Can Multivariable Risk-Benefit Profiling Be Used to Select Treatment-Favorable Patients for Thrombolysis in Stroke in the 3- to 6-Hour Time Window?

Abstract

The Stroke-Thrombolytic Predictive Instrument (Stroke-TPI) uses multivariate equations to predict outcomes with and without thrombolysis. We sought to examine whether such a multivariate predictive instrument might be useful in selecting patients with a favorable risk-benefit treatment profile for therapy after 3 hours. We explored outcomes in patients from 5 major randomized clinical trials testing intravenous recombinant tissue plasminogen activator (rt-PA) classified by the Stroke-TPI as "treatment-favorable" or "treatment-unfavorable." We used iterative bootstrap re-sampling to estimate how such a model would perform on independent test data. Among patients treated within the 3- to 6-hour window, 67% of patients were classified by Stroke-TPI predicted outcomes as "treatment-favorable" and 33% were classified as "treatment-unfavorable." Outcomes in the treatment-favorable group demonstrated benefit for thrombolysis (modified Rankin Scale score < or =1: 44.0% with rt-PA versus 34.2 with placebo, P=0.005), whereas harm was demonstrated in the treatment-unfavorable group (modified Rankin Scale score < or =1: 31.3% with rt-PA versus 38.3% with placebo; P=0.004). Bootstrap resampling with complete cross-validation showed that the absolute margin of benefit in the treatment-favorable group diminished on average by 36% between derivation and independent validation sets, but still represented a significant tripling of improvement in benefit compared with conventional inclusion criteria (5.2% [interquartile range, 1.7% to 8.6%] versus 1.8% [interquartile range, -0.5 to 4.1], P<0.0001). Such multivariable risk-benefit profiling may be useful in the selection of acute stroke patients for rt-PA therapy even more than 3 hours after symptom onset. Prospective testing is indicated.