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Diagnostic performance of prediction models for extraprostatic extension in prostate cancer: a systematic review and meta-analysis

PURPOSE: In recent decades, diverse nomograms have been proposed to predict extraprostatic extension (EPE) in prostate cancer (PCa). We aimed to systematically evaluate the accuracy of MRI-inclusive nomograms and traditional clinical nomograms in predicting EPE in PCa. The purpose of this meta-analy...

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Autores principales: Zhu, MeiLin, Gao, JiaHao, Han, Fang, Yin, LongLin, Zhang, LuShun, Yang, Yong, Zhang, JiaWen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Vienna 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10444717/
https://www.ncbi.nlm.nih.gov/pubmed/37606802
http://dx.doi.org/10.1186/s13244-023-01486-7
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author Zhu, MeiLin
Gao, JiaHao
Han, Fang
Yin, LongLin
Zhang, LuShun
Yang, Yong
Zhang, JiaWen
author_facet Zhu, MeiLin
Gao, JiaHao
Han, Fang
Yin, LongLin
Zhang, LuShun
Yang, Yong
Zhang, JiaWen
author_sort Zhu, MeiLin
collection PubMed
description PURPOSE: In recent decades, diverse nomograms have been proposed to predict extraprostatic extension (EPE) in prostate cancer (PCa). We aimed to systematically evaluate the accuracy of MRI-inclusive nomograms and traditional clinical nomograms in predicting EPE in PCa. The purpose of this meta-analysis is to provide baseline summative and comparative estimates for future study designs. MATERIALS AND METHODS: The PubMed, Embase, and Cochrane databases were searched up to May 17, 2023, to identify studies on prediction nomograms for EPE of PCa. The risk of bias in studies was assessed by using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). Summary estimates of sensitivity and specificity were obtained with bivariate random-effects model. Heterogeneity was investigated through meta-regression and subgroup analysis. RESULTS: Forty-eight studies with a total of 57 contingency tables and 20,395 patients were included. No significant publication bias was observed for either the MRI-inclusive nomograms or clinical nomograms. For MRI-inclusive nomograms predicting EPE, the pooled AUC of validation cohorts was 0.80 (95% CI: 0.76, 0.83). For traditional clinical nomograms predicting EPE, the pooled AUCs of the Partin table and Memorial Sloan Kettering Cancer Center (MSKCC) nomogram were 0.72 (95% CI: 0.68, 0.76) and 0.79 (95% CI: 0.75, 0.82), respectively. CONCLUSION: Preoperative risk stratification is essential for PCa patients; both MRI-inclusive nomograms and traditional clinical nomograms had moderate diagnostic performance for predicting EPE in PCa. This study provides baseline comparative values for EPE prediction for future studies which is useful for evaluating preoperative risk stratification in PCa patients. CRITICAL RELEVANCE STATEMENT: This meta-analysis firstly evaluated the diagnostic performance of preoperative MRI-inclusive nomograms and clinical nomograms for predicting extraprostatic extension (EPE) in prostate cancer (PCa) (moderate AUCs: 0.72–0.80). We provide baseline estimates for EPE prediction, these findings will be useful in assessing preoperative risk stratification of PCa patients. KEY POINTS: • MRI-inclusive nomograms and traditional clinical nomograms had moderate AUCs (0.72–0.80) for predicting EPE. • MRI combined clinical nomogram may improve diagnostic accuracy of MRI alone for EPE prediction. • MSKCC nomogram had a higher specificity than Partin table for predicting EPE. • This meta-analysis provided baseline and comparative estimates of nomograms for EPE prediction for future studies. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13244-023-01486-7.
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spelling pubmed-104447172023-08-24 Diagnostic performance of prediction models for extraprostatic extension in prostate cancer: a systematic review and meta-analysis Zhu, MeiLin Gao, JiaHao Han, Fang Yin, LongLin Zhang, LuShun Yang, Yong Zhang, JiaWen Insights Imaging Critical Review PURPOSE: In recent decades, diverse nomograms have been proposed to predict extraprostatic extension (EPE) in prostate cancer (PCa). We aimed to systematically evaluate the accuracy of MRI-inclusive nomograms and traditional clinical nomograms in predicting EPE in PCa. The purpose of this meta-analysis is to provide baseline summative and comparative estimates for future study designs. MATERIALS AND METHODS: The PubMed, Embase, and Cochrane databases were searched up to May 17, 2023, to identify studies on prediction nomograms for EPE of PCa. The risk of bias in studies was assessed by using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). Summary estimates of sensitivity and specificity were obtained with bivariate random-effects model. Heterogeneity was investigated through meta-regression and subgroup analysis. RESULTS: Forty-eight studies with a total of 57 contingency tables and 20,395 patients were included. No significant publication bias was observed for either the MRI-inclusive nomograms or clinical nomograms. For MRI-inclusive nomograms predicting EPE, the pooled AUC of validation cohorts was 0.80 (95% CI: 0.76, 0.83). For traditional clinical nomograms predicting EPE, the pooled AUCs of the Partin table and Memorial Sloan Kettering Cancer Center (MSKCC) nomogram were 0.72 (95% CI: 0.68, 0.76) and 0.79 (95% CI: 0.75, 0.82), respectively. CONCLUSION: Preoperative risk stratification is essential for PCa patients; both MRI-inclusive nomograms and traditional clinical nomograms had moderate diagnostic performance for predicting EPE in PCa. This study provides baseline comparative values for EPE prediction for future studies which is useful for evaluating preoperative risk stratification in PCa patients. CRITICAL RELEVANCE STATEMENT: This meta-analysis firstly evaluated the diagnostic performance of preoperative MRI-inclusive nomograms and clinical nomograms for predicting extraprostatic extension (EPE) in prostate cancer (PCa) (moderate AUCs: 0.72–0.80). We provide baseline estimates for EPE prediction, these findings will be useful in assessing preoperative risk stratification of PCa patients. KEY POINTS: • MRI-inclusive nomograms and traditional clinical nomograms had moderate AUCs (0.72–0.80) for predicting EPE. • MRI combined clinical nomogram may improve diagnostic accuracy of MRI alone for EPE prediction. • MSKCC nomogram had a higher specificity than Partin table for predicting EPE. • This meta-analysis provided baseline and comparative estimates of nomograms for EPE prediction for future studies. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13244-023-01486-7. Springer Vienna 2023-08-22 /pmc/articles/PMC10444717/ /pubmed/37606802 http://dx.doi.org/10.1186/s13244-023-01486-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Critical Review
Zhu, MeiLin
Gao, JiaHao
Han, Fang
Yin, LongLin
Zhang, LuShun
Yang, Yong
Zhang, JiaWen
Diagnostic performance of prediction models for extraprostatic extension in prostate cancer: a systematic review and meta-analysis
title Diagnostic performance of prediction models for extraprostatic extension in prostate cancer: a systematic review and meta-analysis
title_full Diagnostic performance of prediction models for extraprostatic extension in prostate cancer: a systematic review and meta-analysis
title_fullStr Diagnostic performance of prediction models for extraprostatic extension in prostate cancer: a systematic review and meta-analysis
title_full_unstemmed Diagnostic performance of prediction models for extraprostatic extension in prostate cancer: a systematic review and meta-analysis
title_short Diagnostic performance of prediction models for extraprostatic extension in prostate cancer: a systematic review and meta-analysis
title_sort diagnostic performance of prediction models for extraprostatic extension in prostate cancer: a systematic review and meta-analysis
topic Critical Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10444717/
https://www.ncbi.nlm.nih.gov/pubmed/37606802
http://dx.doi.org/10.1186/s13244-023-01486-7
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