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.

SUBMITTER: Taylor A 

PROVIDER: S-EPMC2974263 | biostudies-other | 2010 Oct

REPOSITORIES: biostudies-other