Number needed to treat estimates incorporating effects over the entire range of clinical outcomes - Novel derivation method and application to thrombolytic therapy for acute stroke

Background: Number needed to treat (NNT) is a useful measure of a treatment's clinical benefit or harm. However, NNT estimates for treatments for neurologic conditions have previously been generated only for dichotomized functional outcomes, which may underestimate clinically relevant treatment effects. Objectives: To develop a method for estimating NNTs for nonbinary outcomes from parallel design clinical trials and to illustrate its application to outcomes of fibrinolytic stroke therapy across the full range of the modified Rankin Scale (mRS) of disability. samples of 100 patients assigned to placebo and active therapy. Methods: Expert generation of joint distribution outcome tables in a model population affords a novel means to derive NNTs for nonbinary end points. Using mRS distributions from the National Institute of Neurological Disorders and Stroke-Tissue Plasminogen Activator trials, 10 neurologist and emergency physician acute stroke care experts independently specified the joint distribution of outcomes in model. Results: The average estimated NNT for 1 additional patient to have a better outcome by 1 or more grades on the mRS as a result of treatment was 3.1 (95% confidence interval, 2.6-3.6). The estimated number needed to harm was 30.1 (95% confidence interval, 25.1-36.0). Expert estimates were robust across alternative stratifications of the mRS, with the NNT for benefit on 6- and 5-rank versions of 3.3 and 3.7 and the number needed to harm of 56.6 and 100.0, respectively. Conclusions: Expert generation of joint distribution outcome tables enables NNT estimation across a full spectrum of nonbinary outcomes. For every 100 patients with acute stroke treated with tissue plasminogen activator, approximately 32 have a better final outcome and 3 have a worse final outcome as a result of treatment.