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Learning curve for magnetic resonance imaging/ultrasound fusion prostate biopsy in detecting prostate cancer using cumulative sum analysis.
Xu, Linhan; Ye, Nancy Yating; Lee, Adrianna; Chopra, Jasleen; Naslund, Michael; Wong-You-Cheong, Jade; Wnorowski, Amelia; Siddiqui, Mohummad Minhaj.
Afiliación
  • Xu L; University of Maryland School of Medicine, Baltimore, MD, USA.
  • Ye NY; Division of Urology, Department of General Surgery, Kaiser Permanente Los Angeles Medical Center, Los Angeles, CA, USA.
  • Lee A; University of Maryland School of Medicine, Baltimore, MD, USA.
  • Chopra J; Department of Diagnostic Radiology, University of Maryland School of Medicine, Baltimore, MD, USA.
  • Naslund M; Division of Urology, Department of Surgery, University of Maryland School of Medicine, University of Maryland Medical Center, Baltimore, MD, USA.
  • Wong-You-Cheong J; Department of Diagnostic Radiology, University of Maryland School of Medicine, Baltimore, MD, USA.
  • Wnorowski A; Department of Diagnostic Radiology, University of Maryland School of Medicine, Baltimore, MD, USA.
  • Siddiqui MM; Division of Urology, Department of Surgery, University of Maryland School of Medicine, University of Maryland Medical Center, Baltimore, MD, USA.
Curr Urol ; 17(3): 159-164, 2023 Sep.
Article en En | MEDLINE | ID: mdl-37448610
Background: Targeted magnetic resonance (MR) with ultrasound (US) fusion-guided biopsy has been shown to improve detection of prostate cancer. The implementation of this approach requires integration of skills from radiologists and urologists. Objective methods for assessment of learning curves, such as cumulative sum (CUSUM) analysis, may be helpful in identifying the presence and duration of a learning curve. The aim of this study is to determine the learning curve for MR/US fusion-guided biopsy in detecting clinically significant prostate cancer using CUSUM analysis. Materials and methods: Retrospective analysis was performed in this institutional review board-approved study. Two urologists implemented an MR/US fusion-guided prostate biopsy program between March 2015 and September 2017. The primary outcome measure was cancer detection rate (CDR) stratified by Prostate Imaging Reporting and Data System (PI-RADS) scores assigned on the MR imaging. Cumulative sum analysis quantified actual cancer detection versus a predetermined target satisfactory CDR of MR/US fusion biopsies in a sequential case-by-case basis. For this analysis, satisfactory performance was defined as >80% CDR in patients with PI-RADS 5, >50% in PI-RADS 4, and <20% in PI-RADS 1-3. Results: Complete data were available for MR/US fusion-guided biopsies performed on 107 patients. The CUSUM learning curve analysis demonstrated intermittent underperformance until approximately 50 cases. After this inflection point, there was consistently good performance, evidence that no further learning curve was being encountered. Conclusions: At a new center implementing MR/US fusion-guided prostate biopsy, the learning curve was approximately 50 cases before a consistently high performance for prostate cancer detection.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Curr Urol Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Curr Urol Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos