Literature DB >> 30429594

The role of Prostate Imaging Reporting and Data System score in Gleason 3 + 3 active surveillance candidates enrollment: a diagnostic meta-analysis.

Lingyun Zhai1,2,3,4, Yu Fan1,2,5,3,4, Yisen Meng1,2,3,4, Xueru Feng6, Wei Yu7,8,9,10, Jie Jin11,12,13,14.   

Abstract

BACKGROUND: The contemporary active surveillance (AS) criteria may result in an unsatisfactory misclassification rate, which may delay curative treatment for prostate cancer patients. The magnetic resonance imaging (MRI), not included in any AS criteria, provides useful information for prostate cancer diagnosis. Our goal is to evaluate the diagnostic performance of Prostate Imaging Reporting and Data Systems (PI-RADS) score, a standardized MRI reporting system, in AS candidates enrollment.
METHODS: We searched Cochrane CENTRAL, PubMed, and Embase for pertinent studies through June 2018. The standard methods recommended for meta-analyses of diagnostic evaluation were employed. We draw the summary receiver operating characteristic (SROC) curve. Meta-regression analysis was performed to evaluate the effects of confounding factors.
RESULTS: From the resulting 168 studies, 5 provided the diagnostic data on PI-RADS score and pathological results; 834 patients were included. All AS candidates in these studies were defined by Prostate Cancer Research International: Active Surveillance (PRIAS) criterion. The pooled estimates of PI-RADS 4 or 5 on adverse pathological features at radical prostatectomy (RP) among AS candidates were: sensitivity, 0.77 (95% confidence interval (CI), 0.71-0.82); specificity, 0.63 (95% CI, 0.55-0.71); positive predictive value, 0.72 (95% CI, 0.64-0.79); negative predictive value, 0.68 (95% CI, 0.63-0.73); and diagnostic odds ratio, 6 (95% CI, 4-8). The SROC curve was positioned toward the desired upper left corner of the curve, the area under the curve was 0.77 (95% CI, 0.73-0.80). The P-value for heterogeneity was <0.01. The pathological outcomes and endorectal coils contributed to the heterogeneity of sensitivity. The evidences supporting the advantage of PI-RADS v2 over v1 were not sufficient yet.
CONCLUSION: AS candidates with PI-RADS 4 or 5 may be unsuitable for AS even though they fulfill current AS criteria. Those with PI-RADS 3 or less indicated relative safety for AS enrollment.

Entities:  

Year:  2018        PMID: 30429594     DOI: 10.1038/s41391-018-0111-4

Source DB:  PubMed          Journal:  Prostate Cancer Prostatic Dis        ISSN: 1365-7852            Impact factor:   5.554


  6 in total

1.  Diagnostic Accuracy of Contemporary Selection Criteria in Prostate Cancer Patients Eligible for Active Surveillance: A Bayesian Network Meta-Analysis.

Authors:  Yu Fan; Yelin Mulati; Lingyun Zhai; Yuke Chen; Yu Wang; Juefei Feng; Wei Yu; Qian Zhang
Journal:  Front Oncol       Date:  2022-01-10       Impact factor: 6.244

Review 2.  The current role of MRI for guiding active surveillance in prostate cancer.

Authors:  Guillaume Ploussard; Olivier Rouvière; Morgan Rouprêt; Roderick van den Bergh; Raphaële Renard-Penna
Journal:  Nat Rev Urol       Date:  2022-04-07       Impact factor: 16.430

Review 3.  Advances in the selection of patients with prostate cancer for active surveillance.

Authors:  James L Liu; Hiten D Patel; Nora M Haney; Jonathan I Epstein; Alan W Partin
Journal:  Nat Rev Urol       Date:  2021-02-23       Impact factor: 14.432

4.  Complementing the active surveillance criteria with multiparametric magnetic resonance imaging.

Authors:  Tae Un Kim; Seung Ryong Baek; Won Hoon Song; Jong Kil Nam; Hyun Jung Lee; Sung Woo Park
Journal:  Investig Clin Urol       Date:  2020-11

5.  Five-year Outcomes of Magnetic Resonance Imaging-based Active Surveillance for Prostate Cancer: A Large Cohort Study.

Authors:  Vasilis Stavrinides; Francesco Giganti; Bruce Trock; Shonit Punwani; Clare Allen; Alex Kirkham; Alex Freeman; Aiman Haider; Rhys Ball; Neil McCartan; Hayley Whitaker; Clement Orczyk; Mark Emberton; Caroline M Moore
Journal:  Eur Urol       Date:  2020-04-30       Impact factor: 20.096

6.  MRI-derived radiomics model for baseline prediction of prostate cancer progression on active surveillance.

Authors:  Nikita Sushentsev; Leonardo Rundo; Oleg Blyuss; Vincent J Gnanapragasam; Evis Sala; Tristan Barrett
Journal:  Sci Rep       Date:  2021-06-21       Impact factor: 4.379

  6 in total

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