Evidence map›Paper›PMID 37448610›Full record

ArticleCurrent urology2023

Learning curve for magnetic resonance imaging/ultrasound fusion prostate biopsy in detecting prostate cancer using cumulative sum analysis.

Linhan Xu, Nancy Yating Ye, Adrianna Lee, Jasleen Chopra, Michael Naslund, Jade Wong-You-Cheong, Amelia Wnorowski, Mohummad Minhaj Siddiqui

Open access · diamondAbstract read
In one paragraph

Article in Current urology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.7field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 13 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Linhan XuUniversity of Maryland School of Medicine, Baltimore, MD, USA.
Nancy Yating YeDivision of Urology, Department of General Surgery, Kaiser Permanente Los Angeles Medical Center, Los Angeles, CA, USA.
Adrianna LeeUniversity of Maryland School of Medicine, Baltimore, MD, USA.
Jasleen ChopraDepartment of Diagnostic Radiology, University of Maryland School of Medicine, Baltimore, MD, USA.
Michael NaslundDivision of Urology, Department of Surgery, University of Maryland School of Medicine, University of Maryland Medical Center, Baltimore, MD, USA.
Jade Wong-You-CheongDepartment of Diagnostic Radiology, University of Maryland School of Medicine, Baltimore, MD, USA.
Amelia WnorowskiDepartment of Diagnostic Radiology, University of Maryland School of Medicine, Baltimore, MD, USA.
Mohummad Minhaj SiddiquiDivision of Urology, Department of Surgery, University of Maryland School of Medicine, University of Maryland Medical Center, Baltimore, MD, USA.
University of Maryland, Baltimore · USKaiser Permanente · USUniversity of Maryland Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Cumulative sum analysisLearning curveMagnetic resonance/ultrasound fusion biopsyProstate cancer

Identifiers

PMID37448610
PMCPMC10337819
OpenAlexW4292640224

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.