Indication for Active Surveillance in the Era of MRI-Targeted Prostate Biopsies
| Autor: | Joel R Federer-Gsponer, Christian Wetterauer, Maciej Kwiatkowski, Franz Recker, Robin Mona, Hans Helge Seifert, Lukas Manka, F. Leboutte, Cyrill A. Rentsch, Stephen Wyler, Jan Ebbing |
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| Rok vydání: | 2021 |
| Předmět: |
Image-Guided Biopsy
Male medicine.medical_specialty Prostate biopsy Overtreatment medicine.diagnostic_test business.industry Urology Prostatic Neoplasms Cancer Middle Aged Magnetic Resonance Imaging Interventional medicine.disease Prostate cancer medicine.anatomical_structure Prostate medicine Retrospective analysis Humans Radiology Watchful Waiting business Aged Retrospective Studies |
| Zdroj: | Urologia Internationalis. 106:83-89 |
| ISSN: | 1423-0399 0042-1138 |
| DOI: | 10.1159/000517300 |
| Popis: | Introduction: Active surveillance (AS) strategies were established to avoid overtreatment of low-risk prostate cancer (PCa) patients. Low tumor volume represents one indication criteria; however, applying this criterion after MRI-targeted prostate biopsies may lead to overestimation of tumor volume; wherefore, patients suitable for AS would be exposed to the risk of overtreatment. Methods: This retrospective analysis included 318 patients in which PCa was detected by MRI-TRUS fusion prostate biopsy. Classic and extended indication for AS included Gleason 6 and Gleason 3 + 4 cancer, respectively. We assessed the effect of targeted biopsies and temporary rating strategies on eligibility for AS and developed new “composite” algorithms to more accurately assess eligibility for AS. Results: Forty-four (13.8%) and 60 (18.9%) of the 318 patients qualified for AS according to “classic” and “extended” criteria, respectively. Application of the “composite 1” definition led to AS eligibility of 52 of 248 patients (20.97%) in the classic and of 77 of 248 patients (31.05%) in the “extended” group. Conclusions: We could demonstrate that classic algorithms led to ineligibility of patients for AS. We propose a new rating algorithm to improve tumor assessment for a more accurate indication for AS. |
| Databáze: | OpenAIRE |
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