The influence of prostate volume on clinical parameters in prostate cancer screening

J Clin Lab Anal. 2022 Oct;36(10):e24700. doi: 10.1002/jcla.24700. Epub 2022 Sep 13.

Abstract

Purpose: The purpose of the study was to evaluate the diagnostic significance of two new and a few clinical markers for prostate cancer (PCa) at various prostate volumes (PV).

Methods: The study subjects were divided into two groups. Among them, there were 70 cases in the PV ≤30 ml group (benign prostatic hyperplasia [BPH]: 32 cases, PCa: 38 cases) and 372 cases in the PV > 30 ml group (BPH: 277 cases, PCa: 95 cases). SPSS 26.0 and GraphPad Prism 8.0 were used to construct their receiver operating characteristic (ROC) curves for diagnosing PCa and calculating their area under the ROC curve (AUC).

Results: In the PV ≤30 ml group, the diagnostic parameters based on prostate-specific antigen (PSA) had a decreased diagnostic significance for PCa. In the PV > 30 ml group, PSAD (AUC = 0.709), AVR (AVR = Age/PV, AUC = 0.742), and A-PSAD (A-PSAD = Age×PSA/PV, AUC = 0.736) exhibited moderate diagnostic significance for PCa, which was better than PSA-AV (AUC = 0.672), free PSA (FPSA, AUC = 0.509), total PSA (TPSA, AUC = 0.563), (F/T) PSA (AUC = 0.540), and (F/T)/PSAD (AUC = 0.663). Compared with AVR, A-PSAD exhibited similar diagnostic significance for PCa, but higher than PSA density (PSAD).

Conclusions: Choosing appropriate indicators for different PVs could contribute to the early screening and diagnosis of PCa. The difference in the diagnostic value of two new indicators (A-PSAD and AVR), and PSAD for PCa may require further validation by increasing the sample size.

Keywords: clinical indicator; prostate biopsy; prostate cancer; prostate volume; screening.

MeSH terms

  • Biomarkers
  • Early Detection of Cancer
  • Humans
  • Male
  • Prostate / diagnostic imaging
  • Prostate-Specific Antigen
  • Prostatic Hyperplasia* / diagnosis
  • Prostatic Neoplasms* / diagnosis
  • ROC Curve

Substances

  • Biomarkers
  • Prostate-Specific Antigen