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Individual patient data meta-analysis of diagnostic and prognostic studies in obstetrics, gynaecology and reproductive medicine
BACKGROUND: In clinical practice a diagnosis is based on a combination of clinical history, physical examination and additional diagnostic tests. At present, studies on diagnostic research often report the accuracy of tests without taking into account the information already known from history and e...
Autores principales: | , , , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2667527/ https://www.ncbi.nlm.nih.gov/pubmed/19327146 http://dx.doi.org/10.1186/1471-2288-9-22 |
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author | Broeze, Kimiko A Opmeer, Brent C Bachmann, Lucas M Broekmans, Frank J Bossuyt, Patrick MM Coppus, Sjors FPJ Johnson, Neil P Khan, Khalid S ter Riet, Gerben van der Veen, Fulco van Wely, Madelon Mol, Ben WJ |
author_facet | Broeze, Kimiko A Opmeer, Brent C Bachmann, Lucas M Broekmans, Frank J Bossuyt, Patrick MM Coppus, Sjors FPJ Johnson, Neil P Khan, Khalid S ter Riet, Gerben van der Veen, Fulco van Wely, Madelon Mol, Ben WJ |
author_sort | Broeze, Kimiko A |
collection | PubMed |
description | BACKGROUND: In clinical practice a diagnosis is based on a combination of clinical history, physical examination and additional diagnostic tests. At present, studies on diagnostic research often report the accuracy of tests without taking into account the information already known from history and examination. Due to this lack of information, together with variations in design and quality of studies, conventional meta-analyses based on these studies will not show the accuracy of the tests in real practice. By using individual patient data (IPD) to perform meta-analyses, the accuracy of tests can be assessed in relation to other patient characteristics and allows the development or evaluation of diagnostic algorithms for individual patients. In this study we will examine these potential benefits in four clinical diagnostic problems in the field of gynaecology, obstetrics and reproductive medicine. METHODS/DESIGN: Based on earlier systematic reviews for each of the four clinical problems, studies are considered for inclusion. The first authors of the included studies will be invited to participate and share their original data. After assessment of validity and completeness the acquired datasets are merged. Based on these data, a series of analyses will be performed, including a systematic comparison of the results of the IPD meta-analysis with those of a conventional meta-analysis, development of multivariable models for clinical history alone and for the combination of history, physical examination and relevant diagnostic tests and development of clinical prediction rules for the individual patients. These will be made accessible for clinicians. DISCUSSION: The use of IPD meta-analysis will allow evaluating accuracy of diagnostic tests in relation to other relevant information. Ultimately, this could increase the efficiency of the diagnostic work-up, e.g. by reducing the need for invasive tests and/or improving the accuracy of the diagnostic workup. This study will assess whether these benefits of IPD meta-analysis over conventional meta-analysis can be exploited and will provide a framework for future IPD meta-analyses in diagnostic and prognostic research. |
format | Text |
id | pubmed-2667527 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-26675272009-04-10 Individual patient data meta-analysis of diagnostic and prognostic studies in obstetrics, gynaecology and reproductive medicine Broeze, Kimiko A Opmeer, Brent C Bachmann, Lucas M Broekmans, Frank J Bossuyt, Patrick MM Coppus, Sjors FPJ Johnson, Neil P Khan, Khalid S ter Riet, Gerben van der Veen, Fulco van Wely, Madelon Mol, Ben WJ BMC Med Res Methodol Study Protocol BACKGROUND: In clinical practice a diagnosis is based on a combination of clinical history, physical examination and additional diagnostic tests. At present, studies on diagnostic research often report the accuracy of tests without taking into account the information already known from history and examination. Due to this lack of information, together with variations in design and quality of studies, conventional meta-analyses based on these studies will not show the accuracy of the tests in real practice. By using individual patient data (IPD) to perform meta-analyses, the accuracy of tests can be assessed in relation to other patient characteristics and allows the development or evaluation of diagnostic algorithms for individual patients. In this study we will examine these potential benefits in four clinical diagnostic problems in the field of gynaecology, obstetrics and reproductive medicine. METHODS/DESIGN: Based on earlier systematic reviews for each of the four clinical problems, studies are considered for inclusion. The first authors of the included studies will be invited to participate and share their original data. After assessment of validity and completeness the acquired datasets are merged. Based on these data, a series of analyses will be performed, including a systematic comparison of the results of the IPD meta-analysis with those of a conventional meta-analysis, development of multivariable models for clinical history alone and for the combination of history, physical examination and relevant diagnostic tests and development of clinical prediction rules for the individual patients. These will be made accessible for clinicians. DISCUSSION: The use of IPD meta-analysis will allow evaluating accuracy of diagnostic tests in relation to other relevant information. Ultimately, this could increase the efficiency of the diagnostic work-up, e.g. by reducing the need for invasive tests and/or improving the accuracy of the diagnostic workup. This study will assess whether these benefits of IPD meta-analysis over conventional meta-analysis can be exploited and will provide a framework for future IPD meta-analyses in diagnostic and prognostic research. BioMed Central 2009-03-27 /pmc/articles/PMC2667527/ /pubmed/19327146 http://dx.doi.org/10.1186/1471-2288-9-22 Text en Copyright ©2009 Broeze et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Study Protocol Broeze, Kimiko A Opmeer, Brent C Bachmann, Lucas M Broekmans, Frank J Bossuyt, Patrick MM Coppus, Sjors FPJ Johnson, Neil P Khan, Khalid S ter Riet, Gerben van der Veen, Fulco van Wely, Madelon Mol, Ben WJ Individual patient data meta-analysis of diagnostic and prognostic studies in obstetrics, gynaecology and reproductive medicine |
title | Individual patient data meta-analysis of diagnostic and prognostic studies in obstetrics, gynaecology and reproductive medicine |
title_full | Individual patient data meta-analysis of diagnostic and prognostic studies in obstetrics, gynaecology and reproductive medicine |
title_fullStr | Individual patient data meta-analysis of diagnostic and prognostic studies in obstetrics, gynaecology and reproductive medicine |
title_full_unstemmed | Individual patient data meta-analysis of diagnostic and prognostic studies in obstetrics, gynaecology and reproductive medicine |
title_short | Individual patient data meta-analysis of diagnostic and prognostic studies in obstetrics, gynaecology and reproductive medicine |
title_sort | individual patient data meta-analysis of diagnostic and prognostic studies in obstetrics, gynaecology and reproductive medicine |
topic | Study Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2667527/ https://www.ncbi.nlm.nih.gov/pubmed/19327146 http://dx.doi.org/10.1186/1471-2288-9-22 |
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