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结合PI-RADS v2建立预测前列腺穿刺结果的评分系统

  

  1. 南方医科大学南方医院  泌尿外科,广东 广州 510515
  • 出版日期:2017-10-05 发布日期:2017-10-10
  • 通讯作者: 通信作者:谭万龙,Email: twl@smu.edu.cn

Establishing a point-scoring system to predict prostate biopsy outcome with PI-RADS v2

  1. Department of Urology,  Nanfang Hospital,  Southern Medical University,  Guangzhou 510515,  China
  • Online:2017-10-05 Published:2017-10-10
  • Contact: Corresponding auther: Tan Wanlong,Email: twl@smu.edu.cn

摘要: 目的  结合PIRADS v2分析影响前列腺穿刺前列腺癌阳性率的影响因素,制定评分系统预测穿刺阳性,减少不必要的穿刺。方法  回顾性分析2013年8月至2017年6月南方医院泌尿外科行经直肠超声引导前列腺穿刺活检的病例资料共392例,267例纳入建模组,125例纳入验证组,分析多个因素对前列腺癌穿刺阳性率的预测作用,并根据Logistic回归分析结果制定评分系统。利用验证组患者资料对评分系统进行验证。结果  Logistic回归分析结果显示年龄、前列腺特异抗原密度(PSAD)、体重指数(BMI)、PIRADS v2评分、前列腺体积是影响前列腺癌检出的因素。根据回归系数设定分值。理论分值为-2~9.5分。根据评分系统计算每例患者得分,然后在建模组及验证组绘制评分系统的ROC曲线,曲线下面积分别为0.923(P<0.01),0.895(P<0.01)。评分≤3分前列腺癌可能性极小,而评分>3分前列腺癌可能性大。结论  结合PIRADS v2建立的该评分系统用于评价前列腺癌风险效能优秀,对于≤3分的患者,前列腺癌风险较小,不建议穿刺;>3分的患者必须行前列腺穿刺。合理利用PIRADS v2对建立评分系统有明显帮助。

关键词: 前列腺肿瘤, 穿刺术, 磁共振成像, PIRADS, 评分系统

Abstract: Objective   To explore risk factors of prostate biopsy  and to establish scoring a system to predict prostate biopsy outcome and reduce unnecessary prostate biopsy through PIRADS v2.Methods  A total of 392 patients who had accepted prostate biopsy were enrolled from August 2013 to June 2017 in Nanfang Hospital retrospectively, 267 patients in modeling group and 125 patients in authentication group.  Risk factors were analyzed in diagnosis performance for prostate cancer. According to the results of Logistic regression analysis, a scoring system was developed to predict prostate cancer. The scoring system was validated using patient data from the validation group.Results  According to Logistic analysis, age, prostate specific antigen density(PSAD), BMI,  PIRADS, prostate volume were affecting factors for prostate cancer  detection. Value of scoring system was set in accordance with regression coefficient. It ranked from -2 to 9.5 scores. Calculating overall score was used to draw receiver operating characteristic curve of modeling group and authentication group. The areas under the ROC curve were 0.923 and 0.895. Patients acquired a score ≤3 scores with low risk of prostate cancer. The patients who gained more than 3 scores met a high risk of prostate cancer. Conclusion  The scoring system combined  with   PIRADS v2  has outstanding diagnosis performance for the risks in prostate cancer. The patients with scores lower than 3 do not recommend  prostate biopsy as minimal risk of prostate cancer. In view of high risk of cancer, patients obtained 3 scores need prostate biopsy. The rational use of PIRADS v2 can help set up scoring systems.

Key words: prostatic neoplasms;punctures;magnetic resonance imaging;PI-RADS, scoring system