Did you know that insufficient enrollment is the leading cause for clinical trials being halted? One recent analysis of clinical trials estimated that 55% of all trials which terminate early was due to poor enrollment.[1] Further illustration of this was given by the Tufts Center for the Study of Drug Development[2] which found that 37% of sites under enroll and 11% of sites fail to enroll a single subject! Given these challenges, study sponsors rightly embrace those sites which are high performing as they give a study the best opportunity to meet its enrollment targets. However, is it possible for there to be overreliance on these high enrolling sites? Unfortunately, the answer is yes.
When designing a clinical trial, statisticians will work to ensure that if a clinical benefit is identified it can be attributed to the treatment under investigation and not to a confounding factor (i.e., a different variable that could be the cause for the observed clinical benefit). When studies rely too heavily on a subset of sites for enrollment, this introduces the possibility of the effect of treatment & study site becoming confounded, meaning we can no longer tell what is causing the clinical benefit which is problematic. Inevitably, the question then arises, “Should I have an enrollment cap for sites on my study?” Similarly, “How many subjects is too many for a site?”
As in most situations, the answer to these questions is heavily dependent on the context (e.g., how many sites are involved in the trial, how many subjects are planned for the trial, how challenging is it to find subjects, etc.). In a perfect world, each site would contribute roughly the same number of subjects. For example, a 100-subject study with 20 sites would mean 5 subjects enrolled/site. Realizing that this is unlikely to occur, a common rule of thumb is to take the “optimal” (uniform) number of subjects/site and assume 3-5x this value would be the maximum number of subjects allowed for a site.
Of course, there may be situations where following this sort of rule isn’t feasible. Consultation with a statistician can help with providing advice as to your study’s site enrollment cap and/or analytical strategies to determine if there are site effects being observed. As you prepare to design your next study and begin wrestling with these questions, contact us to speak with one of our statistical experts to help navigate them!
[1] Pharmaceutical Technology Enrolment Issues are the Top Factor in Clinical Trial Terminations. 2018. Dec 05
[2] Tufts CSDD Impact Report. 2013. January/February. Volume 15 Number 1.
Scott Mollan, Associate Director, Biostatistics, has over 17 years of experience in clinical and non-clinical statistics across the CRO & pharmaceutical industry. Having led studies of all phases (pilot, pivotal, post-market, phases I-IV) and assisting clients during both the pre-submission phase and FDA approval via the NDA/PMA process (2 NDAs/10 PMAs), he has a wealth of experience to draw upon to support clients. Armed with graduate degrees in business and statistics, Mr. Mollan has been able to leverage his understanding of the clinical trial process via a diverse range of indications to publish on the medical device trial process, lung cancer diagnostics, and women’s health while similarly offering industry presentations on missing data analysis strategies and the use of adaptive trial designs within medical devices studies.