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

Department of Biostatistics, Emory University, vhertzb{at}sph.emory.edu

Timothy Ingall

Department of Neurology, Mayo Clinic

William O'Fallon

Department of Biostatistics, Mayo Clinic

Kjell Asplund

National Board of Health and Welfare, Stockholm, Sweden

Lewis Goldfrank

Emergency Medicine, New York University School of Medicine

Thomas Louis

Department of Biostatistics, Johns Hopkins SPH

Teresa Christianson

Department of Biostatistics, Mayo Clinic

Background Treatment 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.

Purpose Describe the steps used to independently re-evaluate this trial.

Methods NIH 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.

Results Despite 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.

Conclusion With 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. Clinical Trials 2008; 5: 308—315. http://ctj.sagepub.com

Clinical Trials, Vol. 5, No. 4, 308-315 (2008)
DOI: 10.1177/1740774508094404


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