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基于PCA3的列线图用于预测初次经直肠引导活检时的前列腺癌和高级别癌。

PCA3-based nomogram for predicting prostate cancer and high grade cancer on initial transrectal guided biopsy.

作者信息

Elshafei Ahmed, Chevli K Kent, Moussa Ayman S, Kara Onder, Chueh Shih-Chieh, Walter Peter, Hatem Asmaa, Gao Tianming, Jones J Stephen, Duff Michael

机构信息

Glickman Urological & Kidney Institute Cleveland Clinic Foundation, Cleveland, Ohio.

Urology Department, Al Kasr Al Aini Hospital, Cairo University, Giza, Egypt.

出版信息

Prostate. 2015 Dec;75(16):1951-7. doi: 10.1002/pros.23096. Epub 2015 Sep 18.

Abstract

BACKGROUND

To develop a validated prostate cancer antigen 3 (PCA3) based nomogram that predicts likelihood of overall prostate cancer (PCa) and intermediate/high grade prostate cancer (HGPCa) in men pursuing initial transrectal prostate biopsy (TRUS-PBx).

METHODS

Data were collected on 3,675 men with serum prostate specific antigen level (PSA) ≤ 20 ng/ml who underwent initial prostate biopsy with at least 10 cores sampling at time of the biopsy. Two logistic regression models were constructed to predict overall PCa and HGPCa incorporating age, race, family history (FH) of PCa, PSA at diagnosis, PCA3, total prostate volume (TPV), and digital rectal exam (DRE).

RESULTS

One thousand six hundred twenty (44%) patients had biopsy confirmed PCa with 701 men (19.1%) showing HGPCa. Statistically significant predictors of overall PCa were age (P < 0.0001, OR. 1.51), PSA at diagnosis (P < 0.0001, OR.1.95), PCA3 (P < 0.0001, OR.3.06), TPV (P < 0.0001, OR.0.47), FH (P = 0.003, OR.1.32), and abnormal DRE (P = 0.001, OR. 1.32). While for HGPCa, predictors were age (P < 0.0001, OR.1.77), PSA (P < 0.0001, OR.2.73), PCA3 (P < 0.0001, OR.2.26), TPV (P < 0.0001, OR.0.4), and DRE (P < 0.0001, OR.1.53). Two nomograms were reconstructed for predicted overall PCa probability at time of initial biopsy with a concordance index of 0.742 (Fig. 1), and HGPCa with a concordance index of 0.768 (Fig. 2).

CONCLUSIONS

Our internally validated initial biopsy PCA3 based nomogram is reconstructed based on a large dataset. The c-index indicates high predictive accuracy, especially for high grade PCa and improves the ability to predict biopsy outcomes.

摘要

背景

开发一种基于前列腺癌抗原3(PCA3)的经过验证的列线图,用于预测接受初次经直肠前列腺穿刺活检(TRUS-PBx)的男性患总体前列腺癌(PCa)和中/高级别前列腺癌(HGPCa)的可能性。

方法

收集了3675名血清前列腺特异性抗原水平(PSA)≤20 ng/ml且在活检时接受至少10针穿刺取样的初次前列腺活检男性的数据。构建了两个逻辑回归模型,以纳入年龄、种族、PCa家族史(FH)、诊断时的PSA、PCA3、前列腺总体积(TPV)和直肠指检(DRE)来预测总体PCa和HGPCa。

结果

1620名(44%)患者活检确诊为PCa,其中701名男性(19.1%)为HGPCa。总体PCa的统计学显著预测因素为年龄(P<0.0001,OR.1.51)、诊断时的PSA(P<0.0001,OR.1.95)、PCA3(P<0.0001,OR.3.06)、TPV(P<0.0001,OR.0.47)、FH(P = 0.003,OR.1.32)和异常DRE(P = 0.001,OR.1.32)。而对于HGPCa,预测因素为年龄(P<0.0001,OR.1.77)、PSA(P<0.0001,OR.2.73)、PCA3(P<0.0001,OR.2.26)、TPV(P<0.0001,OR.0.4)和DRE(P<0.0001,OR.1.53)。重建了两个列线图,用于预测初次活检时总体PCa的概率,一致性指数为0.742(图1),以及HGPCa的一致性指数为0.768(图2)。

结论

我们基于内部验证的初次活检PCA3的列线图是基于一个大型数据集重建的。c指数表明预测准确性高,特别是对于高级别PCa,并提高了预测活检结果的能力。

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