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优化前列腺癌抗原3(PCA3)在初次前列腺活检中诊断前列腺癌的临床应用价值。

Optimizing the clinical utility of PCA3 to diagnose prostate cancer in initial prostate biopsy.

作者信息

Rubio-Briones Jose, Borque Angel, Esteban Luis M, Casanova Juan, Fernandez-Serra Antonio, Rubio Luis, Casanova-Salas Irene, Sanz Gerardo, Domínguez-Escrig Jose, Collado Argimiro, Gómez-Ferrer Alvaro, Iborra Inmaculada, Ramírez-Backhaus Miguel, Martínez Francisco, Calatrava Ana, Lopez-Guerrero Jose A

机构信息

Department of Urology, Instituto Valenciano de Oncología, C/ Prof. Beltrán Báguena 8, 46009, Valencia, Spain.

Department of Urology, Hospital Universitario Miguel Servet, Zaragoza, Spain.

出版信息

BMC Cancer. 2015 Sep 11;15:633. doi: 10.1186/s12885-015-1623-0.

Abstract

BACKGROUND

PCA3 has been included in a nomogram outperforming previous clinical models for the prediction of any prostate cancer (PCa) and high grade PCa (HGPCa) at the initial prostate biopsy (IBx). Our objective is to validate such IBx-specific PCA3-based nomogram. We also aim to optimize the use of this nomogram in clinical practice through the definition of risk groups.

METHODS

Independent external validation. Clinical and biopsy data from a contemporary cohort of 401 men with the same inclusion criteria to those used to build up the reference's nomogram in IBx. The predictive value of the nomogram was assessed by means of calibration curves and discrimination ability through the area under the curve (AUC). Clinical utility of the nomogram was analyzed by choosing thresholds points that minimize the overlapping between probability density functions (PDF) in PCa and no PCa and HGPCa and no HGPCa groups, and net benefit was assessed by decision curves.

RESULTS

We detect 28% of PCa and 11 % of HGPCa in IBx, contrasting to the 46 and 20% at the reference series. Due to this, there is an overestimation of the nomogram probabilities shown in the calibration curve for PCa. The AUC values are 0.736 for PCa (C.I.95%:0.68-0.79) and 0.786 for HGPCa (C.I.95%:0.71-0.87) showing an adequate discrimination ability. PDF show differences in the distributions of nomogram probabilities in PCa and not PCa patient groups. A minimization of the overlapping between these curves confirms the threshold probability of harboring PCa >30 % proposed by Hansen is useful to indicate a IBx, but a cut-off > 40% could be better in series of opportunistic screening like ours. Similar results appear in HGPCa analysis. The decision curve also shows a net benefit of 6.31% for the threshold probability of 40%.

CONCLUSIONS

PCA3 is an useful tool to select patients for IBx. Patients with a calculated probability of having PCa over 40% should be counseled to undergo an IBx if opportunistic screening is required.

摘要

背景

在用于预测初次前列腺穿刺活检(IBx)时任何前列腺癌(PCa)和高级别前列腺癌(HGPCa)的列线图中,PCA3已被纳入其中,其性能优于先前的临床模型。我们的目标是验证这种基于IBx特异性PCA3的列线图。我们还旨在通过定义风险组来优化该列线图在临床实践中的应用。

方法

独立外部验证。来自当代401名男性队列的临床和活检数据,这些男性具有与用于构建IBx参考列线图相同的纳入标准。通过校准曲线评估列线图的预测价值,并通过曲线下面积(AUC)评估鉴别能力。通过选择使PCa和非PCa以及HGPCa和非HGPCa组中概率密度函数(PDF)重叠最小的阈值点来分析列线图的临床效用,并通过决策曲线评估净效益。

结果

我们在IBx中检测到28%的PCa和11%的HGPCa,而参考系列中的比例分别为46%和20%。因此,校准曲线中显示的列线图概率被高估。PCa的AUC值为0.736(95%置信区间:0.68 - 0.79),HGPCa的AUC值为0.786(95%置信区间:0.71 - 0.87),显示出足够的鉴别能力。PDF显示PCa和非PCa患者组中列线图概率分布存在差异。这些曲线之间重叠的最小化证实,Hansen提出的患PCa概率>30%的阈值概率对于指示IBx是有用的,但在像我们这样的机会性筛查系列中,>40%的临界值可能更好。HGPCa分析中出现类似结果。决策曲线还显示,40%的阈值概率的净效益为6.31%。

结论

PCA3是选择进行IBx患者的有用工具。如果需要进行机会性筛查,对于计算出患PCa概率超过40%的患者,应建议其接受IBx。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b867/4567811/76733846a06e/12885_2015_1623_Fig1_HTML.jpg

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