前列腺癌根治术后病理升级的预测模型

Prediction model of pathological escalation after radical prostatectomy

目的通过列线图的形式构建预测模型以评估前列腺癌根治术后病理较术前穿刺病理升级的风险。方法收集了2015年1月至2020年6月期间接受前列腺癌根治性切除术患者共158例的临床资料,建模集研究对象年龄跨度46岁~81岁,通过列线图的形式构建预测模型。结果我们构建的预测模型包含了前列腺特异性抗原密度(prostatespecific antigen density,PSAD)、第2版前列腺影像报告和数据系统评分(Prostate Imaging-Reporting and Data System score version 2.0,PI-RADS评分V2.0)、前列腺穿刺阳性针数占比、身体质量指数(Body Mass Index,BMI)、穿刺病理ISUP分组(International Society of Urological Pathology,ISUP)共五个变量,该模型外部验证的C指数为0.818、Calibration曲线的P值为0.562,决策曲线也显示该模型评估效果良好。结论本研究构建的预测模型有助于在前列腺癌根治术后病理升级方面进行个体化预测。

Objective To construct a predictive model in the form of a nomogram to assess the risk of pathologic progression after radical prostatectomy compared with biopsy pathology.Methods Clinical data of 158 patients who underwent radical prostatic cancer resection from January 2015 to June 2020 were collected.Age of the study subjects in the modeling set ranged from 46 to 81 years old.The prediction model was constructed in the form of nomogram.Results The constructed predictive model consisted of five parameters:prostate-specific antigen density(PSAD),prostate imaging-reporting and data system score Version 2.0(PI-RADS score V2.0),proportion of positive needles in prostate puncture,body mass index(BMI),international society of urological pathology(ISUP)grouping of biopsy pathology,The C index of external validation of this model was 0.818,and the P-value of the Calibration curve was 0.562.The decision curve also showed that the evaluation effect of this model was good.Conclusion The prediction model constructed in this study is helpful for individualized prediction of pathological progression after radical prostatectomy.