一种前列腺癌风险计算器：利用临床和磁共振成像数据预测北美男性的活检结果。
A prostate cancer risk calculator: Use of clinical and magnetic resonance imaging data to predict biopsy outcome in North American men.
作者信息
Kinnaird Adam, Brisbane Wayne, Kwan Lorna, Priester Alan, Chuang Ryan, Barsa Danielle E, Delfin Merdie, Sisk Anthony, Margolis Daniel, Felker Ely, Hu Jim, Marks Leonard S
机构信息
Department of Urology, David Geffen School of Medicine, UCLA, Los Angeles, CA, United States.
Division of Urology, Department of Surgery, University of Alberta, Edmonton, AB, Canada.
出版信息
Can Urol Assoc J. 2022 Mar;16(3):E161-E166. doi: 10.5489/cuaj.7380.
INTRODUCTION
A functional tool to optimize patient selection for magnetic resonance imaging (MRI)-guided prostate biopsy (MRGB) is an unmet clinical need. We sought to develop a prostate cancer risk calculator (PCRC-MRI) that combines MRI and clinical characteristics to aid decision-making for MRGB in North American men.
METHODS
Two prospective registries containing 2354 consecutive men undergoing MRGB (September 2009 to April 2019) were analyzed. Patients were randomized into five groups, with one group randomly assigned to be the validation cohort against the other four groups as the discovery cohort. The primary outcome was detection of clinically significant prostate cancer (csPCa) defined as Gleason grade group ≥2. Variables included age, ethnicity, digital rectal exam (DRE), prior biopsy, prostate-specific antigen (PSA), prostate volume, PSA density, and MRI score. Odds ratios (OR) were calculated from multivariate logistic regression comparing two models: one with clinical variables only (clinical) against a second combining clinical variables with MRI data (clinical+MRI).
RESULTS
csPCa was present in 942 (40%) of the 2354 men available for study. The positive and negative predictive values for csPCa in the clinical+MRI model were 57% and 89%, respectively. The area under the curve of the clinical+MRI model was superior to the clinical model in discovery (0.843 vs. 0.707, p<0.0001) and validation (0.888 vs. 0.757, p<0.0001) cohorts. Use of PCRC-MRI would have avoided approximately 16 unnecessary biopsies in every 100 men. Of all variables examined, Asian ethnicity was the most protective factor (OR 0.46, 0.29-0.75) while MRI score 5 indicated greatest risk (OR15.8, 10.5-23.9).
CONCLUSIONS
A risk calculator (PCRC-MRI), based on a large North American cohort, is shown to improve patient selection for MRGB, especially in preventing unnecessary biopsies. This tool is available at https://www.uclahealth.org/urology/prostate-cancer-riskcalculator and may help rationalize biopsy decision-making.
引言
优化磁共振成像（MRI）引导下前列腺穿刺活检（MRGB）患者选择的实用工具是一项尚未满足的临床需求。我们试图开发一种前列腺癌风险计算器（PCRC-MRI），它结合了MRI和临床特征，以辅助北美男性进行MRGB的决策。
方法
分析了两个前瞻性登记库，其中包含2354名连续接受MRGB的男性（2009年9月至2019年4月）。患者被随机分为五组，其中一组被随机指定为验证队列，其他四组作为发现队列。主要结局是检测到临床显著前列腺癌（csPCa），定义为Gleason分级组≥2。变量包括年龄、种族、直肠指检（DRE）、既往活检、前列腺特异性抗原（PSA）、前列腺体积、PSA密度和MRI评分。通过多因素逻辑回归比较两个模型计算比值比（OR）：一个仅包含临床变量（临床模型），另一个将临床变量与MRI数据相结合（临床+MRI模型）。
结果
在可供研究的2354名男性中，942名（40%）存在csPCa。临床+MRI模型中csPCa的阳性和阴性预测值分别为57%和89%。临床+MRI模型的曲线下面积在发现队列（0.843对0.707，p<0.0001）和验证队列（0.888对0.757，p<0.0001）中均优于临床模型。使用PCRC-MRI每100名男性中可避免约16次不必要的活检。在所有检查的变量中，亚洲种族是最具保护作用的因素（OR 0.46，0.29-0.75），而MRI评分为5表明风险最高（OR15.8，10.5-23.9）。
结论
基于北美大型队列的风险计算器（PCRC-MRI）被证明可改善MRGB的患者选择，尤其是在预防不必要的活检方面。该工具可在https://www.uclahealth.org/urology/prostate-cancer-riskcalculator获取，可能有助于使活检决策合理化。
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