Optimizing stroke clinical trial design: estimating the proportion of eligible patients.

Abstract

Clinical trial planning and site selection require an accurate estimate of the number of eligible patients at each site. In this study, we developed a tool to calculate the proportion of patients who would meet a specific trial's age, baseline severity, and time to treatment inclusion criteria. From a sample of 1322 consecutive patients with acute ischemic cerebrovascular syndromes, we developed regression curves relating the proportion of patients within each range of the 3 variables. We used half the patients to develop the model and the other half to validate it by comparing predicted vs actual proportions who met the criteria for 4 current stroke trials. The predicted proportion of patients meeting inclusion criteria ranged from 6% to 28% among the different trials. The proportion of trial-eligible patients predicted from the first half of the data were within 0.4% to 1.4% of the actual proportion of eligible patients. This proportion increased logarithmically with National Institutes of Health Stroke Scale score and time from onset; lowering the baseline limits of the National Institutes of Health Stroke Scale score and extending the treatment window would have the greatest impact on the proportion of patients eligible for a stroke trial. This model helps estimate the proportion of stroke patients eligible for a study based on different upper and lower limits for age, stroke severity, and time to treatment, and it may be a useful tool in clinical trial planning.