Matched case-control studies: a review of reported statistical methodology

Daniel J Niven1, Luc R Berthiaume2, Gordon H Fick1, Kevin B Laupland11Department of Critical Care Medicine, Peter Lougheed Centre, Calgary, 2Department of Community Health Sciences, University of Calgary, Calgary, Alberta, CanadaBackground: Case-control studies are a common and efficient means of st...

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Main Authors: Niven DJ, Berthiaume LR, Fick GH, Laupl, KB
Format: Article
Language:English
Published: Dove Medical Press 2012-04-01
Series:Clinical Epidemiology
Online Access:http://www.dovepress.com/matched-case-control-studies-a-review-of-reported-statistical-methodol-a9783
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spelling doaj-5d35ddff5f6a43a8a0b1b3045cd4a5c32020-11-24T22:15:28ZengDove Medical PressClinical Epidemiology1179-13492012-04-012012default99110Matched case-control studies: a review of reported statistical methodologyNiven DJBerthiaume LRFick GHLauplKBDaniel J Niven1, Luc R Berthiaume2, Gordon H Fick1, Kevin B Laupland11Department of Critical Care Medicine, Peter Lougheed Centre, Calgary, 2Department of Community Health Sciences, University of Calgary, Calgary, Alberta, CanadaBackground: Case-control studies are a common and efficient means of studying rare diseases or illnesses with long latency periods. Matching of cases and controls is frequently employed to control the effects of known potential confounding variables. The analysis of matched data requires specific statistical methods.Methods: The objective of this study was to determine the proportion of published, peer reviewed matched case-control studies that used statistical methods appropriate for matched data. Using a comprehensive set of search criteria we identified 37 matched case-control studies for detailed analysis.Results: Among these 37 articles, only 16 studies were analyzed with proper statistical techniques (43%). Studies that were properly analyzed were more likely to have included case patients with cancer and cardiovascular disease compared to those that did not use proper statistics (10/16 or 63%, versus 5/21 or 24%, P = 0.02). They were also more likely to have matched multiple controls for each case (14/16 or 88%, versus 13/21 or 62%, P = 0.08). In addition, studies with properly analyzed data were more likely to have been published in a journal with an impact factor listed in the top 100 according to the Journal Citation Reports index (12/16 or 69%, versus 1/21 or 5%, P ≤ 0.0001).Conclusion: The findings of this study raise concern that the majority of matched case-control studies report results that are derived from improper statistical analyses. This may lead to errors in estimating the relationship between a disease and exposure, as well as the incorrect adaptation of emerging medical literature.Keywords: case-control, matched, dependent data, statisticshttp://www.dovepress.com/matched-case-control-studies-a-review-of-reported-statistical-methodol-a9783
collection DOAJ
language English
format Article
sources DOAJ
author Niven DJ
Berthiaume LR
Fick GH
Laupl
KB
spellingShingle Niven DJ
Berthiaume LR
Fick GH
Laupl
KB
Matched case-control studies: a review of reported statistical methodology
Clinical Epidemiology
author_facet Niven DJ
Berthiaume LR
Fick GH
Laupl
KB
author_sort Niven DJ
title Matched case-control studies: a review of reported statistical methodology
title_short Matched case-control studies: a review of reported statistical methodology
title_full Matched case-control studies: a review of reported statistical methodology
title_fullStr Matched case-control studies: a review of reported statistical methodology
title_full_unstemmed Matched case-control studies: a review of reported statistical methodology
title_sort matched case-control studies: a review of reported statistical methodology
publisher Dove Medical Press
series Clinical Epidemiology
issn 1179-1349
publishDate 2012-04-01
description Daniel J Niven1, Luc R Berthiaume2, Gordon H Fick1, Kevin B Laupland11Department of Critical Care Medicine, Peter Lougheed Centre, Calgary, 2Department of Community Health Sciences, University of Calgary, Calgary, Alberta, CanadaBackground: Case-control studies are a common and efficient means of studying rare diseases or illnesses with long latency periods. Matching of cases and controls is frequently employed to control the effects of known potential confounding variables. The analysis of matched data requires specific statistical methods.Methods: The objective of this study was to determine the proportion of published, peer reviewed matched case-control studies that used statistical methods appropriate for matched data. Using a comprehensive set of search criteria we identified 37 matched case-control studies for detailed analysis.Results: Among these 37 articles, only 16 studies were analyzed with proper statistical techniques (43%). Studies that were properly analyzed were more likely to have included case patients with cancer and cardiovascular disease compared to those that did not use proper statistics (10/16 or 63%, versus 5/21 or 24%, P = 0.02). They were also more likely to have matched multiple controls for each case (14/16 or 88%, versus 13/21 or 62%, P = 0.08). In addition, studies with properly analyzed data were more likely to have been published in a journal with an impact factor listed in the top 100 according to the Journal Citation Reports index (12/16 or 69%, versus 1/21 or 5%, P ≤ 0.0001).Conclusion: The findings of this study raise concern that the majority of matched case-control studies report results that are derived from improper statistical analyses. This may lead to errors in estimating the relationship between a disease and exposure, as well as the incorrect adaptation of emerging medical literature.Keywords: case-control, matched, dependent data, statistics
url http://www.dovepress.com/matched-case-control-studies-a-review-of-reported-statistical-methodol-a9783
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