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http://conacyt.repositorioinstitucional.mx/jspui/handle/1000/218| Detecting heterogeneity of intervention effects using analysis and meta-analysis of differences in variance between arms of a trial | |
| Nicola Wiles George Davey Smith Kate Tilling Jon Heron David Kessler Richard W Morris Julian PT Higgins Harriet L Mills | |
| Novel Coronavirus | |
| Acceso Abierto | |
| Atribución | |
| 10.1101/2020.03.07.20032516 | |
| Randomised controlled trials (RCTs) with continuous outcomes usually only examine mean differences in response between trial arms. If the intervention has heterogeneous effects (e.g. the effect of the intervention differs by individual characteristics), then outcome variances will also differ between arms. However, power of an individual trial to assess heterogeneity is lower than the power to detect the same size of main effect. The aim of this work was to describe and implement methods for examining heterogeneity of effects of interventions, in trials with individual patient data (IPD) and also in meta-analyses using summary data. Several methods for assessing differences in variance were applied using IPD from a single trial, and summary data from two meta-analyses. In the single trial there was agreement between methods, and the difference in variance was largely due to differences in depression at baseline. In two meta-analyses, most individual trials did not show strong evidence of a difference in variance between arms, with wide confidence intervals. However, both meta-analyses showed evidence of greater variance in the control arm, and in one example this was perhaps because mean outcome in the control arm was higher. Low power of individual trials to examine differences in variance can be overcome using meta-analysis. Evidence of differences in variance should be followed-up to identify potential effect modifiers and explore other possible causes such as varying compliance. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement KT, HM, GDS work in the Medical Research Council Integrative Epidemiology Unit at the University of Bristol which is supported by the Medical Research Council and the University of Bristol (MC_UU_00011/1 and MC_UU_00011/3). JH is supported by Medical Research Council and Alcohol Research UK (MR/L022206/1). JPTH is a member of the National Institute for Health Research Applied Research Collaboration West (ARC West) at University Hospitals Bristol NHS Foundation Trust. JPTH received funding from National Institute for Health Research Senior Investigator award NF-SI-0617-10145. This study was supported by the National Institute for Health Research Biomedical Research Centre at University Hospitals Bristol NHS Foundation Trust and the University of Bristol. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health and Social Care. ### Author Declarations All relevant ethical guidelines have been followed; any necessary IRB and/or ethics committee approvals have been obtained and details of the IRB/oversight body are included in the manuscript. Yes All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes The data for the single RCT example used in this paper are not available with this article and requests should go via David Kessler lead author of the original trial paper. Data for the meta-analysis examples are provided in the supplementary material. Code for each method in R is provided online at the link below. <https://github.com/harrietlmills/DetectingDifferencesInVariance> | |
| Cold Spring Harbor Laboratory Press | |
| 2020 | |
| Preimpreso | |
| https://www.medrxiv.org/content/10.1101/2020.03.07.20032516v1 | |
| Inglés | |
| VIRUS RESPIRATORIOS | |
| Aparece en las colecciones: | Artículos científicos |
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