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建立基于传统诊断方法的临床意义的前列腺癌风险预测模型

Wen-Tong Ji¹, Yong-Kun Wang², Zhan-Yang Han³

¹Urology 2nd Department, China-Japan Union Hospital of Jilin University, Changchun, Jilin, China.

Frontiers in oncology

|January 6, 2025

概括

一个新的模型使用PSA,DRE和TRUS预测临床显著的前列腺癌 (csPCa). 这种具有成本效益的工具可以提高cspca在活检前的检测准确性,特别是在服务不足的地区.

科学领域:

泌尿器科泌尿器科泌尿器科泌尿器科
在瘤学瘤学.
医学诊断医学诊断医学诊断

背景情况:

前列腺癌的诊断依赖于多种方法,包括PSA,DRE和TRUS.
在活检之前准确预测临床显著的前列腺癌 (csPCa) 对于有效的患者管理至关重要.
需要具有成本效益和可访问的诊断工具,特别是在亚洲和欠发达地区.

研究的目的:

开发和验证使用传统诊断参数对csPCa的预测模型.
评估模型的性能和临床实用性,用于预测csPCa.
为了创建一个非侵入性,成本效益高的工具,用于csPCa检测.

主要方法:

对1196名亚洲患者进行了经直肠超声导向活检 (TRUSB) 的回顾性分析.
基于后勤回归的csPCa风险预测模型的开发,使用培训 (n=837) 和验证 (n=359) 集.
使用校准曲线,ROC曲线,DCA和CIC进行性能评估.

主要成果:

血清PSA,年龄,DRE,前列腺形状,边缘和低声区与病理结果有关.
该模型在训练组中以良好的校准和临床实用性实现了0.890的AUC.
预测模型显示的NPV (89.8%) 和PPV (68.0%) 比MRI高,在线计算器开发用于活检优化.

结论:

使用PSA,DRE和TRUS建立了一个具有成本效益和准确的csPCa预测模型.
开发的模型为csPCa检测提供了一个非侵入性和高效的工具.
这个模型有可能改善亚洲和其他资源有限的环境中的前列腺癌诊断.

关键词:

临床上显著的前列腺癌.诊断诊断诊断诊断诊断诊断这个名字是名ogramogram.前列腺活检活检前列腺活检风险预测模型的风险预测模型

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