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 curve analyses. Results Age, prostate-specific antigen density (PSAD), and PI-RADS v2.1 scores were used as predictors of the model. In the development cohort, the areas under the ROC curve (AUC) for csPCa about age, PSAD, PI-RADS v2.1 scores, and the model were 0.675, 0.823, 0.875, and 0.938, respectively. In the external validation cohort, the AUC values predicted by the four were 0.619, 0.811, 0.863, and 0.914, respectively. Decision curve analysis revealed that the clear net benefit of the model was higher than PI-RADS v2.1 scores and PSAD. The model significantly reduced unnecessary prostate biopsies within the risk threshold of > 10%. Conclusions In both internal and external validation, the model constructed by combining age, PSAD, and PI-RADS v2.1 scores exhibited excellent clinical efficacy and can be utilized to reduce unnecessary prostate biopsies.

Long-term follow-up results of multiparametric prostate MRI and the prognostic value of PI-RADS: a single-center retrospective cohort study

“…Wang et al 21 , in their study evaluating risk factors associated with progression in patients undergoing active surveillance for PCa, found that both PI-RADS category and PSAD were significant factors in both univariable and multivariable analyses. Ma et al 22 included age as a variable in their predictive model for cs-PCa, in addition to the PI-RADS category and PSAD, and achieved an AUC of 0.914 after external validation. Patel et al 23 emphasized the importance of prior biopsy status and reported that the percentages of PCa and cs-PCa in biopsy-naïve cases were approximately twice as high as those in cases with prior negative biopsies.…”

Reliability of Systematic and Targeted Biopsies versus Prostatectomy

“…There are several studies devoted to diagnosis of prostate cancer by prostatectomy [19][20][21][22][23]. A number of studies compare the efficacy of systematic biopsy (SBx) with other types of biopsies [24][25][26][27], none of which is a gold standard. Prostatectomy is accurate but cannot be a gold standard procedure.…”