Department of Urology, Singapore General Hospital, Singapore.
Department of Urology, Singapore General Hospital, Singapore.
Urol Oncol. 2021 Nov;39(11):783.e1-783.e10. doi: 10.1016/j.urolonc.2021.03.003. Epub 2021 Mar 26.
Several multiparametric magnetic resonance imaging (mpMRI)-based models have been developed with significant improvements in diagnostic accuracy for clinically significant prostate cancer (csCaP), but lack proper external validation. We therefore sought to externally validate and compare all published mpMRI-based csCaP risk prediction models in an independent Asian population.
A total of 449 men undergoing combined transperineal fusion-targeted/systematic prostate biopsy at our specialist center between 2015 to 2019 were retrospectively analyzed. csCaP was defined as lesions with ISUP (International Society of Urological Pathology) grade group ≥2. The performance of 6 mpMRI-based risk models (MRI-ERSPC-3/4, Distler, Radtke, Mehralivand, van Leeuwen and He) were evaluated in terms of discrimination, calibration and clinical utility, using area under the receiver operating characteristic curve (AUC), calibration curves and decision curve analyses.
A total of 202 (45%) subjects were diagnosed with csCaP. All models demonstrated excellent accuracy with AUCs ranging from 0.75 to 0.86, and most significantly outperformed mpMRI PIRADSv2.0 (Prostate Imaging Reporting and Data System version 2.0) alone. The models by Mehralivand and He showed good calibration to our validation population, with respective intercepts of -0.08 and -0.84. All models were nevertheless recalibrated to the csCaP prevalence in our population for analysis. Decision curve analysis showed that above a threshold probability of 10%, all mpMRI-based models demonstrated superior net benefit compared to mpMRI PIRADSv2.0 or a biopsy-all-men strategy. The van Leeuwen model had the greatest net benefit, avoiding 39% of unnecessary biopsies while missing only 4% of csCaP, at a threshold probability of 15%.
The mpMRI-based risk models demonstrate excellent discrimination and clinical utility and are easy to apply in practice, suggesting that individualized risk-based approaches can be considered over mpMRI alone to avoid unnecessary biopsies.
已经开发了几种基于多参数磁共振成像(mpMRI)的模型,这些模型在临床上显著提高了对有意义的前列腺癌(csCaP)的诊断准确性,但缺乏适当的外部验证。因此,我们旨在对所有已发表的基于 mpMRI 的 csCaP 风险预测模型在独立的亚洲人群中进行外部验证和比较。
回顾性分析了 2015 年至 2019 年期间在我们的专科中心接受经会阴融合靶向/系统前列腺活检的 449 名男性患者。csCaP 定义为具有国际泌尿病理学会(ISUP)分级组≥2 的病变。使用接收者操作特征曲线(AUC)下面积、校准曲线和决策曲线分析评估 6 种基于 mpMRI 的风险模型(MRI-ERSPC-3/4、Distler、Radtke、Mehralivand、van Leeuwen 和 He)在鉴别、校准和临床实用性方面的表现。
共有 202 名(45%)患者被诊断为 csCaP。所有模型的准确性都很高,AUC 范围为 0.75 至 0.86,并且明显优于单独的 mpMRI PIRADSv2.0(前列腺成像报告和数据系统版本 2.0)。Mehralivand 和 He 的模型在我们的验证人群中具有良好的校准,各自的截距为-0.08 和-0.84。然而,所有模型都根据我们人群中的 csCaP 患病率进行了重新校准以进行分析。决策曲线分析显示,在阈值概率高于 10%时,与 mpMRI PIRADSv2.0 或全男性活检策略相比,所有基于 mpMRI 的模型均具有更高的净收益。van Leeuwen 模型具有最大的净收益,在阈值概率为 15%时,避免了 39%的不必要活检,而仅遗漏了 4%的 csCaP。
基于 mpMRI 的风险模型具有出色的鉴别能力和临床实用性,易于在实践中应用,这表明可以考虑基于个体风险的方法,而不是仅基于 mpMRI,以避免不必要的活检。