Zhang Yu, Zeng Na, Zhang Feng Bo, Rui Huang Yang Xin, Tian Ye
Department of Urology, Beijing Friendship Hospital, Capital Medical University, Beijing, People's Republic of China.
National Clinical Research Center for Digestive Diseases, Beijing Friendship Hospital, Capital Medical University, Beijing, People's Republic of China.
Clin Genitourin Cancer. 2020 Oct;18(5):367-377. doi: 10.1016/j.clgc.2019.11.011. Epub 2019 Dec 5.
The primary objective of the present study was to avoid unnecessary prostate biopsy in biopsy-naive patients with Prostate Imaging Reporting and Data System, version 2 (PI-RADS v2), score 3, lesions.
We reviewed our prospectively maintained database from January 2012 to July 2018. Logistic regression analyses were performed to test different clinical factors as predictors of clinically significant prostate cancer (CSPCa) and build nomograms. Calibration curves were used to assess the concordance between the predictive value and the true risk. Decision curves were created to measure the overall net benefit.
The prostate cancer (PCa) and CSPCa detection rates were 37.2% (81 of 218) and 23.9% (52 of 218) in the PI-RADS v2, score 3, cohort. More PCa cases (61.7%; 50 of 81) and CSPCa cases (75%; 39 of 52) were found in the peripheral zone than in the transitional zone. Multivariate analysis showed that age, prostate-specific antigen density, lesion region, and apparent diffusion coefficient (ADC) were predictive factors for CSPCa and PCa. Internally validated calibration curves showed that the predicted risk of CSPCa was closer to the actual probability when the threshold was > 60%. Decision curves showed that a better net benefit was achieved when the model was used to guide clinical practice.
More cases of PCa and CSPCa were seen in the peripheral zone than in the transitional zone among patients with PI-RADS v2, score 3. The positive predictive value for a positive ADC (< 900 μm/s) for the detection of CSPCa and PCa improved with an increasing prostate-specific antigen density. Biopsy can be avoided if the equivocal lesion has a negative ADC (> 900 μm/s) and was in the transition zone.
本研究的主要目的是避免对前列腺影像报告和数据系统第2版(PI-RADS v2)评分为3分的初诊患者进行不必要的前列腺活检。
我们回顾了2012年1月至2018年7月前瞻性维护的数据库。进行逻辑回归分析以测试不同临床因素作为临床显著前列腺癌(CSPCa)的预测指标,并构建列线图。校准曲线用于评估预测值与真实风险之间的一致性。创建决策曲线以衡量总体净效益。
在PI-RADS v2评分为3分的队列中,前列腺癌(PCa)和CSPCa的检出率分别为37.2%(218例中的81例)和23.9%(218例中的52例)。在外周区发现的PCa病例(61.7%;81例中的50例)和CSPCa病例(75%;52例中的39例)比移行区更多。多变量分析表明,年龄、前列腺特异性抗原密度、病变区域和表观扩散系数(ADC)是CSPCa和PCa的预测因素。内部验证的校准曲线表明,当阈值>60%时,CSPCa的预测风险更接近实际概率。决策曲线表明,使用该模型指导临床实践时可获得更好的净效益。
在PI-RADS v2评分为3分的患者中,外周区的PCa和CSPCa病例比移行区更多。随着前列腺特异性抗原密度的增加,ADC阳性(<900μm/s)对CSPCa和PCa检测的阳性预测值提高。如果可疑病变的ADC为阴性(>900μm/s)且位于移行区,则可避免活检。