Participant characteristics and exclusion from trials: a meta-analysis of individual participant-level data from phase 3/4 industry-funded trials in chronic medical conditions

Jennifer S. Lees*, Jamie Crowther, Peter Hanlon, Elaine W Butterly, Sarah H Wild, Frances S Mair, Bruce Guthrie, Katie Gillies, Sofia Dias, Nicky J Welton, Srinivasa Vittal Katikireddi, David A McAllister

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Objectives
Trials often do not represent their target populations, threatening external validity. The aim was to assess whether age, sex, comorbidity count and/or race/ethnicity are associated with likelihood of screen failure (i.e., failure to be enrolled in the trial for any reason) among potential trial participants.

Design
Bayesian meta-analysis of individual participant-level data (IPD).

Setting
Industry-funded phase 3/4 trials in chronic medical conditions. Participants were identified as “enrolled” or “screen failure” using trial IPD.

Participants
Data were available for 52 trials involving 72,178 screened individuals of whom 24,733 (34%) failed screening.

Main outcome measures
For each trial, logistic regression models were constructed to assess likelihood of screen failure in people who had been invited to screening, regressed on age (per 10-year increment), sex (male versus female), comorbidity count (per one additional comorbidity) and race/ethnicity. Trial-level analyses were combined in Bayesian hierarchical models with pooling across condition.

Results
In age- and sex-adjusted models across all trials, neither age nor sex was associated with increased odds of screen failure, though weak associations were detected after additionally adjusting for comorbidity (age, per 10-year increment: odds ratio [OR] 1.02; 95% credibility interval [CI] 1.01 to 1.04 and male sex: OR 0.95; 95% CI 0.91 to 1.00). Comorbidity count was weakly associated with screen failure, but in an unexpected direction (OR 0.97 per additional comorbidity, 95% CI 0.94 to 1.00, adjusted for age and sex). Those who self-reported as Black were slightly more likely to fail screening (OR 1.04; 95% CI 0.99 to 1.09); an effect which persisted after adjustment for age, sex and comorbidity count (OR 1.05; 95% CI 0.98 to 1.12). The between-trial heterogeneity was generally low, but there was evidence of heterogeneity by sex across conditions (variation in odds ratios on log-scale of 0.01-0.13).

Conclusions
Though the conclusions are limited by uncertainty about the completeness or accuracy of data collection among non-randomised participants, we identified mostly weak associations between age, sex, comorbidity count and Black race/ethnicity and increased likelihood of screen failure. Proportionate increases in screening these underserved populations may improve representation in trials.

Trial registration
Relevant trials in chronic medical conditions were identified according to pre-specified criteria (PROSPERO CRD42018048202) then analysed according to availability of IPD.
Original languageEnglish
Article numbere000732
Number of pages11
JournalBMJ Medicine
Volume3
Issue number1
DOIs
Publication statusPublished - 3 May 2024

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