Department of Urology, Ospedale Sant'Andrea-Università di Roma "Sapienza", Rome, Italy.
Department of Urology, Ospedale Sant'Andrea-Università di Roma "Sapienza", Rome, Italy.
Eur J Surg Oncol. 2021 Oct;47(10):2640-2645. doi: 10.1016/j.ejso.2021.04.033. Epub 2021 Apr 30.
The Rotterdam Prostate Cancer Risk calculator (RPCRC) has been validated in the past years. Recently a new version including multiparametric magnetic resonance imaging (mpMRI) data has been released. The aim of our study was to analyze the performance of the mpMRI RPCRC app.
A series of men undergoing prostate biopsies were enrolled in eleven Italian centers. Indications for prostate biopsy included: abnormal Prostate specific antigen levels (PSA>4 ng/ml), abnormal DRE and abnormal mpMRI. Patients' characteristics were recorded. Prostate cancer (PCa) risk and high-grade PCa risk were assessed using the RPCRC app. The performance of the mpMRI RPCRC in the prediction of cancer and high-grade PCa was evaluated using receiver operator characteristics, calibration plots and decision curve analysis.
Overall, 580 patients were enrolled: 404/580 (70%) presented PCa and out of them 224/404 (55%) presented high-grade PCa. In the prediction of cancer, the RC presented good discrimination (AUC = 0.74), poor calibration (p = 0.01) and a clinical net benefit in the range of probabilities between 50 and 90% for the prediction of PCa (Fig. 1). In the prediction of high-grade PCa, the RC presented good discrimination (AUC = 0.79), good calibration (p = 0.48) and a clinical net benefit in the range of probabilities between 20 and 80% (Fig. 1).
The Rotterdam prostate cancer risk App accurately predicts the risk of PCa and particularly high-grade cancer. The clinical net benefit is wide for high-grade cancer and therefore its implementation in clinical practice should be encouraged. Further studies should assess its definitive role in clinical practice.
过去几年里，鹿特丹前列腺癌风险计算器（RPCRC）已经过验证。最近，一个包含多参数磁共振成像（mpMRI）数据的新版本已经发布。本研究旨在分析 mpMRI RPCRC 应用程序的性能。
在 11 个意大利中心招募了一系列接受前列腺活检的男性患者。前列腺活检的指征包括：前列腺特异性抗原（PSA）水平异常（PSA>4ng/ml）、直肠指检异常和 mpMRI 异常。记录患者的特征。使用 RPCRC 应用程序评估前列腺癌（PCa）风险和高级别 PCa 风险。使用接收器操作特征、校准图和决策曲线分析评估 mpMRI RPCRC 在预测癌症和高级别 PCa 中的性能。
总体而言，共招募了 580 名患者：404/580（70%）患有 PCa，其中 224/404（55%）患有高级别 PCa。在预测癌症方面，RC 表现出良好的区分度（AUC=0.74）、较差的校准（p=0.01），并且在预测 PCa 的概率范围为 50%至 90%时具有临床净收益（图 1）。在预测高级别 PCa 方面，RC 表现出良好的区分度（AUC=0.79）、良好的校准（p=0.48），并且在预测高级别癌症的概率范围为 20%至 80%时具有临床净收益（图 1）。
鹿特丹前列腺癌风险应用程序能够准确预测 PCa 的风险，特别是高级别癌症的风险。对于高级别癌症，其临床净收益范围广泛，因此应鼓励在临床实践中实施。进一步的研究应评估其在临床实践中的明确作用。
