Department of Urology, Barrualde-Galdakao Integrated Health Organisation, Osakidetza Basque Health Service, Calle Itsasondo 10, 3B 48993, Getxo Bizkaia, Spain.
Biocruces Bizkaia Health Research Institute, Barakaldo, Spain.
World J Urol. 2024 Mar 13;42(1):141. doi: 10.1007/s00345-024-04833-5.
External validation of existing risk calculators (RC) to assess the individualized risk of detecting prostate cancer (PCa) in prostate biopsies is needed to determine their clinical usefulness. The objective was to externally validate the Rotterdam Prostate Cancer RCs 3 and 4 (RPCRC-3/4) and that incorporating PHI (RPCRC-PHI) in a contemporary Spanish cohort.
Multicenter prospective study that included patients suspicious of harboring PCa. Men who attended the urology consultation were tested for PHI before prostate biopsy. To evaluate the performance of the prediction models: discrimination (receiver operating characteristic (ROC) curves), calibration and net benefit [decision curve analysis (DCA)] were calculated. These analyses were carried out for detection of any PCa and clinically significant (cs)PCa, defined as ISUP grade ≥ 2.
Among the 559 men included, 337 (60.28%) and 194 (34.7%) were diagnosed of PCa and csPCa, respectively. RPCRC-PHI had the best discrimination ability for detection of PCa and csPCa with AUCs of 0.85 (95%CI 0.82-0.88) and 0.82 (95%CI 0.78-0.85), respectively. Calibration plots showed that RPCRC-3/4 underestimates the risk of detecting PCa showing the need for recalibration. In DCA, RPCRC-PHI shows the highest net benefit compared to biopsy all men.
The RPCRC-PHI performed properly in a contemporary clinical setting, especially for prediction of csPCa.
需要对现有的风险计算器(RC)进行外部验证,以评估前列腺活检中检测前列腺癌(PCa)的个体化风险,从而确定其临床应用价值。本研究的目的是在一个当代西班牙队列中对包含 PHI 的鹿特丹前列腺癌 RC 3 型和 4 型(RPCRC-3/4)和 RC 进行外部验证。
这是一项多中心前瞻性研究,纳入了疑似患有 PCa 的患者。在进行前列腺活检之前,在泌尿科就诊的男性接受 PHI 检测。为了评估预测模型的性能:采用区分度(接收者操作特征(ROC)曲线)、校准度和净获益[决策曲线分析(DCA)]进行评估。对所有 PCa 和临床显著(cs)PCa(定义为 ISUP 分级≥2)的检测进行了这些分析。
在 559 名纳入的男性中,337 名(60.28%)和 194 名(34.7%)分别被诊断为 PCa 和 csPCa。RPCRC-PHI 对检测 PCa 和 csPCa 的区分能力最佳,AUC 分别为 0.85(95%CI 0.82-0.88)和 0.82(95%CI 0.78-0.85)。校准图显示,RPCRC-3/4 低估了检测 PCa 的风险,需要重新校准。在 DCA 中,与对所有男性进行活检相比,RPCRC-PHI 显示出更高的净获益。
RPCRC-PHI 在当代临床环境中表现良好,尤其是在预测 csPCa 方面。