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.

IF 42.1 1区 医学 Q1 ONCOLOGY
Andrew J Armstrong, Vinnie Y T Liu, Ramprasaath R Selvaraju, Emmalyn Chen, Jeffry P Simko, Sandy DeVries, Oliver Sartor, Howard M Sandler, Osama Mohamad, Huei-Chung Huang, Jacqueline Griffin, Rikiya Yamashita, Andre Esteva, Phuoc T Tran, Daniel E Spratt, John Hi Carson, Christopher Peters, Elizabeth Gore, Steve P Lee, Jedidiah M Monson, Mark E Augspurger, Ali El-Gayed, Joseph P Rodgers, Rana McKay, Todd Morgan, Felix Y Feng, Paul L Nguyen
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引用次数: 0

Abstract

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.

开发和验证一种人工智能数字病理生物标志物,用于预测高风险前列腺癌患者长期激素治疗和放疗的益处。
目的:长期雄激素剥夺治疗(ADT)可提高接受放疗(RT)的高危局限性前列腺癌(PCa)患者的生存率。需要预测性生物标志物来指导ADT持续时间。方法:使用预处理数字前列腺活检图像和来自六项NRG肿瘤学III期随机放疗试验的临床数据(年龄、前列腺特异性抗原、Gleason和T分期),对一种多模式人工智能(MMAI)衍生的预测性生物标志物进行长期(LT)与短期(ST) ADT的训练。开发了一种新的mmai衍生生物标志物,用于预测LT-ADT对主要终点远处转移(DM)的差异益处。第七项随机试验RTOG 9202 (N = 1192)验证了MMAI的预测效用,该试验将男性随机分配到RT + ST-ADT组(4个月)和RT + LT-ADT组(28个月)。进行了DM的细灰色和累积发生率分析,其次是DM的死亡。无糖尿病的死亡被视为竞争风险。结果:在验证队列中(中位随访17.2年),LT-ADT将DM从26%显著改善至17%(亚分布风险比[sHR], 0.64 [95% CI, 0.50 ~ 0.82], P < .001)。在DM中观察到显著的生物标志物-治疗预测相互作用(P = 0.04), MMAI生物标志物阳性的男性(n = 785, 66%)与ST-ADT相比,LT-ADT减少了DM (sHR, 0.55 [95% CI, 0.41至0.73],P < 0.001),而MMAI生物标志物阴性的男性没有观察到治疗益处(n = 407;sHR, 1.06 [95% CI, 0.61 ~ 1.84], P = 0.84)。在MMAI生物标志物阳性的男性中,RT + LT-ADT和RT + ST-ADT的15年糖尿病风险差异估计为14%,在MMAI生物标志物阴性的男性中为0%。与治疗无关,MMAI生物标志物也能预测糖尿病的预后(sHR, 2.35 [95% CI, 1.72至3.19],P < 0.001)。结论:据我们所知,MMAI模型是第一个经过验证的预测生物标志物,用于指导局部/局部晚期PCa的ADT持续时间。大约三分之一的高危前列腺癌患者可以安全地避免额外的24个月的ADT和相关的发病率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Clinical Oncology
Journal of Clinical Oncology 医学-肿瘤学
CiteScore
41.20
自引率
2.20%
发文量
8215
审稿时长
2 months
期刊介绍: The Journal of Clinical Oncology serves its readers as the single most credible, authoritative resource for disseminating significant clinical oncology research. In print and in electronic format, JCO strives to publish the highest quality articles dedicated to clinical research. Original Reports remain the focus of JCO, but this scientific communication is enhanced by appropriately selected Editorials, Commentaries, Reviews, and other work that relate to the care of patients with cancer.
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