Developing a predictive model for clinically significant prostate cancer by combining age, PSA density, and mpMRI

ABSTRACT:

Purpose

The study aimed to construct a predictive model for clinically significant prostate cancer (csPCa) and investigate its clinical efficacy to reduce unnecessary prostate biopsies.

Methods

A total of 847 patients from institute 1 were included in cohort 1 for model development. Cohort 2 included a total of 208 patients from institute 2 for external validation of the model. The data obtained were used for retrospective analysis. The results of magnetic resonance imaging were obtained using Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1). Univariate and multivariate analyses were performed to determine significant predictors of csPCa. The diagnostic performances were compared using the receiver operating characteristic (ROC) curve and decision cur

SUBMITTER: Ma Z 

PROVIDER: S-EPMC9990202 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature