Urinary Biomarker Panel to Improve Accuracy in Predicting Prostate Biopsy Result in Chinese Men with PSA 4-10 ng/mL

Biomed Res Int. 2017:2017:2512536. doi: 10.1155/2017/2512536. Epub 2017 Feb 15.

Abstract

This study aims to evaluate the effectiveness and clinical performance of a panel of urinary biomarkers to diagnose prostate cancer (PCa) in Chinese men with PSA levels between 4 and 10 ng/mL. A total of 122 patients with PSA levels between 4 and 10 ng/mL who underwent consecutive prostate biopsy at three hospitals in China were recruited. First-catch urine samples were collected after an attentive prostate massage. Urinary mRNA levels were measured by quantitative real-time polymerase chain reaction (qRT-PCR). The predictive accuracy of these biomarkers and prediction models was assessed by the area under the curve (AUC) of the receiver-operating characteristic (ROC) curve. The diagnostic accuracy of PCA3, PSGR, and MALAT-1 was superior to that of PSA. PCA3 performed best, with an AUC of 0.734 (95% CI: 0.641, 0.828) followed by MALAT-1 with an AUC of 0.727 (95% CI: 0.625, 0.829) and PSGR with an AUC of 0.666 (95% CI: 0.575, 0.749). The diagnostic panel with age, prostate volume, % fPSA, PCA3 score, PSGR score, and MALAT-1 score yielded an AUC of 0.857 (95% CI: 0.780, 0.933). At a threshold probability of 20%, 47.2% of unnecessary biopsies may be avoided whereas only 6.2% of PCa cases may be missed. This urinary panel may improve the current diagnostic modality in Chinese men with PSA levels between 4 and 10 ng/mL.

MeSH terms

  • Aged
  • Algorithms
  • Biomarkers, Tumor / urine*
  • Biopsy
  • China
  • Humans
  • Male
  • Middle Aged
  • Probability
  • Prostate / pathology
  • Prostate-Specific Antigen / urine*
  • Prostatic Neoplasms / diagnosis*
  • Prostatic Neoplasms / ethnology
  • Prostatic Neoplasms / urine*
  • ROC Curve
  • Real-Time Polymerase Chain Reaction
  • Regression Analysis
  • Reproducibility of Results
  • Severity of Illness Index

Substances

  • Biomarkers, Tumor
  • Prostate-Specific Antigen