前列腺穿刺活检结果预测模型的建立
wf（2016）
Abstract
目的基于前列腺特异性抗原(PSA)等指标,建立能够预测前列腺穿刺活检结果的数学模型.方法收集2009年7月至2015年3月在解放军总医院进行前列腺穿刺活检患者的年龄、前列腺体积、游离PSA(fPSA)和总PSA(tPSA)等临床资料.所有研究对象中随机选择80％为建模组,其余20％为验证组.在建模组中利用单因素和多因素 Logistic 分析筛选出预测前列腺癌的独立性影响因素,构建回归方程,并以此为基础建立预测前列腺穿刺结果的数学模型.利用受试者工作特征(receiver operating characteristic,ROC)曲线评估该模型对前列腺癌的诊断价值,并与临床常用的 PSA 及其相关参数比较诊断价值的差异.结果选取资料完整且 tPSA 100 ng/ml以下的患者纳入研究,共958例.其中建模组767例(tPSA 4~20 ng/ml者587例),验证组191例.在建模组中,将所有指标纳入单因素和多因素 Logistic 回归分析,发现年龄、tPSA 和前列腺体积是前列腺癌独立的预测因素.将所有指标(包括 fPSA)纳入回归方程,构建数学模型Y＝－4．765＋0.074×(年龄)＋0．057×(tPSA)＋0．052×(fPSA)－0．029×(前列腺体积).在建模组和验证组中, ROC曲线分析显示该模型预测前列腺癌的 ROC 曲线下面积高于 tPSA、f/tPSA 和 PSA 密度.取Y＝－0．076,即约登指数最大值作为本模型最佳临界值,预测前列腺癌的灵敏度为76．2％、特异度为76．6％、阳性预测值76．5％、阴性预测值76．3％.结论本预测模型与单独应用PSA及其相关参数相比具有更高的诊断价值,并且可以在不增加患者检查项目的前提下提高预测前列腺癌的能力.
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Prostate cancer,Prostate specific antigen,Model
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