PI-RADS v2.1联合PSA相关指标预测PSA灰区前列腺癌的价值研究

张苏波; 徐永军; 孙毅; 万金鑫; 赵妍; 刘静芳; 王锐

doi:10.15953/j.1004-4140.2021.30.05.04

PI-RADS v2.1联合PSA相关指标预测PSA灰区前列腺癌的价值研究

江苏大学附属连云港医院(连云港市第二人民医院)影像科, 江苏连云港 222000

基金项目:

江苏大学临床医学科技发展基金（动态增强MRI联合标准化表观扩散系数对预测中高级别前列腺癌的应用价值研究（JLY2021089））。

详细信息

作者简介:
张苏波,男,硕士,江苏省连云港市第二人民医院主治医师,主要从事影像诊断工作,E-mail:zsb3210@126.com;徐永军^*,男,江苏省连云港市第二人民医院影像科副主任医师,主要从事影像诊断工作,E-mail:z15161309079@126.com。

中图分类号: O242;R445.3
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出版历程
- 收稿日期: 2021-01-06
- 网络出版日期: 2021-09-22

Study on the Value of Predicting Prostate Cancer in the Grey Zone of PSA by Use of PI-RADS v2.1 Combined with PSA-related Indicators

Department of Radiology, Lianyungang Hospital Affiliated of Jiangsu University(Lianyungang Second People's Hospital), Lianyungang 222000, China

摘要

摘要: 目的：探讨建立前列腺影像报告及数据系统（PI-RADS v2.1）联合前列腺抗原（PSA）相关衍生物的Logistic模型对PSA灰区（4～10ng/mL）前列腺癌（PCa）的诊断价值。材料与方法：回顾性分析经病理证实的49例前列腺癌（PCa）和118例非癌患者的资料，包括年龄、tPSA、fPSA、PI-RADS v2.1评分、PSAD、fPSA/tPSA。对组间有统计学差异的指标进行Logistic回归分析，确定PCa独立预测指标，并分别联合PI-RADS v2.1评分建立Logistic回归预测模型。通过受试者工作特性曲线（ROC）评价各模型的诊断效能。结果：①年龄、tPSA、fPSA在PCa与非癌组间无统计学差异，fPSA/tPSA、PSAD、PI-RADS v2.1评分有统计学差异。②Logistic回归分析显示PI-RADS v2.1评分、PSAD、fPSA/tPSA为PCa独立预测因子；拟建立预测模型，A模型：Logit（P）=-10.82+2.32×PI-RADS v2.1+11.89×PSAD；B模型：Logit（P）=-6.13+2.19×PI-RADS v2.1-12.02×fPSA/tPSA。ROC曲线下面积分别为0.918和0.893，均高于单独使用PI-RADS v2.1评分，差异具有统计学意义。其中A模型敏感度0.843、特异度0.829，较单独使用PI-RADS v2.1评分（敏感度0.767、特异度0.801）诊断效能最佳。结论：PI-RADS v2.1评分联合PSA相关指标建立的Logistic模型在PSA灰区前列腺癌的诊断效能均优于单独运用PI-RADS v2.1评分，能够避免不必要的穿刺活检，对优化临床治疗策略具有较好的指导作用。
- 前列腺癌 /
- Logistic回归模型 /
- PSA灰区
Abstract: Objective: We intend to investigate the diagnostic value of establishing the Logistic regression model based on Prostate Imaging Report and Data System (PI-RADS v2.1) combined with prostate specific antigen (PSA) which is applied in PSA gray area(4~10ng/mL) prostate cancer. Materials and Methods: We retrospectively analyzed the pathologically-certified clinical data of 49 cases with prostate cancer (PCa) and 118 non-cancer cases who underwent prostate biopsy, the data covered age, tPSA, fPSA, PI-RADS v2.1 evaluation, PSAD and fPSA/tPSA. We performed logistic regression analysis on the indicators with statistical difference between the groups, and obtained ascertained independent PCa predictors, furthermore we respectively established regression prediction model by combination with PI-RADS v2.1 evaluation. The diagnostic efficacy of each model was evaluated by the operating characteristic curve (ROC) of subjects. Results: (1) There was no significant statistical difference in age, tPSA and fPSA between the PCa and non-cancer patients. But evaluation of PI-RADS v2.1, fPSA/tPSA, and PSAD showed significant statistical differences. (2) Logistic regression analysis indicated that PI-RADS v2.1evaluation, PSAD, and fPSA/tPSA are independent predictors of PCa; we established prediction models A and B as follows;Model A: Logit (P)=-10.82+2.32×PI-RADS v2.1+11.89×PSAD; Model B: Logit (P)=-6.13+2.19×PI-RADS v2.1-12.02×fPSA/tPSA. The area under the ROC curve was respectively 0.918 and 0.893, both were higher than the PI-RADS v2.1 evaluation independently applied, and we found that the differences were statistically significant. The sensitivity of model A was 0.843 and the specificity was 0.829, which showed better diagnostic efficacy compared with the sensitivity and specificity we got when the PI-RADS v2.1 evaluation was independently used (sensitivity 0.767 and specificity 0.801).Conclusion: The Logistic model established by combing PI-RADS v2.1 evaluation with PSA-related indicators showed better diagnostic efficacy in PSA grey area prostate cancer than PI-RADS v2.1 applied independently, in this way unnecessary needle biopsy can be avoided, and would play a significant instructive role in optimizing clinical treatment strategies.
- prostate cancer /
- logistic regression model /
- PSA grey zone

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参考文献(16)

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施引文献(6)

期刊类型引用(4)

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2.	殷帅涛，王嘉南，蒋召强，王向阳，姬彤宇，单磊. PI-RADS v2.1评分联合前列腺特异性抗原衍生指标对灰区前列腺癌的诊断价值. 中华实用诊断与治疗杂志. 2023(04): 372-376 . 百度学术
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4.	孙东方，姚伟根，刘洁，鲁鹏聪，康聪. 基于PI-RADS联合PSA及衍生物构建前列腺癌定量评分体系的研究. 现代实用医学. 2022(12): 1564-1566 . 百度学术