Crowther, J. , Butterly, E. W., Hannigan, L. J. , Guthrie, B., Wild, S., Mair, F. S. , Hanlon, P. , Chadwick, F. J. and McAllister, D. (2023) Correlations between comorbidities in trials and the community: an individual-level participant data meta-analysis. Journal of Multimorbidity and Comorbidity, 13, pp. 1-9. (doi: 10.1177/26335565231213571) (PMID:37953975) (PMCID:PMC10637135)
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Abstract
Background: People with comorbidities are under-represented in randomised controlled trials, and it is unknown whether patterns of comorbidity are similar in trials and the community. Methods: Individual-level participant data were obtained for 83 clinical trials (54,688 participants) for 16 index conditions from two trial repositories: Yale University Open Data Access (YODA) and the Centre for Global Clinical Research Data (Vivli). Community data (860,177 individuals) were extracted from the Secure Anonymised Information Linkage (SAIL) databank for the same index conditions. Comorbidities were defined using concomitant medications. For each index condition, we estimated correlations between comorbidities separately in trials and community data. For the six commonest comorbidities we estimated all pairwise correlations using Bayesian multivariate probit models, conditioning on age and sex. Correlation estimates from trials with the same index condition were combined into a single estimate. We then compared the trial and community estimates for each index condition. Results: Despite a higher prevalence of comorbidities in the community than in trials, the correlations between comorbidities were mostly similar in both settings. On comparing correlations between the community and trials, 21% of correlations were stronger in the community, 10% were stronger in the trials and 68% were similar in both. In the community, 5% of correlations were negative, 21% were null, 56% were weakly positive and 18% were strongly positive. Equivalent results for the trials were 11%, 33%, 45% and 10% respectively. Conclusions: Comorbidity correlations are generally similar in both the trials and community, providing some evidence for the reporting of comorbidity-specific findings from clinical trials.
| Item Type: | Articles |
|---|---|
| Additional Information: | David McAllister was funded to complete this work via an Intermediate Clinical Fellowship and Beit Fellowship from the Wellcome Trust, who also supported other costs related to this project such as data access costs and database licences (“Treatment effectiveness in multimorbidity: Combining efficacy estimates from clinical trials with the natural history obtained from large routine healthcare databases to determine net overall treatment Benefits.” - 201492/Z/16/Z). Peter Hanlon is funded through a Clinical Research Training Fellowship from the Medical Research Council (Grant reference: MR/S021949/1). |
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | McAllister, Professor David and Chadwick, Mr Fergus and Hanlon, Dr Peter and Butterly, Dr Elaine and Hannigan, Dr Laurie and Mair, Professor Frances and Crowther, Mr Jamie |
| Authors: | Crowther, J., Butterly, E. W., Hannigan, L. J., Guthrie, B., Wild, S., Mair, F. S., Hanlon, P., Chadwick, F. J., and McAllister, D. |
| College/School: | College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > General Practice and Primary Care College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Health Economics and Health Technology Assessment |
| Journal Name: | Journal of Multimorbidity and Comorbidity |
| Publisher: | SAGE Publications |
| ISSN: | 2633-5565 |
| ISSN (Online): | 2633-5565 |
| Published Online: | 09 November 2023 |
| Copyright Holders: | Copyright © The Author(s) 2023 |
| First Published: | First published in Journal of Multimorbidity and Comorbidity 13:1-9 |
| Publisher Policy: | Reproduced under a Creative Commons license |
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