Abstract
BackgroundSubject recruitment for medical research is challenging. Slow patient accrual leads to increased costs and delays in treatment advances. Researchers need reliable tools to manage and predict the accrual rate. The previously developed Bayesian method integrates researchers’ experience on former trials and data from an ongoing study, providing a reliable prediction of accrual rate for clinical studies.MethodsIn this paper, we present a user-friendly graphical user interface program developed in R. A closed-form solution for the total subjects that can be recruited within a fixed time is derived. We also present a built-in Android system using Java for web browsers and mobile devices.ResultsUsing the accrual software, we re-evaluated the Veteran Affairs Cooperative Studies Program 558— ROBOTICS study. The application of the software in monitoring and management of recruitment is illustrated for different stages of the trial.ConclusionsThis developed accrual software provides a more convenient platform for estimation and prediction of the accrual process.Electronic supplementary materialThe online version of this article (doi:10.1186/s13063-016-1457-3) contains supplementary material, which is available to authorized users.
Highlights
Subject recruitment for medical research is challenging
Here we provide specific examples to illustrate how the accrual software can be used in the evaluation or management of a clinical trial
Initial planning of the study The target total sample size for ROBOTICS was 158, to achieve 90 % power of the protocol-defined effect size and variance assumptions estimated from the literature
Summary
Subject recruitment for medical research is challenging. Slow patient accrual leads to increased costs and delays in treatment advances. Researchers need reliable tools to manage and predict the accrual rate. The previously developed Bayesian method integrates researchers’ experience on former trials and data from an ongoing study, providing a reliable prediction of accrual rate for clinical studies. Subject recruitment is critical and often very challenging in clinical research studies. Investigators frequently overestimate the pool of available subjects and underestimate the time needed to achieve the proposed sample size for their studies. This is known as Lasagna’s law [1] and as Muench’s third law [2]. Extending the recruitment time frame leads to increased costs, while a delay in study completion can lower the scientific impact or relevance.
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