부산대학교 도서관

BACKGROUND AND PURPOSE—: 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 trialʼs age, baseline severity, and time to treatment inclusion criteria. METHODS—: 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. RESULTS—: 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. CONCLUSIONS—: 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.