Interactions between stroke data banks and clinical trials.
The number of clinical trials to evaluate new therapies for stroke treatment and prevention is growing rapidly. Although stroke data banks cannot answer treatment efficacy questions, they can have powerful interactions with the design and conduct of clinical trials. Through data banks one can generate hypotheses regarding treatment, estimate the frequency of outcome events, calculate sample size, determine stratification factors that may or may not be needed in a clinical trial, establish inclusion and exclusion criteria and decide on the elements to include in the data collection forms. Using a data bank one can estimate the number of patients that may be screened, eligible, refused, and enrolled in a clinical trial with given inclusion and exclusion criteria. Data banks are helpful for surveillance of all eligible subjects and calculating the proportion of the total cases who were randomized. With the more widespread analyses of stroke data banks we can design focused clinical trials and reach some definitive conclusions regarding the future treatment of stroke.
Sacco
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Department of Neurology and Public Health (Epidemiology), Sergievsky Center, Columbia-Presbyterian Medical Center, New York, N.Y.
D015982:Bias; D002561:Cerebrovascular Disorders / Q000175:diagnosis / Q000453:epidemiology / Q000534:rehabilitation*; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D016208:Databases, Factual / Q000706:statistics & numerical data*; D006801:Humans; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data*; D012107:Research Design; D016896:Treatment Outcome