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

BACKGROUND: Several active surveillance (AS) criteria have been established to screen insignificant prostate cancer (insigPCa, defined as organ confined, low grade and small volume tumors confirmed by postoperative pathology). However, their comparative diagnostic performance varies. The aim of this...

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Autores principales: Fan, Yu, Mulati, Yelin, Zhai, Lingyun, Chen, Yuke, Wang, Yu, Feng, Juefei, Yu, Wei, Zhang, Qian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8785217/
https://www.ncbi.nlm.nih.gov/pubmed/35083157
http://dx.doi.org/10.3389/fonc.2021.810736
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author Fan, Yu
Mulati, Yelin
Zhai, Lingyun
Chen, Yuke
Wang, Yu
Feng, Juefei
Yu, Wei
Zhang, Qian
author_facet Fan, Yu
Mulati, Yelin
Zhai, Lingyun
Chen, Yuke
Wang, Yu
Feng, Juefei
Yu, Wei
Zhang, Qian
author_sort Fan, Yu
collection PubMed
description BACKGROUND: Several active surveillance (AS) criteria have been established to screen insignificant prostate cancer (insigPCa, defined as organ confined, low grade and small volume tumors confirmed by postoperative pathology). However, their comparative diagnostic performance varies. The aim of this study was to compare the diagnostic accuracy of contemporary AS criteria and validate the absolute diagnostic odds ratio (DOR) of optimal AS criteria. METHODS: First, we searched Pubmed and performed a Bayesian network meta-analysis (NMA) to compare the diagnostic accuracy of contemporary AS criteria and obtained a relative ranking. Then, we searched Pubmed again to perform another meta-analysis to validate the absolute DOR of the top-ranked AS criteria derived from the NMA with two endpoints: insigPCa and favorable disease (defined as organ confined, low grade tumors). Subgroup and meta-regression analyses were conducted to identify any potential heterogeneity in the results. Publication bias was evaluated. RESULTS: Seven eligible retrospective studies with 3,336 participants were identified for the NMA. The diagnostic accuracy of AS criteria ranked from best to worst, was as follows: Epstein Criteria (EC), Yonsei criteria, Prostate Cancer Research International: Active Surveillance (PRIAS), University of Miami (UM), University of California-San Francisco (UCSF), Memorial Sloan-Kettering Cancer Center (MSKCC), and University of Toronto (UT). I(2) = 50.5%, and sensitivity analysis with different insigPCa definitions supported the robustness of the results. In the subsequent meta-analysis of DOR of EC, insigPCa and favorable disease were identified as endpoints in ten and twenty-two studies, respectively. The pooled DOR for insigPCa and favorable disease were 0.44 (95%CI, 0.31–0.58) and 0.66 (95%CI, 0.61–0.71), respectively. According to a subgroup analysis, the DOR for favorable disease was significantly higher in US institutions than that in other regions. No significant heterogeneity or evidence of publication bias was identified. CONCLUSIONS: Among the seven AS criteria evaluated in this study, EC was optimal for positively identifying insigPCa patients. The pooled diagnostic accuracy of EC was 0.44 for insigPCa and 0.66 when a more liberal endpoint, favorable disease, was used. SYSTEMATIC REVIEW REGISTRATION: [https://www.crd.york.ac.uk/prospero/], PROSPERO [CRD42020157048].
