A Model for Predicting Clinically Significant Prostate Cancer Using Prostate MRI and Risk Factors.

ABSTRACT:

Purpose

The aim of this study was to develop and validate a predictive model for clinically significant prostate cancer (csPCa) using prostate MRI and patient risk factors.

Methods

In total, 960 men who underwent MRI from 2015 to 2019 and biopsy either 6 months before or 6 months after MRI were identified. Men diagnosed with csPCa were identified, and csPCa risk was modeled using known patient factors (age, race, and prostate-specific antigen [PSA] level) and prostate MRI findings (location, Prostate Imaging Reporting and Data System score, extraprostatic extension, dominant lesion size, and PSA density). csPCa was defined as Gleason score sum ≥ 7. Using a derivation cohort, a multivariable logistic regression model and a point-based scoring system were developed to predict

SUBMITTER: Lacson R 

PROVIDER: S-EPMC12788969 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature