Indication for Active Surveillance in the Era of MRI-Targeted Prostate Biopsies

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;...

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Veröffentlicht in:Urologia internationalis 2022-01, Vol.106 (1), p.83-89
Hauptverfasser: Wetterauer, Christian, Federer-Gsponer, Joel R., Leboutte, Francois D.J.P., Mona, Robin, Ebbing, Jan, Rentsch, Cyrill A., Manka, Lukas, Seifert, Hans H., Wyler, Stephen, Recker, Franz, Kwiatkowski, Maciej
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Sprache:eng
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Zusammenfassung: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.
ISSN:0042-1138
1423-0399
DOI:10.1159/000517300