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spelling pubmed-87852172022-01-25 Diagnostic Accuracy of Contemporary Selection Criteria in Prostate Cancer Patients Eligible for Active Surveillance: A Bayesian Network Meta-Analysis Fan, Yu Mulati, Yelin Zhai, Lingyun Chen, Yuke Wang, Yu Feng, Juefei Yu, Wei Zhang, Qian Front Oncol Oncology BACKGROUND: Several active surveillance (AS) criteria have been established to screen insignificant prostate cancer (insigPCa, defined as organ confined, low grade and small volume tumors confirmed by postoperative pathology). However, their comparative diagnostic performance varies. The aim of this study was to compare the diagnostic accuracy of contemporary AS criteria and validate the absolute diagnostic odds ratio (DOR) of optimal AS criteria. METHODS: First, we searched Pubmed and performed a Bayesian network meta-analysis (NMA) to compare the diagnostic accuracy of contemporary AS criteria and obtained a relative ranking. Then, we searched Pubmed again to perform another meta-analysis to validate the absolute DOR of the top-ranked AS criteria derived from the NMA with two endpoints: insigPCa and favorable disease (defined as organ confined, low grade tumors). Subgroup and meta-regression analyses were conducted to identify any potential heterogeneity in the results. Publication bias was evaluated. RESULTS: Seven eligible retrospective studies with 3,336 participants were identified for the NMA. The diagnostic accuracy of AS criteria ranked from best to worst, was as follows: Epstein Criteria (EC), Yonsei criteria, Prostate Cancer Research International: Active Surveillance (PRIAS), University of Miami (UM), University of California-San Francisco (UCSF), Memorial Sloan-Kettering Cancer Center (MSKCC), and University of Toronto (UT). I(2) = 50.5%, and sensitivity analysis with different insigPCa definitions supported the robustness of the results. In the subsequent meta-analysis of DOR of EC, insigPCa and favorable disease were identified as endpoints in ten and twenty-two studies, respectively. The pooled DOR for insigPCa and favorable disease were 0.44 (95%CI, 0.31–0.58) and 0.66 (95%CI, 0.61–0.71), respectively. According to a subgroup analysis, the DOR for favorable disease was significantly higher in US institutions than that in other regions. No significant heterogeneity or evidence of publication bias was identified. CONCLUSIONS: Among the seven AS criteria evaluated in this study, EC was optimal for positively identifying insigPCa patients. The pooled diagnostic accuracy of EC was 0.44 for insigPCa and 0.66 when a more liberal endpoint, favorable disease, was used. SYSTEMATIC REVIEW REGISTRATION: [https://www.crd.york.ac.uk/prospero/], PROSPERO [CRD42020157048]. Frontiers Media S.A. 2022-01-10 /pmc/articles/PMC8785217/ /pubmed/35083157 http://dx.doi.org/10.3389/fonc.2021.810736 Text en Copyright © 2022 Fan, Mulati, Zhai, Chen, Wang, Feng, Yu and Zhang https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Fan, Yu
Mulati, Yelin
Zhai, Lingyun
Chen, Yuke
Wang, Yu
Feng, Juefei
Yu, Wei
Zhang, Qian
Diagnostic Accuracy of Contemporary Selection Criteria in Prostate Cancer Patients Eligible for Active Surveillance: A Bayesian Network Meta-Analysis
title Diagnostic Accuracy of Contemporary Selection Criteria in Prostate Cancer Patients Eligible for Active Surveillance: A Bayesian Network Meta-Analysis
title_full Diagnostic Accuracy of Contemporary Selection Criteria in Prostate Cancer Patients Eligible for Active Surveillance: A Bayesian Network Meta-Analysis
title_fullStr Diagnostic Accuracy of Contemporary Selection Criteria in Prostate Cancer Patients Eligible for Active Surveillance: A Bayesian Network Meta-Analysis
title_full_unstemmed Diagnostic Accuracy of Contemporary Selection Criteria in Prostate Cancer Patients Eligible for Active Surveillance: A Bayesian Network Meta-Analysis
title_short Diagnostic Accuracy of Contemporary Selection Criteria in Prostate Cancer Patients Eligible for Active Surveillance: A Bayesian Network Meta-Analysis
title_sort diagnostic accuracy of contemporary selection criteria in prostate cancer patients eligible for active surveillance: a bayesian network meta-analysis
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8785217/
https://www.ncbi.nlm.nih.gov/pubmed/35083157
http://dx.doi.org/10.3389/fonc.2021.810736
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