Cargando…
Optimizing biopsy strategy for prostate cancer: Bayesian framework of network meta-analysis and hierarchical summary receiver operating characteristic model for diagnostic accuracy
Overdiagnosis and overtreatment are well known problems in prostate cancer (PCa). The transrectal ultrasound (TRUS) Guided biopsy (GB) as a current gold standard investigation has a low positive detection rate resulting in unnecessary biopsies. The choice of optimal biopsy strategy needs to be defin...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer - Medknow
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8033239/ https://www.ncbi.nlm.nih.gov/pubmed/33850352 http://dx.doi.org/10.4103/iju.IJU_187_20 |
_version_ | 1783676373025423360 |
---|---|
author | Rahman, Ilham Akbar Nusaly, Ilham Fauzan Syahrir, Syakri Nusaly, Harry Kasim, Firdaus |
author_facet | Rahman, Ilham Akbar Nusaly, Ilham Fauzan Syahrir, Syakri Nusaly, Harry Kasim, Firdaus |
author_sort | Rahman, Ilham Akbar |
collection | PubMed |
description | Overdiagnosis and overtreatment are well known problems in prostate cancer (PCa). The transrectal ultrasound (TRUS) Guided biopsy (GB) as a current gold standard investigation has a low positive detection rate resulting in unnecessary biopsies. The choice of optimal biopsy strategy needs to be defined. Therefore, we undertook a Bayesian network meta analysis (NMA) and Bayesian prediction in the hierarchical summary receiver operating characteristic (HSROC) model to present a method for optimizing biopsy strategy in PCa. Twenty eight relevant studies were retrieved through online databases of EMBASE, MEDLINE, and CENTRAL up to February 2020. Markov chain Monte Carlo simulation and Surface Under the Cumulative RAnking curve were used to calculate the rank probability using odds ratio with 95% credible interval. HSROC model was used to formulate the predicted true sensitivity and specificity of each biopsy strategy. Six different PCa biopsy strategies including transrectal ultrasound GB (TRUS GB), fusion GB (FUS GB), fusion + transrectal ultrasound GB (FUS + TRUS GB), magnetic resonance imaging GB (MRI GB), transperineal ultrasound GB (TPUS GB), and contrast enhanced ultrasound GB were analyzed in this study with a total of 7584 patients. These strategies were analyzed on five outcomes including detection rate of overall PCa, clinically significant PCa, insignificant PCa, complication rate, and HSROC. The rank probability showed that the overall PCa detection rate was higher in FUS + TRUS GB, MRI GB, and FUS GB. In terms of clinically significant PCa detection, FUS + TRUS GB and FUS GB had a relatively higher clinically significant PCa detection rate, whereas TRUS GB had a relatively lower rate for clinically significant PCa detection rate. MRI GB (91% and 81%) and FUS GB (82% and 83%) had the highest predicted true sensitivity and specificity, respectively, whereas TRUS GB (62% and 83%) had a lower predicted true sensitivity and specificity. MRI GB, FUS GB, and FUS + TRUS GB were associated with lower complication rate, whereas TPUS GB and TRUS GB were more associated with higher complication rate. This NMA and HSROC model highlight the important finding that FUS + TRUS GB, FUS GB, and MRI GB were superior compared with other strategies to avoid the overdiagnosis and overtreatment of PCa. FUS GB, MRI GB, and FUS + TRUS GB had lower complication rates. These results may assist in shared decision making between patients, carers, and their surgeons. |
format | Online Article Text |
id | pubmed-8033239 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Wolters Kluwer - Medknow |
record_format | MEDLINE/PubMed |
spelling | pubmed-80332392021-04-12 Optimizing biopsy strategy for prostate cancer: Bayesian framework of network meta-analysis and hierarchical summary receiver operating characteristic model for diagnostic accuracy Rahman, Ilham Akbar Nusaly, Ilham Fauzan Syahrir, Syakri Nusaly, Harry Kasim, Firdaus Indian J Urol Review Article Overdiagnosis and overtreatment are well known problems in prostate cancer (PCa). The transrectal ultrasound (TRUS) Guided biopsy (GB) as a current gold standard investigation has a low positive detection rate resulting in unnecessary biopsies. The choice of optimal biopsy strategy needs to be defined. Therefore, we undertook a Bayesian network meta analysis (NMA) and Bayesian prediction in the hierarchical summary receiver operating characteristic (HSROC) model to present a method for optimizing biopsy strategy in PCa. Twenty eight relevant studies were retrieved through online databases of EMBASE, MEDLINE, and CENTRAL up to February 2020. Markov