浙江医学2026，Vol.48Issue(5)：464-470,7.DOI:10.12056/j.issn.1006-2785.2026.48.5.2025-477
双参数MRI联合临床指标构建预测模型对PSA 4～10 ng/mL临床显著性前列腺癌的诊断价值研究
Diagnostic value of nomogram model constructed by biparametric MRI combined with clinical indicators for clinically significant prostate cancer in patients with PSA 4-10 ng/mL
摘要
Abstract
Objective To investigate the diagnostic value of a prediction model based on biparametric magnetic resonance imaging(bpMRI)according to Prostate Imaging Report and Data System version 2.1(PI-RADS v2.1)combined with clinical indicators for clinically significant prostate cancer(csPCa)in patients with prostate specific antigen(PSA)4-10 ng/mL.Methods Clinical data of 266 patients who underwent bpMRI and prostate biopsy at Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University from June 2017 to August 2024 were retrospectively analyzed.The patients were randomly divided into a training cohort(n=186)and a validation cohort(n=80)at a ratio of 7∶3.Independent risk factors were screened by univariate and multivariate logistic regression analyses,and a prediction model was established and presented as a nomogram.The diagnostic performance of the model was evaluated using ROC curve,calibration curve and decision curve analysis.Results Univariate analysis showed that there were statistically significant differences between the csPCa group and non-csPCa group in age,free/total PSA ratio(f/tPSA),prostate volume(PV),PSA density(PSAD),age-to-volume ratio(AVR),PSA-age volume(PSA-AV)and bpMRI(all P＜0.001).Multivariate logistic regression analysis revealed that age,PSA-AV and bpMRI were independent risk factors for csPCa in patients with PSA 4-10 ng/mL.The prediction model based on the above three factors showed favorable predictive efficacy in both the training and validation cohorts,with AUC of 0.92 and 0.81,respectively,which was significantly higher than that of bpMRI(AUC:0.87 and 0.75,respectively),PSA-AV(AUC:0.71 and 0.68,respectively)and age(AUC:0.65 and 0.64,respectively).The calibration curve showed high consistency between the predicted probability and the actual probability.Decision curve analysis indicated that the model achieved a high net clinical benefit within the threshold range of 0-0.75.Conclusion The prediction model constructed by bpMRI combined with clinical indicators has high predictive value for csPCa in patients with PSA 4-10 ng/mL,which is helpful for clinicians to select the optimal management strategy.关键词
前列腺癌/前列腺特异性抗原/前列腺影像报告和数据评分系统/双参数磁共振成像Key words
Prostate cancer/Prostate specific antigen/Prostate Imaging Report and Data System/Biparametric magnetic resonance imaging引用本文复制引用
徐辉景,颜丹,张永胜,李志平,杨丽勤,洪璐威,崔凤..双参数MRI联合临床指标构建预测模型对PSA 4～10 ng/mL临床显著性前列腺癌的诊断价值研究[J].浙江医学,2026,48(5):464-470,7.基金项目
浙江省医药卫生科技计划项目(2024KY1386、2025KY1217、2025KY1160、2025KY1161) （2024KY1386、2025KY1217、2025KY1160、2025KY1161）
浙江省中医药科技计划项目(2024ZL668) （2024ZL668）
杭州市卫生科技计划项目(A20230086) （A20230086）
萧山区科技计划引导项目(2022338) （2022338）
