The influence of prostate volume in prostate health index performance in patients with total PSA lower than 10 μg/L

被引:30
作者
Filella, Xavier [1 ]
Foj, Laura [1 ]
Alcover, Joan [2 ]
Auge, Josep Maria [1 ]
Molina, Rafael [1 ]
Jimenez, Wladimiro [1 ]
机构
[1] Hosp Clin Barcelona, Dept Biochem & Mol Genet CDB, IDIBAPS, E-08036 Barcelona, Catalonia, Spain
[2] Hosp Clin Barcelona, Dept Urol, IDIBAPS, E-08036 Barcelona, Catalonia, Spain
关键词
Prostate cancer; Prostate health index; PSA; p2PSA; Prostate volume; SIGNIFICANTLY IMPROVES; CANCER DETECTION; MULTICENTER; PREDICTION; ANTIGEN; NG/ML; ISOFORM; MARKERS; NETWORK;
D O I
10.1016/j.cca.2014.06.019
中图分类号
R446 [实验室诊断]; R-33 [实验医学、医学实验];
学科分类号
1001 ;
摘要
Prostate health index (phi), a measure calculated as p2PSA/fPSA x root tPSA, has shown valuable results in the detection of prostate cancer (PCa), improving the prediction of the aggressiveness of the tumor. The aim of our study was to test whether prostate volume influences phi performance using univariate and multivariate models. 220 patients with PSA < 10 mu g/L (102 with negative biopsy and 118 with PCa) were included in the study. Serum concentrations of tPSA, fPSA and p2PSA were measured on Access2 analyzer. The higher accuracy was found for phi, obtaining an AUC of 0.748. Bigger AUCs were obtained for phi, %p2PSA, %fPSA and tPSA in patients with small prostate volume (<= 35 cc); meanwhile, the lowest AUCs were found in patients with large prostate volume (>50 cc). Including phi and %p2PSA in a multivariable analysis based on patient age, prostate volume, tPSA, and %fPSA accuracy increased from 0.762 to 0.802 (logistic regression model) or 0.815 (artificial neural network). Accuracy excluding prostate volume in these models was 0.762 and 0.775, respectively. The inclusion of phi and %p2PSA in a multivariate model identifies better men with PCa. Prostate volume remains a key factor in the interpretation of biomarkers used to detect PCa. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:303 / 307
页数:5
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