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首页> 外文期刊>The Journal of Urology >Development and Internal Validation of a Prostate Health Index Based Nomogram for Predicting Prostate Cancer at Extended Biopsy
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Development and Internal Validation of a Prostate Health Index Based Nomogram for Predicting Prostate Cancer at Extended Biopsy

机译:基于前列腺健康指数的线型图在长期活检中预测前列腺癌的发展和内部验证

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Purpose: We developed and validated a Prostate Health Index (Beckman Coulter, Brea, California) based nomogram to predict prostate cancer at extended prostate biopsy. Materials and Methods: The study population consisted of 729 patients who were scheduled for prostate biopsy following suspicious digital rectal examination and/or increased prostate specific antigen. Total and free prostate specific antigen, percent free-to-total prostate specific antigen, [-2]proPSA and the prostate health index [([-2] proPSA/free prostate specific antigen) X Vtotal prostate specific antigen)] were determined. Logistic regression models were fitted to test prostate cancer predictors. Predictive accuracy estimates of biopsy outcome predictions were quantified. Regression coefficients were used to create a decision making tool to predict prostate cancer. A calibration plot was used to evaluate the extent of overestimating or underestimating the observed prostate cancer rate. Decision curve analysis provided an estimate of the net benefit obtained using the prostate health index based nomogram. Results: Overall 280 of 729 patients (38.4%) were diagnosed with prostate cancer at extended prostate biopsy. On accuracy analyses prostate health index emerged as the most informative predictor of prostate cancer (AUC 0.70) compared to established predictors, such as total prostate specific antigen (0.51) and percent free-to-total prostate specific antigen (0.62). Including the prostate health index in a multivariable logistic regression model based on patient age, prostate volume, digital rectal examination and biopsy history significantly increased predictive accuracy by 7% from 0.73 to 0.80 (p <0.001). Nomogram calibration was good. Decision curve analysis showed that using the prostate health index based nomogram resulted in the highest net benefit. Conclusions: The prostate health index based nomogram can assist clinicians in the decision to perform biopsy by providing an accurate estimation of an individual risk of prostate cancer.
机译:目的:我们开发并验证了基于前列腺健康指数(贝克曼库尔特,加利福尼亚州布雷亚)的列线图,以预测长期前列腺活检时的前列腺癌。材料和方法:研究人群包括729名可疑的直肠指检和/或增加的前列腺特异性抗原后计划进行前列腺穿刺活检的患者。测定总和游离前列腺特异性抗原,总游离前列腺特异性抗原的百分比,[-2] proPSA和前列腺健康指数[([[-2] proPSA /游离前列腺特异性抗原)X总前列腺特异性抗原)]。逻辑回归模型适合测试前列腺癌的预测因子。对活检结果预测的预测准确性评估进行了量化。回归系数用于创建预测前列腺癌的决策工具。使用校准图来评估高估或低估观察到的前列腺癌发生率的程度。决策曲线分析提供了使用基于前列腺健康指数的列线图所获得的净收益的估计。结果:729名患者中有280名(38.4%)在长期前列腺活检中被诊断出患有前列腺癌。在准确性分析中,与已建立的预测指标(例如总前列腺特异性抗原(0.51)和总游离前列腺特异性抗原的百分比(0.62))相比,前列腺健康指数成为前列腺癌信息最丰富的预测指标(AUC 0.70)。在基于患者年龄,前列腺体积,直肠指检和活检史的多变量logistic回归模型中包括前列腺健康指数,可将预测准确度从0.73提高到0.80,提高了7%(p <0.001)。线照相法校准很好。决策曲线分析表明,使用基于前列腺健康指数的列线图可获得最高的净收益。结论:基于前列腺健康指数的列线图可以通过提供对前列腺癌个人风险的准确估计来帮助临床医生进行活检。

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