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A methodology review on the incremental prognostic value of computed tomography biomarkers in addition to Framingham risk score in predicting cardiovascular disease: the use of association, discrimination and reclassification

BACKGROUND: Computed tomography (CT) biomarkers claim to improve cardiovascular risk stratification. This review focuses on significant differences in incremental measures between adequate and inadequate reporting practise. METHODS: Studies included were those that used Framingham Risk Score as a ba...

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Autores principales: Pang, Chun Lap, Pilkington, Nicola, Wei, Yinghui, Peters, Jaime, Roobottom, Carl, Hyde, Chris
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5822603/
https://www.ncbi.nlm.nih.gov/pubmed/29466951
http://dx.doi.org/10.1186/s12872-018-0777-5
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author Pang, Chun Lap
Pilkington, Nicola
Wei, Yinghui
Peters, Jaime
Roobottom, Carl
Hyde, Chris
author_facet Pang, Chun Lap
Pilkington, Nicola
Wei, Yinghui
Peters, Jaime
Roobottom, Carl
Hyde, Chris
author_sort Pang, Chun Lap
collection PubMed
description BACKGROUND: Computed tomography (CT) biomarkers claim to improve cardiovascular risk stratification. This review focuses on significant differences in incremental measures between adequate and inadequate reporting practise. METHODS: Studies included were those that used Framingham Risk Score as a baseline and described the incremental value of adding calcium score or CT coronary angiogram in predicting cardiovascular risk. Searches of MEDLINE, EMBASE, Web of Science and Cochrane Central were performed with no language restriction. RESULTS: Thirty five studies consisting of 206,663 patients (men = 118,114, 55.1%) were included. The baseline Framingham Risk Score included the 1998, 2002 and 2008 iterations. Selective reporting, inconsistent reference groupings and thresholds were found. Twelve studies (34.3%) had major and 23 (65.7%) had minor alterations and the respective Δ AUC were significantly different (p = 0.015). When the baseline model performed well, the Δ AUC was relatively lower with the addition of a CT biomarker (Spearman coefficient = − 0.46, p < 0.0001; n = 33; 76 pairs of data). Other factors that influenced AUC performance included exploration of data analysis, calibration, validation, multivariable and AUC documentation (all p < 0.05). Most studies (68.7%) that reported categorical NRI (n = 16; 46 pairs of data) subjectively drew strong conclusions along with other poor reporting practices. However, no significant difference in values of NRI was found between adequate and inadequate reporting. CONCLUSIONS: The widespread practice of poor reporting particularly association, discrimination, reclassification, calibration and validation undermines the claimed incremental value of CT biomarkers over the Framingham Risk Score alone. Inadequate reporting of discrimination inflates effect estimate, however, that is not necessarily the case for reclassification. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12872-018-0777-5) contains supplementary material, which is available to authorized users.
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spelling pubmed-58226032018-02-26 A methodology review on the incremental prognostic value of computed tomography biomarkers in addition to Framingham risk score in predicting cardiovascular disease: the use of association, discrimination and reclassification Pang, Chun Lap Pilkington, Nicola Wei, Yinghui Peters, Jaime Roobottom, Carl Hyde, Chris BMC Cardiovasc Disord Research Article BACKGROUND: Computed tomography (CT) biomarkers claim to improve cardiovascular risk stratification. This review focuses on significant differences in incremental measures between adequate and inadequate reporting practise. METHODS: Studies included were those that used Framingham Risk Score as a baseline and described the incremental value of adding calcium score or CT coronary angiogram in predicting cardiovascular risk. Searches of MEDLINE, EMBASE, Web of Science and Cochrane Central were performed with no language restriction. RESULTS: Thirty five studies consisting of 206,663 patients (men = 118,114, 55.1%) were included. The baseline Framingham Risk Score included the 1998, 2002 and 2008 iterations. Selective reporting, inconsistent reference groupings and thresholds were found. Twelve studies (34.3%) had major and 23 (65.7%) had minor alterations and the respective Δ AUC were significantly different (p = 0.015). When the baseline model performed well, the Δ AUC was relatively lower with the addition of a CT biomarker (Spearman coefficient = − 0.46, p < 0.0001; n = 33; 76 pairs of data). Other factors that influenced AUC performance included exploration of data analysis, calibration, validation, multivariable and AUC documentation (all p < 0.05). Most studies (68.7%) that reported categorical NRI (n = 16; 46 pairs of data) subjectively drew strong conclusions along with other poor reporting practices. However, no significant difference in values of NRI was found between adequate and inadequate reporting. CONCLUSIONS: The widespread practice of poor reporting particularly association, discrimination, reclassification, calibration and validation undermines the claimed incremental value of CT biomarkers over the Framingham Risk Score alone. Inadequate reporting of discrimination inflates effect estimate, however, that is not necessarily the case for reclassification. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12872-018-0777-5) contains supplementary material, which is available to authorized users. BioMed Central 2018-02-21 /pmc/articles/PMC5822603/ /pubmed/29466951 http://dx.doi.org/10.1186/s12872-018-0777-5 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Pang, Chun Lap
Pilkington, Nicola
Wei, Yinghui
Peters, Jaime
Roobottom, Carl
Hyde, Chris
A methodology review on the incremental prognostic value of computed tomography biomarkers in addition to Framingham risk score in predicting cardiovascular disease: the use of association, discrimination and reclassification
title A methodology review on the incremental prognostic value of computed tomography biomarkers in addition to Framingham risk score in predicting cardiovascular disease: the use of association, discrimination and reclassification
title_full A methodology review on the incremental prognostic value of computed tomography biomarkers in addition to Framingham risk score in predicting cardiovascular disease: the use of association, discrimination and reclassification
title_fullStr A methodology review on the incremental prognostic value of computed tomography biomarkers in addition to Framingham risk score in predicting cardiovascular disease: the use of association, discrimination and reclassification
title_full_unstemmed A methodology review on the incremental prognostic value of computed tomography biomarkers in addition to Framingham risk score in predicting cardiovascular disease: the use of association, discrimination and reclassification
title_short A methodology review on the incremental prognostic value of computed tomography biomarkers in addition to Framingham risk score in predicting cardiovascular disease: the use of association, discrimination and reclassification
title_sort methodology review on the incremental prognostic value of computed tomography biomarkers in addition to framingham risk score in predicting cardiovascular disease: the use of association, discrimination and reclassification
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5822603/
https://www.ncbi.nlm.nih.gov/pubmed/29466951
http://dx.doi.org/10.1186/s12872-018-0777-5
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