Wang Yu, Shi Yao, Wang Li, Rong Wenli, Du Yunhong, Duan Yuliang, Peng Lili
School of Nursing, Hunan University of Chinese Medicine, Changsha, China.
Anesthesiology Department, The First Affiliated Hospital of Naval Medical University, Shanghai, China.
Quant Imaging Med Surg. 2025 Sep 1;15(9):8648-8662. doi: 10.21037/qims-2024-2843. Epub 2025 Aug 13.
Biochemical recurrence (BCR) after radical prostatectomy (RP) affects the prognosis of patients and early accurate prediction is crucial. Magnetic resonance imaging (MRI) is of great value in the assessment of prostate cancer (PCa). However, there is a lack of a systematic summary of the current research status for the construction of a postoperative BCR prediction model applicable to Chinese PCa patients based on MRI features. This study aimed to systematically evaluate the predictive performance and clinical applicability of the available models.
A standardized search of relevant literature in the PubMed, Cochrane Library, Embase, Web of Science, CINAHL, CNKI, VIP, Wanfang Data, and CBM databases was performed, with the search time restricted to the establishment of the database to 11 September 2024. Studies that developed and/or validated prediction models based on MRI examination to identify and/or predict BCR in patients after RP in China were included. Two researchers independently screened the literature and used the prediction model risk of bias assessment tool to assess the quality of research on the prediction models and performed descriptive analyses of predictor variables for modeling.
A total of 17 studies were included, and 41 prediction models for BCR risk in Chinese patients after RP based on MRI examination were constructed, with the area under the receiver operating characteristic curve (AUC) or concordance index (C-index) of the cases ranging from 0.610 to 0.982. A total of 36 prediction models had good predictive performance, eight studies performed model calibration, two studies performed internal validation, two studies performed external validation, and seven studies conducted both internal and external validation. The results of the quality assessment revealed that all 17 studies were at high risk of bias. The most frequent predictors were prostate-specific antigen (PSA) level, MRI image features, and Gleason score.
At present, a prediction model based on MRI examination for the risk of BCR in Chinese patients after RP is still in the development stage, and the overall quality of research needs to be further improved. In the future, the study design and reporting process should be improved, and the existing model should be validated to provide a basis for the development of effective prevention strategies.
根治性前列腺切除术后生化复发（BCR）影响患者预后，早期准确预测至关重要。磁共振成像（MRI）在前列腺癌（PCa）评估中具有重要价值。然而，目前缺乏基于MRI特征构建适用于中国PCa患者术后BCR预测模型的研究现状的系统总结。本研究旨在系统评估现有模型的预测性能和临床适用性。
在PubMed、Cochrane图书馆、Embase、Web of Science、CINAHL、CNKI、VIP、万方数据和CBM数据库中对相关文献进行标准化检索，检索时间限制为数据库建立至2024年9月11日。纳入在中国基于MRI检查开发和/或验证预测模型以识别和/或预测根治性前列腺切除术后患者BCR的研究。两名研究人员独立筛选文献，并使用预测模型偏倚风险评估工具评估预测模型的研究质量，并对建模的预测变量进行描述性分析。
共纳入17项研究，构建了41个基于MRI检查的中国根治性前列腺切除术后患者BCR风险预测模型，病例的受试者工作特征曲线下面积（AUC）或一致性指数（C-index）范围为0.610至0.982。共有三十六种预测模型具有良好的预测性能，八项研究进行了模型校准，两项研究进行了内部验证，两项研究进行了外部验证，七项研究同时进行了内部和外部验证。质量评估结果显示，所有17项研究均存在高偏倚风险。最常见的预测因素是前列腺特异性抗原（PSA）水平、MRI图像特征和Gleason评分。
目前，基于MRI检查的中国根治性前列腺切除术后患者BCR风险预测模型仍处于开发阶段，研究的整体质量有待进一步提高。未来，应改进研究设计和报告流程，并对现有模型进行验证，为制定有效的预防策略提供依据。
