Guerra, A.; Alves, F.C.; Maes, K.; Maio, R.; Villeirs, G.; Mouriño, H. Risk Biomarkers for Biochemical Recurrence after Radical Prostatectomy for Prostate Cancer Using Clinical and MRI-Derived Semantic Features. Cancers2023, 15, 5296.
Guerra, A.; Alves, F.C.; Maes, K.; Maio, R.; Villeirs, G.; Mouriño, H. Risk Biomarkers for Biochemical Recurrence after Radical Prostatectomy for Prostate Cancer Using Clinical and MRI-Derived Semantic Features. Cancers 2023, 15, 5296.
Guerra, A.; Alves, F.C.; Maes, K.; Maio, R.; Villeirs, G.; Mouriño, H. Risk Biomarkers for Biochemical Recurrence after Radical Prostatectomy for Prostate Cancer Using Clinical and MRI-Derived Semantic Features. Cancers2023, 15, 5296.
Guerra, A.; Alves, F.C.; Maes, K.; Maio, R.; Villeirs, G.; Mouriño, H. Risk Biomarkers for Biochemical Recurrence after Radical Prostatectomy for Prostate Cancer Using Clinical and MRI-Derived Semantic Features. Cancers 2023, 15, 5296.
Abstract
Objectives: This study aimed to assess the impact of a predictive model for detecting extracapsular extension on pathology (pECE+) on biochemical recurrence-free survival (BCRFS) within 4 years after robotic-assisted radical prostatectomy (RARP). Methods: Retrospective data analysis from a single center between 2015 to 2022. Variables under consideration included prostate-specific antigen (PSA) levels, patient age, prostate volume, MRI semantic features and Gleason score (GS). We also assessed the influence of pECE+ and positive surgical margins on BCRFS. using the Kaplan-Meier survival function and Cox regression model were assessed. Additionally, we analyzed the MRI features on BCR (biochemical recurrence) in low/intermediate risk patients. Results: 177 participants with a follow-up exceeding 6 months post-RARP were included. The 1-year, 2-year, and 4-year risks of BCR after curative prostatectomy were 5%, 13%, and 21%, respectively. The survival analysis showed that adverse MRI features as macroscopic ECE on MRI (mECE+), capsular disruption, high tumor capsular contact length (TCCL), GS≥8, positive surgical margins (PSM), and pECE+ on pathology were risk factors for BCR. In low/intermediate-risk patients (pECE- and GS <(4+4)) the presence of adverse MRI features, has been shown to increase the risk of BCR. Conclusions: The study highlights the importance of incorporating predictive MRI features for detecting extracapsular extension pre-surgery in influencing early outcomes and clinical decision-making; mECE+, TCCL, capsular disruption, and GS≥8 based on pre-surgical biopsy were independent prognostic factors for early BCR. The presence of adverse features on MRI can assist in identifying low/intermediate-risk patients who would benefit from closer monitoring.
Copyright:
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