摘要
目的:建立预测前列腺癌术后切缘阳性结果的列线图模型,并进行相应的验证,为预测术后切缘阳性的风险提供依据。方法:纳入PC-follow数据库中北京医院、北京大学第一医院、北京大学第三医院、海军军医大学第一附属医院、西安交通大学第一附属医院2015—2018年收治的2215例前列腺癌患者的病例资料,年龄67.3(33~88)岁。PSA(45.2±18.9)ng/ml。前列腺穿刺活检针数6~32针,穿刺阳性针数百分比4%~100%,穿刺活检病理Gleason评分6~10分。采用单纯随机抽样法将患者分为建模组和验证组。建模组1770例,年龄65.5(33~88)岁,PSA(48.2±12.4)(0.01~99.4)ng/ml。验证组445例,年龄68.6(47~82)岁,PSA(43.7±14.8)(0.01~87.2)ng/ml。对两组患者年龄(<60岁,60~70岁,>70岁)、PSA(<4 ng/ml,4~10 ng/ml,11~20 ng/ml,>20 ng/ml)、盆腔MRI检查结果(阴性,可疑,阳性)、肿瘤临床分期(T 1~T 2期,≥T 3期)、穿刺阳性针数百分比(≤33%,34%~66%,>66%)、穿刺活检病理Gleason评分(≤6分,7分,≥8分)进行单因素和多因素logistic分析,筛选有意义的指标构建预测前列腺癌术后切缘阳性结果的列线图模型。在验证组对该模型进行验证,并与构成列线图的单一因素的预测效果进行比较。结果:单因素分析结果显示,术前PSA水平、盆腔MRI检查结果、穿刺针数阳性率、穿刺病理Gleason评分与术后切缘阳性率有相关性(P<0.05)。多因素分析结果显示,术前PSA水平(OR=2.046,95%CI 1.022~4.251,P=0.009)、穿刺阳性针数百分比(OR=1.502,95%CI 1.136~1.978,P=0.002)、穿刺病理Gleason评分(OR=1.568,95%CI 1.063~2.313,P=0.028)、盆腔MRI检查结果(OR=1.525,95%CI 1.160~2.005,P=0.033)为前列腺癌术后切缘阳性的独立预测指标,根据上述指标建立列线图模型。列线图模型预测验证组切缘阳性的受试者工作特征曲线(ROC)的曲线下面积为0.776,而以术前PSA水平、穿刺阳性针数百分比、穿刺病理Gleason评分、盆腔MRI检查结果、术后病理Gleason评分等单一因素预测验证组切缘阳性的ROC曲线下面积分别为0.554、0.615、0.556、0.522和0.560,列线图模型与单一指标比较差异均有统计学意义(P<0.05)。结论:构建的列线图模型较单独应用术前PSA水平、穿刺阳性针数百分比、穿刺病理Gleason评分、盆腔MRI检查结果、术后病理Gleason评分在预测前列腺癌术后切缘阳性方面具有更高的诊断价值。
Objective To establish a nomogram model for predicting positive resection margins after prostate cancer surgery,and to perform the corresponding verification,in order to predict the risk of positive resection margins after surgery.Methods A total of 2215 prostate cancer patients from The First Affiliated Hospital of Naval Medical University,Hospital,Peking University First Hospital,Peking University Third Hospital,Peking University,and First Affiliated Hospital of Xi′an Jiaotong University were included in the PC-follow database from 2015 to 2018,and a simple random sampling method was used.They were divided into 1770 patients in the modeling group and 445 patients in the verification group.In the modeling group,the age(<60 years,60 to 70 years,>70 years),PSA(<4 ng/ml,4-10 ng/ml,11-20 ng/ml,>20 ng/ml),pelvic MRI(negative,suspicious,positive),clinical stage of the tumor(T1-T2,≥T3),percentage of positive needles(≤33%,34%-66%,>66%),Gleason score of biopsy pathology(≤6 points,7 points,≥8 points).Univariate and multivariate logistic analysis were performed to screen meaningful indicators to construct a nomogram model.The model was used for validation in the validation group.Results The results of multivariate analysis showed that preoperative PSA level(OR=2.046,95%CI 1.022 to 4.251,P=0.009),percentage of puncture positive needles(OR=1.502,95%CI 1.136 to 1.978,P=0.002),Gleason score of puncture pathology(OR=1.568,95%CI 1.063 to 2.313,P=0.028),pelvic MRI were correlated(OR=1.525,95%CI 1.160 to 2.005,P=0.033).Establish a nomogram model for independent predictors of positive margin of prostate cancer.The area under the receiver operating characteristic(ROC)curve of the validation group is 0.776.The area under the ROC curve of the preoperative PSA level,percentage of puncture positive needles,puncture pathology Gleason score,pelvic MRI,postoperative pathology Gleason score were 0.554,0.615,0.556,0.522,and 0.560,respectively.The difference between the nomogram model and other indicators was statistically significant(P<0.05).Conclusions The constructed nomogram model has higher diagnostic value than the preoperative PSA level,percentage of puncture positive needles,Gleason score of puncturing pathology,pelvic MRI,and postoperative pathological Gleason score in predicting positive margin.
作者
程万里
逄城
宋新达
付春龙
侯惠民
周利群
马潞林
高旭
贺大林
王建业
刘明
Cheng Wanli;Pang Cheng;Song Xinda;Fu Chunlong;Hou Huimin;Zhou Liqun;Ma Lulin;Gao Xu;He Dalin;Wang Jianye;Liu Ming(Department of Urology,Beijing Hospital,National Geriatric Center,Institute of Geriatrics of Chinese Academy of Medical Sciences,Beijing 100730,China;Department of Urology,Peking University First Hospital,Beijing 100340,China;Department of Urology,Peking University Third Hospital,Beijing 100161,China;Department of Urology,the First Affiliated Hospital,Xi’an Medical University,Xi’an 710061,China;Urology Department of the First Affiliated Hospital,Xi’an Medical University,Xi’an 710061,China)
出处
《中华泌尿外科杂志》
CAS
CSCD
北大核心
2020年第3期205-209,共5页
Chinese Journal of Urology
基金
国家重点研发计划专项(2017YFC0840102)
重大协同创新项目-重大前沿研究(2018-12M-1-002)
首都临床特色应用研究(BJ-2017-055)
121工程项目(BJ-2018-090)
北京医院博士启动基金(BJ-2018-029)。
关键词
前列腺肿瘤
前列腺癌
手术切缘阳性
统计学模型
Prostatic neoplasms
Prostate cancer
Positive surgical margin
Models statistical
