized. MMAI scores ranging from 0 to 1 were generated from digital histopathology and baseline clinical parameters. Patients were categorized into MMAI non–high-risk and high-risk groups using previously validated cutoffs. Kaplan-Meier estimates were calculated for metastasis-free survival (MFS), second progression-free survival (PFS2), and overall survival (OS); comparisons were performed using Cox proportional hazards regression for treatment arms and MMAI risk. The interaction between treatment arm and risk group was evaluated using a Cox proportional hazards model. RESULTS The study included 420 evaluable patients after excluding those with missing clinical data or inadequate histopathology images. Of these, 63% (n = 266) were MMAI high risk and 37% (n = 154) were non–high risk. MMAI risk score was associated with shorter MFS (hazard ratio [HR], 1.72; P < .005), PFS2 (HR, 1.57; P < .005), and OS (HR, 1.41; P = .02). MMAI high-risk patients receiving apalutamide demonstrated significant improvement in MFS (HR, 0.19; P < .005), PFS2 (HR, 0.47; P < .005), and OS (HR, 0.6; P = .01). The interaction between MMAI risk score and treatment for MFS ( P = .01) and PFS2 ( P = .03) was significant, indicating greater benefit from apalutamide treatment in MMAI high-risk patients. CONCLUSION MMAI is a prognostic marker in nmCRPC and may serve as a predictive biomarker with high-risk patients deriving the greatest benefit from treatment with apalutamide. These results represent the first extension of an MMAI classifier to patients with castration-resistant prostate cancer, warranting additional validation.
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