Assessing trial representativeness using serious adverse events: an observational analysis using aggregate and individual-level data from clinical trials and routine healthcare data - PubMed (original) (raw)
Observational Study
Assessing trial representativeness using serious adverse events: an observational analysis using aggregate and individual-level data from clinical trials and routine healthcare data
Peter Hanlon et al. BMC Med. 2022.
Abstract
Background: The applicability of randomised controlled trials of pharmacological agents to older people with frailty/multimorbidity is often uncertain, due to concerns that trials are not representative. However, assessing trial representativeness is challenging and complex. We explore an approach assessing trial representativeness by comparing rates of trial serious adverse events (SAE) to rates of hospitalisation/death in routine care.
Methods: This was an observational analysis of individual (125 trials, n=122,069) and aggregate-level drug trial data (483 trials, n=636,267) for 21 index conditions compared to population-based routine healthcare data (routine care). Trials were identified from ClinicalTrials.gov . Routine care comparison from linked primary care and hospital data from Wales, UK (n=2.3M). Our outcome of interest was SAEs (routinely reported in trials). In routine care, SAEs were based on hospitalisations and deaths (which are SAEs by definition). We compared trial SAEs in trials to expected SAEs based on age/sex standardised routine care populations with the same index condition. Using IPD, we assessed the relationship between multimorbidity count and SAEs in both trials and routine care and assessed the impact on the observed/expected SAE ratio additionally accounting for multimorbidity.
Results: For 12/21 index conditions, the pooled observed/expected SAE ratio was <1, indicating fewer SAEs in trial participants than in routine care. A further 6/21 had point estimates <1 but the 95% CI included the null. The median pooled estimate of observed/expected SAE ratio was 0.60 (95% CI 0.55-0.64; COPD) and the interquartile range was 0.44 (0.34-0.55; Parkinson's disease) to 0.87 (0.58-1.29; inflammatory bowel disease). Higher multimorbidity count was associated with SAEs across all index conditions in both routine care and trials. For most trials, the observed/expected SAE ratio moved closer to 1 after additionally accounting for multimorbidity count, but it nonetheless remained below 1 for most.
Conclusions: Trial participants experience fewer SAEs than expected based on age/sex/condition hospitalisation and death rates in routine care, confirming the predicted lack of representativeness. This difference is only partially explained by differences in multimorbidity. Assessing observed/expected SAE may help assess the applicability of trial findings to older populations in whom multimorbidity and frailty are common.
Keywords: Chronic disease; Epidemiology; Multimorbidity; Randomised controlled trials; Serious adverse events.
© 2022. The Author(s).
Conflict of interest statement
The authors declare that they have no competing interests.
Figures
Fig. 1
Identification and inclusion of eligible trials
Fig. 2
This figure displayed the pooled observed/expected SAE ratio for each of the index conditions. It also shows the number of people in the routine care cohort with each index condition, the number of trials with aggregate data and the total number of SAEs
Fig. 3
This figure shows the ratio of observed/expected serious adverse event rates in aggregate data trials. Four selected index conditions with the largest number of eligible trials are displayed here, with the remaining conditions displayed in the supplementary appendix. The point-estimate and 95% confidence interval for the ratio for each trial is shown by the coloured points and bars, respectively. Different drug classes are separated by colour (full key displayed in supplementary appendix). The pooled ratio and 95% confidence intervals meta-analysed across all trials within each index condition is shown by the black point and line at the bottom of each plot. Findings are based on analysis of aggregate trial data from
ClinicalTrials.gov
(index condition, trial drug, age, sex, SAEs and follow-up) for the observed rate and individual patient data from SAIL was used to calculate the expected rate
Fig. 4
This figure shows the relationship between multimorbidity count and SAE rate in men and women meta-analysed for trials of each index condition (blue) and for each index condition in routine care (red). Shaded areas indicate 95% confidence intervals for the meta-analysis and routine care estimates
Fig. 5
Ratio of observed/expected SAE based on age and sex (square points with solid lines indicating 95% confidence interval), and based on age, sex and multimorbidity count (triangle points with broken lines indicating 95% confidence intervals) for six selected index conditions. Each pair of points correspond to a single trial. Ratios for all other conditions are shown in the supplementary appendix
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