Prostate Cancer Prevention Trial risk calculator 2.0 for the prediction of low- vs high-grade prostate cancer.
Abstract
To modify the Prostate Cancer Prevention Trial risk calculator (PCPTRC) to predict low- vs high-grade (Gleason grade≥7) prostate cancer and incorporate percent free-prostate-specific antigen (PSA).
Data from 6664 Prostate Cancer Prevention Trial placebo arm biopsies (5826 individuals), where prostate-specific antigen and digital rectal examination results were available within 1 year before the biopsy and PSA was ≤10 ng/mL, were used to develop a nominal logistic regression model to predict the risk of no vs low-grade (Gleason grade<7) vs high-grade cancer (Gleason grade≥7). Percent free-PSA was incorporated into the model based on likelihood ratio analysis of a San Antonio Biomarkers of Risk cohort. Models were externally validated on 10 Prostate Biopsy Collaborative Group cohorts and 1 Early Detection Research Network reference set.
Of all the Prostate Cancer Prevention Trial biopsies, 5468 (82.1%) were negative for prostate cancer, 942 (14.1%) detected low-grade, and 254 (3.8%) detected high-grade disease. Significant predictors were (log base 2) PSA (odds ratio for low-grade vs no cancer, 1.29*; high-grade vs no cancer, 2.02*; high-grade vs low-grade cancer, 1.57*), digital rectal examination (0.96, 1.49*, 1.55*, respectively), age (1.02*, 1.05*, 1.03*, respectively), African American race (1.13, 2.83*, 2.51*, respectively), prior biopsy (0.63*, 0.81, 1.27, respectively), and family history (1.31*, 1.25, 0.95, respectively), where * indicates P value<.05. The new PCPTRC 2.0 either with or without percent free-PSA (also significant by the likelihood ratio method) validated well externally.
By differentiating the risk of low- vs high-grade disease on biopsy, PCPTRC 2.0 better enables physician-patient counseling concerning whether to proceed to biopsy.
EDRN PI Authors
Medline Author List
- Ankerst DP
- Bock S
- Goodman PJ
- Hernandez J
- Hoefler J
- Leach RJ
- Sanda MG
- Sokoll LJ
- Thompson IM
- Vickers A
- Wei JT