王 键,任海林

前列腺穿刺活检是前列腺癌诊断的金标准，但过度穿刺与漏诊风险并存，制约了临床诊疗效能。风险因素整合型预测模型通过系统融合临床、影像、实验室等多维度指标，为穿刺决策提供量化依据，成为解决上述困境的关键技术手段。本文综述了该类模型的应用现状，包括传统统计模型、机器学习与AI模型、靶向穿刺专用模型等主要类型及其性能特征；深入分析了当前存在的风险因素整合不全面、模型泛化性不足、可解释性欠缺及临床转化滞后等核心问题；最后从风险因素体系构建、模型技术创新、临床适配性优化及转化机制完善四个维度，提出针对性的优化路径，为推动模型从科研走向临床、提升前列腺癌精准诊断水平提供参考。

前列腺穿刺活检；风险因素整合；预测模型；精准诊断；临床转化

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