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Using Epidemiological Data to Inform Clinical Trial Feasibility Assessments: A Case Study.
Robert J Stanton1, David J Robinson1, Yasmin N Aziz1
1Departments of Neurology and Rehabilitation Medicine (R.J.S., D.J.R., Y.N.A., P.K., J.P.B., M.L.F., D.W., S.F., B.M.K.), University of Cincinnati College of Medicine, OH.
Using epidemiological data for prospective feasibility assessments improved clinical trial eligibility and completion rates. This collaborative approach enhances patient recruitment for stroke research.
Area of Science:
- Neurology
- Clinical Trials
- Epidemiology
Background:
- Clinical trial completion rates are suboptimal, with nearly half of trials facing delays or incompletion.
- The National Institutes of Health StrokeNet initiated feasibility assessments in 2014, collaborating with epidemiologists from the Greater Cincinnati/Northern Kentucky Stroke Study (GCNKSS).
- This initiative aimed to improve trial enrollment and success rates through prospective feasibility analyses using epidemiological data.
Purpose of the Study:
- To describe the process of prospective feasibility analyses for clinical trials.
- To evaluate the impact of epidemiological data and collaborative assessments on trial eligibility and completion.
- To enhance patient recruitment and increase the likelihood of successful clinical trial outcomes.
Main Methods:
- Collaboration between DEFUSE 3 (Endovascular Therapy Following Imaging Evaluation for Ischemic Stroke 3) trialists, National Institutes of Health StrokeNet, and GCNKSS stroke epidemiologists.
- Evaluation of initial inclusion/exclusion criteria for the DEFUSE 3 study.
- Assessment of the stroke population's eligibility based on proposed criteria modifications and statistical analysis using the Wilcoxon rank-sum statistic.
Main Results:
- Initial epidemiological analysis predicted 2.4% of acute stroke patients would be eligible for the DEFUSE 3 trial.
- Modifying four key exclusion criteria increased predicted eligibility to 4% of the stroke population.
- At trial conclusion, 57% of enrolled patients met only the modified criteria, and the trial was stopped early due to demonstrated efficacy.
Conclusions:
- Objective assessment of trial criteria using population-based resources and collaborative input from epidemiologists can significantly improve recruitment.
- This iterative process increases the probability of successful clinical trial completion.
- The findings highlight the value of integrating epidemiological data into trial design for enhanced feasibility and outcomes.
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