Your browser doesn't support javascript.
loading
ERG rearrangement as a novel marker for predicting the extra-prostatic extension of clinically localised prostate cancer.
Lu, L I; Zhang, Hao; Pang, Jun; Hou, Guo-Liang; Lu, Min-Hua; Gao, Xin.
Afiliação
  • Lu LI; Department of Urology, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong 510630, P.R. China.
  • Zhang H; Department of Urology, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong 510630, P.R. China.
  • Pang J; Department of Urology, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong 510630, P.R. China.
  • Hou GL; Department of Urology, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong 510630, P.R. China.
  • Lu MH; Department of Urology, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong 510630, P.R. China.
  • Gao X; Department of Urology, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong 510630, P.R. China.
Oncol Lett ; 11(4): 2532-2538, 2016 Apr.
Article em En | MEDLINE | ID: mdl-27073512
ABSTRACT
Currently, there are no well-established preoperative clinicopathological parameters for predicting extra-prostatic extension (EPE) in patients with clinically localised prostate cancer (PCa). The transmembrane protease serine 2 (TMPRSS2)-ETS-related gene (ERG) fusion gene is a specific biomarker of PCa and is considered a prognostic predictor. The aim of the present study was to assess the value of this marker for predicting EPE in patients with clinically localised PCa. In total, 306 PCa patients with clinically localised disease, including 220 patients (71.9%) with organ-confined disease and 86 EPE cases (28.1%), were included in the study. Receiver operating characteristic curves and logistic regression were employed to establish the optimal cut-off value and to investigate whether ERG rearrangement was an independent predictor for the EPE of clinically localised PCa. A leave-one-out cross-validation (LOOCV) model was implemented to validate the predictive power of ERG rearrangement. An increase in ERG rearrangements was identified to be associate'd with EPE, and the optimal cut-off for predicting EPE was determined to be 2.25%, with a sensitivity of 70.24% [95% confidence interval (CI), 62.6-78.9%], a specificity of 80.43% (95% CI, 75.4-85.1%), and an area under the curve (AUC) of 0.781 (95% CI, 0.730-0.826). In the LOOCV model, ERG rearrangement also demonstrated good performance for predicting EPE (sensitivity, 76.923%; specificity, 71.429%; 95% CI for AUC, 0.724-0.958). In addition, a high Gleason score (≥7) and a cT2c classification upon biopsy were independent factors for EPE.
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2016 Tipo de documento: Article