为了比较目前可用的磁共振成像（MRI）结果整合在内的活体组织检查决策支持工具在预测临床意义显著的前列腺癌（csPCa）方面的表现。我们回顾性纳入了在两个欧洲大型中心进行前列腺MRI检查和随后的定向和/或系统性前列腺活检的男性。可用的决策支持工具通过PubMed搜索确定。在风险阈值为5-20％时，使用校准、区分度、决策曲线分析（DCA）和避免活检数量与错过csPCa病例数量来评估表现，包括校准前后。共纳入了940名男性，其中507人（54％）患有csPCa。年龄、PSA值和PSAD的中位数和四分位数分别为68岁（63-72岁）、9ng/ml（7-15ng/ml）、0.20ng/ml2（0.13-0.32ng/ml2）。评估了18种多变量风险计算器（MRI-RCs）和基于MRI结果和特异性抗原密度阈值（PSAD）的二分类活检决策策略。Van Leeuwen模型和鹿特丹前列腺癌风险计算器（RPCRC）在整个队列中能够评估的MRI-RCs中具有最好的区分能力（AUC为0.86）。DCA显示Van Leeuwen模型具有最高的临床效用，其次是RPCRC。在10％的阈值下，Van Leeuwen模型可以避免22％的活检，并错过1.8％的csPCa，而RPCRC可以避免20％的活检，错过2.6％的csPCa。这些多变量模型胜过仅基于MRI结果和PSAD的二分类决策策略。即使在这个高风险队列中，活检决策支持工具也可以避免许多前列腺活检，同时错过非常少的csPCa病例。Van Leeuwen模型具有最高的临床效用，其次是RPCRC。这些多变量MRI-RCs在表现上优于仅基于MRI和PSAD的决策策略。本文受版权保护。保留所有权利。

To compare the performance of currently available biopsy decision support tools incorporating magnetic resonance imaging (MRI) findings in predicting clinically significant prostate cancer (csPCa).We retrospectively included men who underwent prostate MRI and subsequent targeted and/or systematic prostate biopsies in two large European centres. Available decision support tools were identified by a PubMed search. Performance was assessed by calibration, discrimination, decision curve analysis (DCA) and numbers of biopsies avoided vs. csPCa cases missed, before and after recalibration, at risk thresholds 5-20%.940 men were included, 507 (54%) had csPCa. Median and interquartile ranges of age, PSA, and PSAD were 68 (63-72) years, 9 (7-15) ng/ml, and 0.20 (0.13-0.32) ng/ml2 , respectively. 18 multivariable risk calculators (MRI-RCs) and dichotomous biopsy decision strategies based on MRI findings and prostate-specific antigen density thresholds (PSAD) were assessed. The Van Leeuwen model and the Rotterdam Prostate Cancer Risk Calculator (RPCRC) had the best discriminative ability (AUC 0.86) of MRI-RCs that could be assessed in the whole cohort. DCA showed the highest clinical utility for the Van Leeuwen model, followed by the RPCRC. At the 10% threshold the Van Leeuwen model would avoid 22% of biopsies, missing 1.8% of csPCa, while the RPCRC would avoid 20% of biopsies, missing 2.6% of csPCa. These multivariable models outperformed all dichotomous decision strategies based only on MRI-findings and PSAD.Even in this high-risk cohort, biopsy decision support tools would avoid many prostate biopsies, while missing very few csPCa cases. The Van Leeuwen model had the highest clinical utility, followed by the RPCRC. These multivariable MRI-RCs outperformed and should be favoured over decision strategies based only on MRI and PSAD.This article is protected by copyright. All rights reserved.