Prediction of future risk of any and higher-grade prostate cancer based on the PLCO and SELECT trials.

Abstract

BACKGROUND:

A model was built that characterized effects of individual factors on five-year prostate cancer (PCa) risk in the Prostate, Lung, Colon, and Ovarian Cancer Screening Trial (PLCO) and the Selenium and Vitamin E Cancer Prevention Trial (SELECT). This model was validated in a third San Antonio Biomarkers of Risk (SABOR) screening cohort.

METHODS:

A prediction model for 1- to 5-year risk of developing PCa and Gleason > 7 PCa (HG PCa) was built on PLCO and SELECT using the Cox proportional hazards model adjusting for patient baseline characteristics. Random forests and neural networks were compared to Cox proportional hazard survival models, using the trial datasets for model building and the SABOR cohort for model evaluation. The most accurate prediction model is included in an online calculator.

RESULTS:

The respective rates of PCa were 8.9%, 7.2%, and 11.1% in PLCO (n = 31,495), SELECT (n = 35,507), and SABOR (n = 1790) over median follow-up of 11.7, 8.1 and 9.0 years. The Cox model showed higher prostate-specific antigen (PSA), BMI and age, and African American race to be associated with PCa and HGPCa. Five-year risk predictions from the combined SELECT and PLCO model effectively discriminated risk in the SABOR cohort with C-index 0.76 (95% CI [0.72, 0.79]) for PCa, and 0.74 (95% CI [0.65,0.83]) for HGPCa.

CONCLUSIONS:

A 1- to 5-year PCa risk prediction model developed from PLCO and SELECT was validated with SABOR and implemented online. This model can individualize and inform shared screening decisions.

• Authors: Jonathan A Gelfond, Brian Hernandez, Martin Goros, Joseph G Ibrahim, Ming-Hui Chen, Wei Sun, Robin J Leach, Michael W Kattan, Ian M Thompson, Donna Pauler Ankerst, Michael Liss
• Journal: BMC urology (BMC Urol) Vol. 22 Issue 1 Pg. 45 (Mar 26 2022) ISSN: 1471-2490 [Electronic] England
• PMID: 35351104 (Publication Type: Journal Article)
• Copyright: © 2022. The Author(s).

Topics

• Cohort Studies
• Early Detection of Cancer
• Humans
• Male
• Proportional Hazards Models
• Prostate
• Prostatic Neoplasms (diagnosis, epidemiology, prevention & control)