Tohi Yoichiro, Sahrmann John M, Arbet Jaron, Kato Takuma, Lee Lui Shiong, Peacock Michael, Ginsburg Kevin, Pavlovich Christian, Carroll Peter, Bangma Chris H, Sugimoto Mikio, Boutros Paul C
Department of Urology, Faculty of Medicine, Kagawa University, Kagawa, Japan.
Jonsson Comprehensive Cancer Center, University of California-Los Angeles, Los Angeles, CA, USA; Institute for Precision Health, University of California-Los Angeles, Los Angeles, CA, USA; Department of Human Genetics, University of California-Los Angeles, Los Angeles, CA, USA; Department of Urology, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA.
Eur Urol Oncol. 2025 Apr;8(2):347-354. doi: 10.1016/j.euo.2024.07.006. Epub 2024 Jul 31.
There is no consensus on de-escalation of monitoring during active surveillance (AS) for prostate cancer (PCa). Our objective was to determine clinical criteria that can be used in decisions to reduce the intensity of AS monitoring.
The global prospective AS cohort from the Global Action Plan prostate cancer AS consortium was retrospectively analyzed. The 24656 patients with complete outcome data were considered. The primary goal was to develop a model identifying a subgroup with a high ratio of other-cause mortality (OCM) to PCa-specific mortality (PCSM). Nonparametric competing-risks models were used to estimate cause-specific mortality. We hypothesized that the subgroup with the highest OCM/PCSM ratio would be good candidates for de-escalation of AS monitoring.
Cumulative mortality at 15 yr, accounting for censoring, was 1.3% for PCSM, 11.5% for OCM, and 18.7% for death from unknown causes. We identified body mass index (BMI) >25 kg/m and <11% positive cores at initial biopsy as an optimal set of criteria for discriminating OCM from PCSM. The 15-yr OCM/PCSM ratio was 34.2 times higher for patients meeting these criteria than for those not meeting the criteria. According to these criteria, 37% of the cohort would be eligible for de-escalation of monitoring. Limitations include the retrospective nature of the study and the lack of external validation.
Our study identified BMI >25 kg/m and <11% positive cores at initial biopsy as clinical criteria for de-escalation of AS monitoring in PCa.
We investigated factors that could help in deciding on when to reduce the intensity of monitoring for patients on active surveillance for prostate cancer. We found that patients with higher BMI (body mass index) and lower prostate cancer volume may be good candidates for less intensive monitoring. This model could help doctors and patients in making decisions on active surveillance for prostate cancer.
对于前列腺癌（PCa）主动监测（AS）期间监测方案的降阶梯，目前尚无共识。我们的目的是确定可用于决定降低AS监测强度的临床标准。
对全球行动计划前列腺癌AS联盟的全球前瞻性AS队列进行回顾性分析。纳入了24656例有完整结局数据的患者。主要目标是建立一个模型，识别其他原因死亡率（OCM）与前列腺癌特异性死亡率（PCSM）之比高的亚组。使用非参数竞争风险模型来估计特定原因死亡率。我们假设OCM/PCSM比最高的亚组是AS监测降阶梯的理想候选者。
15年时的累积死亡率，经审查后，PCSM为1.3%，OCM为11.5%，不明原因死亡为18.7%。我们确定初始活检时体重指数（BMI）>25kg/m²且阳性核心<11%是区分OCM与PCSM的最佳标准组合。符合这些标准的患者15年OCM/PCSM比是不符合这些标准患者的34.2倍。根据这些标准，37%的队列符合监测降阶梯条件。局限性包括研究的回顾性性质以及缺乏外部验证。
我们的研究确定初始活检时BMI>25kg/m²且阳性核心<11%是PCa患者AS监测降阶梯的临床标准。
我们研究了有助于决定何时降低前列腺癌主动监测患者监测强度的因素。我们发现BMI较高（体重指数）且前列腺癌体积较小的患者可能是进行强度较低监测的理想候选者。该模型可帮助医生和患者就前列腺癌的主动监测做出决策。
