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用于预测新诊断前列腺癌并开始积极监测的男性疾病进展的分层癌症监测(STRATCANS)多变量模型的开发与外部验证

Development and External Validation of the STRATified CANcer Surveillance (STRATCANS) Multivariable Model for Predicting Progression in Men with Newly Diagnosed Prostate Cancer Starting Active Surveillance.

作者信息

Light Alexander, Lophatananon Artitaya, Keates Alexandra, Thankappannair Vineetha, Barrett Tristan, Dominguez-Escrig Jose, Rubio-Briones Jose, Benheddi Toufik, Olivier Jonathan, Villers Arnauld, Babureddy Kirthana, Abdelmoteleb Haitham, Gnanapragasam Vincent J

机构信息

Division of Urology, Department of Surgery, University of Cambridge, Cambridge CB2 0QQ, UK.

Department of Urology, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, UK.

出版信息

J Clin Med. 2022 Dec 27;12(1):216. doi: 10.3390/jcm12010216.

Abstract

For men with newly diagnosed prostate cancer, we aimed to develop and validate a model to predict the risk of progression on active surveillance (AS), which could inform more personalised AS strategies. In total, 883 men from 3 European centres were used for model development and internal validation, and 151 men from a fourth European centre were used for external validation. Men with Cambridge Prognostic Group (CPG) 1-2 disease at diagnosis were eligible. The endpoint was progression to the composite endpoint of CPG3 disease or worse (≥CPG3). Model performance at 4 years was evaluated through discrimination (C-index), calibration plots, and decision curve analysis. The final multivariable model incorporated prostate-specific antigen (PSA), Grade Group, magnetic resonance imaging (MRI) score (Prostate Imaging Reporting & Data System (PI-RADS) or Likert), and prostate volume. Calibration and discrimination were good in both internal validation (C-index 0.742, 95% CI 0.694-0.793) and external validation (C-index 0.845, 95% CI 0.712-0.958). In decision curve analysis, the model offered net benefit compared to a 'follow-all' strategy at risk thresholds of ≥0.08 and ≥0.04 in development and external validation, respectively. In conclusion, our model demonstrated good accuracy and clinical utility in predicting the progression on AS at 4 years post-diagnosis. Men with lower risk predictions could subsequently be offered less-intense surveillance. Further external validation in larger cohorts is now required.

摘要

对于新诊断出前列腺癌的男性患者,我们旨在开发并验证一种模型,以预测积极监测(AS)过程中的疾病进展风险,从而为更具个性化的AS策略提供依据。总共883名来自3个欧洲中心的男性用于模型开发和内部验证,151名来自第四个欧洲中心的男性用于外部验证。诊断时处于剑桥预后组(CPG)1-2期疾病的男性符合条件。终点是进展为CPG3期疾病或更严重情况(≥CPG3)的复合终点。通过区分度(C指数)、校准图和决策曲线分析评估4年时的模型性能。最终的多变量模型纳入了前列腺特异性抗原(PSA)、分级组、磁共振成像(MRI)评分(前列腺影像报告和数据系统(PI-RADS)或李克特量表)以及前列腺体积。内部验证(C指数0.742,95%置信区间0.694-0.793)和外部验证(C指数0.845,95%置信区间0.712-0.958)中的校准和区分度均良好。在决策曲线分析中,与“全部随访”策略相比,该模型在开发和外部验证中的风险阈值分别≥0.08和≥0.04时提供了净效益。总之,我们的模型在预测诊断后4年AS过程中的进展方面显示出良好的准确性和临床实用性。风险预测较低的男性患者随后可接受强度较低的监测。现在需要在更大的队列中进行进一步的外部验证。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/56df/9821695/c770c9695bf0/jcm-12-00216-g001.jpg

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