Treatment time-specific number needed to treat estimates for tissue plasminogen activator therapy in acute stroke based on shifts over the entire range of the modified Rankin Scale
- PMID: 19372447
- PMCID: PMC2881642
- DOI: 10.1161/STROKEAHA.108.540708
Treatment time-specific number needed to treat estimates for tissue plasminogen activator therapy in acute stroke based on shifts over the entire range of the modified Rankin Scale
Abstract
Background and purpose: To make informed treatment decisions, patients and physicians need to be aware of the benefits and risks of a proposed treatment. The number needed to treat (NNT) for benefit and harm are intuitive and statistically valid measures to describe a treatment effect. The aim of this study is to calculate treatment time-specific NNT estimates based on shifts over the entire spectrum of clinically relevant functional outcomes.
Methods: The pooled data set of the first 6 major randomized acute stroke trials of intravenous tissue plasminogen activator was used for this study. The data were stratified by 90-minute treatment time windows. NNT for benefit and NNT for harm estimates were determined based on expert generation of joint outcome distribution tables. NNT for benefit estimates were also calculated based on joint outcome distribution tables generated by a computer model.
Results: NNT for benefit estimates based on the expert panel were 3.6 for patients treated between 0 and 90 minutes, 4.3 with treatment between 91 and 180 minutes, 5.9 with treatment between 181 and 270 minutes, and 19.3 with treatment between 271 and 360 minutes. The computer simulation yielded very similar results. The NNT for harm estimates for the corresponding time intervals are 65, 38, 30, and 14.
Conclusions: Up to 4(1/2) hours after symptom onset, tissue plasminogen activator therapy is associated with more benefit than harm, whereas there is no evidence of a net benefit in the 4(1/2)- to 6-hour time window. The NNT estimates for each 90-minute epoch provide useful and intuitive information based on which patients may be able to make better informed treatment decisions.
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