Su Rui, Xu Guang, Xiang Lihua, Ding Shisi, Wu Rong
Department of Medical Ultrasound, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China; Department of Urology, Ningbo First Hospital, the Affiliated Hospital of Ningbo University, Ningbo, China.
Department of Medical Ultrasound, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China; Ultrasound Research and Education Institute, Tongji University School of Medicine, Shanghai, China.
Urology. 2018 Nov;121:112-117. doi: 10.1016/j.urology.2018.08.026. Epub 2018 Aug 30.
To develop a novel scoring system for the prediction of prostate cancer (PCa).
We assessed 127 patients who underwent a prostate biopsy. Prior to biopsy, we performed shear wave elastography (SWE), transrectal ultrasound, digital rectal exam, total prostatic specific antigen, PSA density (PSAD), and free PSA/total PSA ratio (F/T). We developed an 11-point scoring system based on SWE and these clinical parameters.
PCa was diagnosed in 51 (40.2%) of 127 patients and 192 (25.2%) of 762 sextants on initial biopsy. ROC curve analyses showed that the cutoff value (COV) for SWE was 40.8 kpa at the sextant level. The AUC of score system based on the SWE and clinical parameters (0.911) was significantly different from scoring systems based on SWE alone (0.842) or clinical parameters alone (0.868). For this 11-point scoring system, the optimal COV, Youden index, sensitivity, specificity, PPV, NPV, and AUC were 3 points, 0.66, 76.5% 89.5%, 82.98%, 85.00%, and 0.911, respectively. There were 68 negative biopsy results in patients with 0-3 points, and the detection rate of PCa was 100% in patients with scores exceeding 6 points.
This 11-point scoring system based on SWE and clinical parameters has the good diagnostic performance for predicting PCa. It may be useful in selecting patients for biopsy, substantially reducing the number of unnecessary biopsies while ensuring that few cancers are missed.
开发一种用于预测前列腺癌（PCa）的新型评分系统。
我们评估了127例行前列腺活检的患者。在活检前，我们进行了剪切波弹性成像（SWE）、经直肠超声、直肠指检、总前列腺特异性抗原、PSA密度（PSAD）以及游离PSA/总PSA比值（F/T）检测。我们基于SWE和这些临床参数开发了一个11分的评分系统。
127例患者中有51例（40.2%）在初次活检时被诊断为PCa，762个前列腺穿刺位点中有192个（25.2%）检测出PCa。ROC曲线分析显示，在穿刺位点水平，SWE的临界值（COV）为40.8 kpa。基于SWE和临床参数的评分系统的曲线下面积（AUC）为0.911，与仅基于SWE的评分系统（0.842）或仅基于临床参数的评分系统（0.868）有显著差异。对于这个11分的评分系统，最佳COV、约登指数、敏感性、特异性、阳性预测值、阴性预测值和AUC分别为3分、0.66、76.5%、89.5%、82.98%、85.00%和0.911。评分0 - 3分的患者中有68例活检结果为阴性，评分超过6分的患者PCa检出率为100%。
这种基于SWE和临床参数的11分评分系统在预测PCa方面具有良好的诊断性能。它可能有助于选择活检患者，在确保极少漏诊癌症的同时，大幅减少不必要活检的数量。
