Health & Medical Heart Diseases

Early Termination of Cardiovascular Trials Due to Recruitment

Early Termination of Cardiovascular Trials Due to Recruitment

Abstract and Introduction

Abstract


Background Early termination of clinical trials due to low recruitment represents an understudied challenge for clinical research. We aimed to describe characteristics of cardiovascular trials terminated because of low recruitment and identify the major predictors of such early termination.

Methods We reviewed all cardiovascular clinical trials (7,042 studies) registered in ClinicalTrials.gov from February 29, 2000, to January 17, 2013, and assessed information about trials that were completed and those that were terminated early. Logistic regression models were developed to identify independent predictors of early termination due to low recruitment.

Results Our search strategy identified 6,279 cardiovascular clinical trials, of which 684 (10.9%) were terminated prematurely. Of these halted trials, the main reason for termination was lower than expected recruitment (278 trials; 53.6%). When comparing trials that terminated early because of low recruitment with those that were completed, we found that studies funded by the National Institutes of Health or other US federal agencies (odds ratio [OR] 0.35, 95% confidence interval [CI] 0.14–0.89), studies of behavior/diet intervention (OR 0.35, 95% CI 0.19–0.65), and single-arm design studies (OR 0.57, 95% CI 0.42–0.78) were associated with a lower risk of early termination. University/hospital-funded (OR 1.52, 95% CI 1.10–2.10) and mixed-source–funded studies (OR 2.14, 95% CI 1.52–3.01) were associated with a higher likelihood of early termination due to lower than expected recruitment rates.

Conclusions Low recruitment represents the main cause of early termination of cardiovascular clinical trials. Funding source, type of intervention, and study design are factors associated with early termination due to low recruitment and might be good targets for improving enrollment into cardiovascular clinical trials.

Introduction


Cardiovascular disease is the primary cause of death and disability globally. High-quality evidence has established that interventions which reduce major cardiovascular events typically have only moderate effects on outcomes; therefore, large numbers of participants are needed in clinical trials to adequately control for random error. As clinical trials in cardiology become more complex and expansive, with increasingly large cohorts to allow for accurate assessment of the treatment effect, a common challenge for such trials is lower than expected recruitment rates, which can culminate in early termination of trials because of failure to reach the initially planned sample size within the expected timeframe. Currently, it is unknown what proportion of cardiovascular trials are halted early due to low recruitment. Moreover, the reasons why certain trials recruit well, but others do not are not fully understood.

The publicly available ClinicalTrials.gov registry was launched more than a decade ago and has emerged as a key element of many public health policy initiatives aimed at improving clinical research. ClinicalTrials.gov represents the most comprehensive source for information about ongoing and completed trials within and outside the United States. Currently, approximately 10% of trials registered in ClinicalTrials.gov are cardiovascular studies. A growing number of researchers and authors of systematic reviews use ClinicalTrials.gov data to generate empirical evidence regarding clinical trials methodology, results, and publication rates. Analysis of the ClinicalTrials.gov database offers a unique opportunity to study a cohort of contemporary cardiovascular trials from registration to completion. Our study aims were to use ClinicalTrials.gov to (1) determine how frequently cardiovascular clinical trials terminate early, both overall and specifically because of lower than expected recruitment; (2) describe the characteristics of trials terminated due to low recruitment; and (3) identify predictors for early termination because of low recruitment.

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