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采用前列腺影像报告和数据系统第 2 版(PI-RADS v2)检测前列腺癌可以避免不必要的活检和侵袭性治疗。

Using the prostate imaging reporting and data system version 2 (PI-RIDS v2) to detect prostate cancer can prevent unnecessary biopsies and invasive treatment.

机构信息

Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.

Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.

出版信息

Asian J Androl. 2018 Sep-Oct;20(5):459-464. doi: 10.4103/aja.aja_19_18.

Abstract

Prostate cancer (PCa) is one of the most common cancers among men globally. The authors aimed to evaluate the ability of the Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) to classify men with PCa, clinically significant PCa (CSPCa), or no PCa, especially among those with serum total prostate-specific antigen (tPSA) levels in the "gray zone" (4-10 ng ml). A total of 308 patients (355 lesions) were enrolled in this study. Diagnostic efficiency was determined. Univariate and multivariate analyses, receiver operating characteristic curve analysis, and decision curve analysis were performed to determine and compare the predictors of PCa and CSPCa. The results suggested that PI-RADS v2, tPSA, and prostate-specific antigen density (PSAD) were independent predictors of PCa and CSPCa. A PI-RADS v2 score ≥4 provided high negative predictive values (91.39% for PCa and 95.69% for CSPCa). A model of PI-RADS combined with PSA and PSAD helped to define a high-risk group (PI-RADS score = 5 and PSAD ≥0.15 ng ml cm, with tPSA in the gray zone, or PI-RADS score ≥4 with high tPSA level) with a detection rate of 96.1% for PCa and 93.0% for CSPCa while a low-risk group with a detection rate of 6.1% for PCa and 2.2% for CSPCa. It was concluded that the PI-RADS v2 could be used as a reliable and independent predictor of PCa and CSPCa. The combination of PI-RADS v2 score with PSA and PSAD could be helpful in the prediction and diagnosis of PCa and CSPCa and, thus, may help in preventing unnecessary invasive procedures.

摘要

前列腺癌(PCa)是全球男性最常见的癌症之一。作者旨在评估前列腺影像报告和数据系统第 2 版(PI-RADS v2)在分类患有 PCa、临床显著 PCa(CSPCa)或无 PCa 的男性中的能力,尤其是在血清总前列腺特异性抗原(tPSA)水平处于“灰色地带”(4-10ng/ml)的男性中。本研究共纳入 308 例患者(355 个病灶)。确定了诊断效率。进行了单变量和多变量分析、受试者工作特征曲线分析和决策曲线分析,以确定和比较 PCa 和 CSPCa 的预测因素。结果表明,PI-RADS v2、tPSA 和前列腺特异性抗原密度(PSAD)是 PCa 和 CSPCa 的独立预测因素。PI-RADS v2 评分≥4 具有较高的阴性预测值(PCa 为 91.39%,CSPCa 为 95.69%)。PI-RADS 与 PSA 和 PSAD 相结合的模型有助于确定高危组(PI-RADS 评分=5 和 PSAD≥0.15ng/ml/cm,tPSA 在灰色地带,或 PI-RADS 评分≥4 伴高 tPSA 水平),其 PCa 和 CSPCa 的检出率分别为 96.1%和 93.0%,而低危组的 PCa 和 CSPCa 的检出率分别为 6.1%和 2.2%。结论:PI-RADS v2 可作为 PCa 和 CSPCa 的可靠且独立的预测因素。PI-RADS v2 评分与 PSA 和 PSAD 的结合可能有助于 PCa 和 CSPCa 的预测和诊断,从而可能有助于避免不必要的侵入性操作。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f4e/6116681/41004ba28876/AJA-20-459-g003.jpg

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