Prostate Cancer Gene 3 (PCA3): Development and Internal Validation of a Novel Biopsy Nomogram
Prostate Cancer Gene 3 (PCA3): Development and Internal Validation of a Novel Biopsy Nomogram
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DOI：
10.1016/j.eururo.2009.03.029
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发表时间：
2009-10-01
期刊：
影响因子：
23.4
通讯作者：
Haese, Alexander
中科院分区：
文献类型：
--
作者：
Chun, Felix K.;de la Taille, Alexandre;Haese, Alexander
背景：尿前列腺癌基因3 （PCA3）是一种很有前途的前列腺癌检测新标志物。目的：探讨尿PCA3检测是否能改善前列腺癌（PCa）的风险评估，并在多机构前列腺活检数据队列中构建决策辅助工具。设计、设置和参与者：PCA3检测截止阈值分析之后采用逻辑回归模型，该模型使用已建立的预测因子来评估809名有PCa风险的男性活检时的PCa风险。测量方法：采用回归系数构建四组模态图。在有和没有PCA3的模型中，使用接受者操作者特征分析曲线下面积来量化活检结果预测的预测准确性（PA）估计。Bootstrap样本用于内部验证并减少过拟合偏差。使用非参数损失校准图以图形方式探讨活检时观察到的PCa率的高估或低估程度。PA的差异采用Mantel-Haenszel检验。最后，通过线图衍生的概率截断值进行测试，以评估识别有或没有前列腺癌患者的能力。结果和局限性：PCA3被确定为活检时PCa的统计学独立危险因素。添加PCA3检测后，基础模型的自举校正多变量PA在2%至5%之间。PA的最高增量来自PCA3测定的截止阈值17，其中PA增加5%（从0.68到0.73,p = 0.04）。Nomogram probability-derived risk cut-off分析进一步证实了PCA3 Nomogram优于base model。结论：PCA3符合一种新的标志物的标准，能够增加多变量活检模型的PA。这种新颖的基于pca3的nomogram前列腺癌图能够更好地识别有前列腺癌风险的男性，并有助于决定是否需要进一步的评估。(C) 2009年欧洲泌尿外科协会。Elsevier B.V.版权所有。
Background: Urinary prostate cancer gene 3 (PCA3) represents a promising novel marker of prostate cancer detection.Objective: To test whether urinary PCA3 assay improves prostate cancer (PCa) risk assessment and to construct a decision-making aid in a multi-institutional cohort with pre-prostate biopsy data.Design, setting, and participants: PCA3 assay cut-off threshold analyses were followed by logistic regression models which used established predictors to assess PCa-risk at biopsy in a large multi-institutional data set of 809 men at risk of harboring PCa.Measurements: Regression coefficients were used to construct four sets of nomograms. Predictive accuracy (PA) estimates of biopsy outcome predictions were quantified using the area under the curve of the receiver operator characteristic analysis in models with and without PCA3. Bootstrap resamples were used for internal validation and to reduce overfit bias. The extent of overestimation or underestimation of the observed PCa rate at biopsy was explored graphically using nonparametric loss-calibration plots. Differences in PA were tested using the Mantel-Haenszel test. Finally, nomogram-derived probability cut-offs were tested to assess the ability to identify patients with or without PCa.Results and limitations: PCA3 was identified as a statistically independent risk factor of PCa at biopsy. Addition of a PCA3 assay improved bootstrap-corrected multivariate PA of the base model between 2% and 5%. The highest increment in PA resulted from a PCA3 assay cut-off threshold of 17, where a 5% gain in PA (from 0.68 to 0.73, p = 0.04) was recorded. Nomogram probability-derived risk cut-off analyses further corroborate the superiority of the PCA3 nomogram over the base model.Conclusions: PCA3 fulfills the criteria for a novel marker capable of increasing PA of multivariate biopsy models. This novel PCA3-based nomogram better identifies men at risk of harboring PCa and assists in deciding whether further evaluation is necessary. (C) 2009 European Association of Urology. Published by Elsevier B.V. All rights reserved.