Predicting prostate cancer: analysing the clinical efficacy of prostate cancer risk calculators in a referral population

Ir J Med Sci. 2015 Sep;184(3):701-6. doi: 10.1007/s11845-015-1291-8. Epub 2015 Apr 7.

Abstract

Background: The decision to proceed to biopsy for the diagnosis of prostate cancer in clinical practice is a difficult one. Prostate cancer risk calculators allow for a systematic approach to the use of patient information to predict a patient's likelihood of prostate cancer.

Aims: In this paper, we validate the two leading prostate cancer risk calculators, the prostate cancer prevention trial (PCPT) and the European Randomized Study of Screening for Prostate Cancer (ERSPC) in an Irish population.

Methods: Data were collected for 337 men referred to one tertiary referral center in Ireland. Calibration analysis, ROC analysis and decision curve analysis were undertaken to ascertain the performance of the PCPT and the ERSPC risk calculators in this cohort.

Results: Of 337 consecutive biopsies, cancer was subsequently diagnosed in 146 men (43 %), 98 (67 %) of which were high grade. The AUC for the PCPT and ERSPC risk calculators were 0.68 and 0.66, respectively for the prediction of prostate cancer. Each calculator was sufficiently calibrated in this cohort. Decision curve analysis demonstrated a net benefit via the use of the PCPT and ERSPC risk calculators in the diagnosis of prostate cancer.

Conclusions: The PCPT and ERSPC risk calculators achieve a statistically significant prediction of prostate cancer in this Irish population. This study provides external validation for these calculators, and therefore these tools can be used to aid in clinical decision making.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Aged
  • Cohort Studies
  • Decision Support Techniques
  • Early Detection of Cancer / statistics & numerical data*
  • Humans
  • Ireland
  • Male
  • Mass Screening / statistics & numerical data*
  • Middle Aged
  • Prostatic Neoplasms / epidemiology*
  • ROC Curve
  • Referral and Consultation / statistics & numerical data
  • Treatment Outcome