chain Monte Carlo simulation and Surface Under the Cumulative RAnking curve were used to calculate the rank probability using odds ratio with 95% credible interval. HSROC model was used to formulate the predicted true sensitivity and specificity of each biopsy strategy. Six different PCa biopsy strategies including transrectal ultrasound GB (TRUS GB), fusion GB (FUS GB), fusion + transrectal ultrasound GB (FUS + TRUS GB), magnetic resonance imaging GB (MRI GB), transperineal ultrasound GB (TPUS GB), and contrast enhanced ultrasound GB were analyzed in this study with a total of 7584 patients. These strategies were analyzed on five outcomes including detection rate of overall PCa, clinically significant PCa, insignificant PCa, complication rate, and HSROC. The rank probability showed that the overall PCa detection rate was higher in FUS + TRUS GB, MRI GB, and FUS GB. In terms of clinically significant PCa detection, FUS + TRUS GB and FUS GB had a relatively higher clinically significant PCa detection rate, whereas TRUS GB had a relatively lower rate for clinically significant PCa detection rate. MRI GB (91% and 81%) and FUS GB (82% and 83%) had the highest predicted true sensitivity and specificity, respectively, whereas TRUS GB (62% and 83%) had a lower predicted true sensitivity and specificity. MRI GB, FUS GB, and FUS + TRUS GB were associated with lower complication rate, whereas TPUS GB and TRUS GB were more associated with higher complication rate. This NMA and HSROC model highlight the important finding that FUS + TRUS GB, FUS GB, and MRI GB were superior compared with other strategies to avoid the overdiagnosis and overtreatment of PCa. FUS GB, MRI GB, and FUS + TRUS GB had lower complication rates. These results may assist in shared decision making between patients, carers, and their surgeons. Wolters Kluwer - Medknow 2021 2021-01-01 /pmc/articles/PMC8033239/ /pubmed/33850352 http://dx.doi.org/10.4103/iju.IJU_187_20 Text en Copyright: © 2021 Indian Journal of Urology https://creativecommons.org/licenses/by-nc-sa/4.0/This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms. |
spellingShingle | Review Article Rahman, Ilham Akbar Nusaly, Ilham Fauzan Syahrir, Syakri Nusaly, Harry Kasim, Firdaus Optimizing biopsy strategy for prostate cancer: Bayesian framework of network meta-analysis and hierarchical summary receiver operating characteristic model for diagnostic accuracy |
title | Optimizing biopsy strategy for prostate cancer: Bayesian framework of network meta-analysis and hierarchical summary receiver operating characteristic model for diagnostic accuracy |
title_full | Optimizing biopsy strategy for prostate cancer: Bayesian framework of network meta-analysis and hierarchical summary receiver operating characteristic model for diagnostic accuracy |
title_fullStr | Optimizing biopsy strategy for prostate cancer: Bayesian framework of network meta-analysis and hierarchical summary receiver operating characteristic model for diagnostic accuracy |
title_full_unstemmed | Optimizing biopsy strategy for prostate cancer: Bayesian framework of network meta-analysis and hierarchical summary receiver operating characteristic model for diagnostic accuracy |
title_short | Optimizing biopsy strategy for prostate cancer: Bayesian framework of network meta-analysis and hierarchical summary receiver operating characteristic model for diagnostic accuracy |
title_sort | optimizing biopsy strategy for prostate cancer: bayesian framework of network meta-analysis and hierarchical summary receiver operating characteristic model for diagnostic accuracy |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8033239/ https://www.ncbi.nlm.nih.gov/pubmed/33850352 http://dx.doi.org/10.4103/iju.IJU_187_20 |
work_keys_str_mv | AT rahmanilhamakbar optimizingbiopsystrategyforprostatecancerbayesianframeworkofnetworkmetaanalysisandhierarchicalsummaryreceiveroperatingcharacteristicmodelfordiagnosticaccuracy AT nusalyilhamfauzan optimizingbiopsystrategyforprostatecancerbayesianframeworkofnetworkmetaanalysisandhierarchicalsummaryreceiveroperatingcharacteristicmodelfordiagnosticaccuracy AT syahrirsyakri optimizingbiopsystrategyforprostatecancerbayesianframeworkofnetworkmetaanalysisandhierarchicalsummaryreceiveroperatingcharacteristicmodelfordiagnosticaccuracy AT nusalyharry optimizingbiopsystrategyforprostatecancerbayesianframeworkofnetworkmetaanalysisandhierarchicalsummaryreceiveroperatingcharacteristicmodelfordiagnosticaccuracy AT kasimfirdaus optimizingbiopsystrategyforprostatecancerbayesianframeworkofnetworkmetaanalysisandhierarchicalsummaryreceiveroperatingcharacteristicmodelfordiagnosticaccuracy |