• Clin Trials · Jan 2008

    Methods and processes for the reanalysis of the NINDS tissue plasminogen activator for acute ischemic stroke treatment trial.

    • Vicki Hertzberg, Timothy Ingall, William O'Fallon, Kjell Asplund, Lewis Goldfrank, Thomas Louis, and Teresa Christianson.
    • Department of Biostatistics, Emory University. vhertzb@sph.emory.edu
    • Clin Trials. 2008 Jan 1;5(4):308-15.

    BackgroundTreatment group imbalances in baseline stroke severity in the NINDS intravenous t-PA for acute stroke treatment trial led to controversy regarding the efficacy of tissue plasminogen activator (t-PA) in the treatment of acute ischemic stroke.PurposeDescribe the steps used to independently re-evaluate this trial.MethodsNIH appointed an independent multidisciplinary committee that gained access to the original data. We undertook analyses of t-PA efficacy accounting for this imbalance, as well as analyses to identify subgroups that experienced additional harm or benefit from t-PA. Analyses of time from stroke onset to treatment (OTT), blood pressure, and intracerebral hemorrhage are given as illustrations.ResultsDespite subgroup imbalances in baseline stroke severity, when t-PA was administered to acute ischemic stroke patients according to study protocol, there was a statistically significant and clinically important benefit of t-PA treatment resulting in a higher likelihood of having a favorable clinical outcome at 3 months. Moreover, we were unable to identify subgroups of patients between which t-PA treatment effect differed, albeit these analyses had low power. These data failed to support the NINDS investigators' conclusion that effect of t-PA therapy diminished with increasing values of OTT within the protocol-specified 3 h time limit. In addition, the blood pressure measurements were highly variable and inconsistently determined so as to be too unreliable for inclusion in analysis.ConclusionWith new NIH requirements for data-sharing, the frequency of re-analysis of clinical trial data may increase substantially. This re-evaluation provides a blueprint for future re-evaluations of other trials. These best practices include re-analysis of the study data, after suitable replication, by an independent multidisciplinary committee, including a skilled statistical programmer analyst. Primary investigators should address significant errors determined in such re-analyses.

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