Effect of age, sex, and morbidity count on trial attrition: meta-analysis of individual participant level data from phase 3/4 industry funded clinical trials

Abstract

Objectives: To estimate the association between individual participant characteristics and attrition from randomised controlled trials.

Design: Meta-analysis of individual participant level data (IPD).

Data sources: Clinical trial repositories (Clinical Study Data Request and Yale University Open Data Access).

Eligibility criteria for selecting studies: Eligible phase 3 or 4 trials identified according to prespecified criteria (PROSPERO CRD42018048202).

Main outcome measures: Association between comorbidity count (identified using medical history or concomitant drug treatment data) and trial attrition (failure for any reason to complete the final trial visit), estimated in logistic regression models and adjusted for age and sex. Estimates were meta-analysed in bayesian linear models, with partial pooling across index conditions and drug classes.

Results: In 92 trials across 20 index conditions and 17 drug classes, the mean comorbidity count ranged from 0.3 to 2.7. Neither age nor sex was clearly associated with attrition (odds ratio 1.04, 95% credible interval 0.98 to 1.11; and 0.99, 0.93 to 1.05, respectively). However, comorbidity count was associated with trial attrition (odds ratio per additional comorbidity 1.11, 95% credible interval 1.07 to 1.14). No evidence of non-linearity (assessed via a second order polynomial) was seen in the association between comorbidity count and trial attrition, with minimal variation across drug classes and index conditions. At a trial level, an increase in participant comorbidity count has a minor impact on attrition: for a notional trial with high level of attrition in individuals without comorbidity, doubling the mean comorbidity count from 1 to 2 translates to an increase in trial attrition from 29% to 31%.

Conclusions: Increased comorbidity count, irrespective of age and sex, is associated with a modest increased odds of participant attrition. The benefit of increased generalisability of including participants with multimorbidity seems likely to outweigh the disadvantages of increased attrition.

Keywords: clinical trial; internal medicine; medicine; research design.

Figure 1

Overview of use of models for meta-analysis output. Shaded areas=analyses conducted within Clinical Study Data Request (CSDR) and Yale University Open Data Access (YODA) repository safe havens. Variance matrices of the effect estimates were exported to allow maximum flexibility in subsequent meta-analyses, if required. IPD=individual participant level data

Figure 2

Plots of the proportion of attritions for 593 clinical trials registered on ClinicalTrials.gov (CTG) and 92 trials with individual participant level data (IPD) available. Violin plots represent the summary estimates for CTG and IPD trials. Horizontal bars=median and interquartile ranges; dots=proportion of attrition for individual trials

Figure 3

Forest plots showing mean odds ratio of atrial attrition (with 50%, 80%, and 95% credible intervals) by index condition and overall result from pooled model, according to age, sex, and comorbidity count at baseline assessment. Vertical line=reference line (ie, no effect, odds ratio of 1); 50% and 80% credible intervals are shown to indicate that the probability of a given estimate is not uniform across the 95% interval

Figure 4

Forest plots showing mean odds ratio of atrial attrition (with 50%, 80%, and 95% credible intervals) by Anatomical Therapeutic Chemical (ATC) drug class and overall result from pooled model, according to age, sex, and comorbidity count at baseline assessment. Vertical line=reference line (ie, no effect, odds ratio of 1); 50% and 80% credible intervals are shown to indicate that the probability of a given estimate is not uniform across the 95% interval