Magnetic Resonance Imaging-based T-staging to Predict Biochemical Recurrence after Radical Prostatectomy: A Step Towards the iTNM Classification
- PMID: 36280445
- DOI: 10.1016/j.euo.2022.09.005
Magnetic Resonance Imaging-based T-staging to Predict Biochemical Recurrence after Radical Prostatectomy: A Step Towards the iTNM Classification
Abstract
Background: Local staging of prostate cancer (PCa) still relies on digital rectal examination (DRE), which therefore remains the standard for risk stratification in guideline recommendations, clinical trials, and patient counseling. This issue is increasingly controversial as multiparametric magnetic resonance imaging (mpMRI) has become the most influential diagnostic tool for local staging of PCa over the past two decades.
Objective: To compare various models of T category based on DRE or mpMRI to predict early biochemical recurrence (BCR) after radical prostatectomy (RP).
Design, setting, and participants: A retrospective multicenter cohort study was conducted between 2014 and 2021. A total of 1436 patients were recruited across eight referral centers in France, Italy, Switzerland, and Belgium.
Outcome measurements and statistical analysis: BCR was defined as two prostate-specific antigen values of ≥0.2 ng/ml during follow-up. Harrell's concordance index (C index) was used to compare the discrimination of four models of T staging based on DRE (model 1: cT1 vs cT2 vs cT3) or mpMRI (model 2: organ-confined disease vs extracapsular extension [iECE] vs seminal vesicle invasion [iSVI]; model 3: Prostate Imaging-Reporting and Data System [PI-RADS] ≤3 vs PI-RADS 4 vs PI-RADS 5; and model 4: iT2a [PI-RADS ≤3] vs iT2b [PI-RADS 4] vs iT2c [PI-RADS 5 excluding ECE or SVI] vs iT3a [ECE] vs iT3b [SVI]) to predict BCR.
Results and limitations: Overall, 74 (5%), 845 (59%), 482 (34%), and 35 (2%) patients had low-, intermediate-, high-, and very high-risk PCa, respectively, according to the Mazzone risk classification. After median follow-up of 16 mo, 113 patients experienced BCR. Although the new five-group mpMRI-based T classification system (model 4) had the highest prognostic discrimination (C index 0.694) for predicting early BCR on multivariable analysis, there was overlap between the 95% confidence intervals of the models. On sensitivity analysis, the new mpMRI-based T staging still had a higher C index than DRE for predicting BCR when excluding cN1 patients and comparing it with a five-group DRE-based T classification (cT1c vs cT2a vs cT2b vs cT2c vs cT3), but the overlap between the 95% confidence intervals of the models remained. The main limitation is the short follow-up.
Conclusions: We described an alternative mpMRI-based T staging for prediction of early BCR after RP for PCa. Our results need to be validated externally before they can be applied in clinical practice.
Patient summary: At present, digital rectal examination of the prostate is used to stage prostate cancer. We developed an alternative model for staging that uses information from magnetic resonance imaging (MRI) scans to predict cancer outcomes for men undergoing surgical removal of the prostate.
Keywords: Biochemical recurrence; Magnetic resonance imaging; Prostate Imaging-Reporting and Data System; Prostate cancer; T stage.
Copyright © 2022 European Association of Urology. Published by Elsevier B.V. All rights reserved.
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