Correlations between comorbidities in trials and the community: an individual-level participant data meta-analysis

Jamie Crowther, Elaine W Butterly, Laurie J Hannigan, Bruce Guthrie, Sarah H Wild, Frances S Mair, Peter Hanlon, Fergus J Chadwick*, David A McAllister*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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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.
Original languageEnglish
Article number26335565231213571
Number of pages9
JournalJournal of Multimorbidity and Comorbidity
Volume13
Early online date9 Nov 2023
DOIs
Publication statusE-pub ahead of print - 9 Nov 2023

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