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.
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.
Authors: Werner Hacke; Markku Kaste; Erich Bluhmki; Miroslav Brozman; Antoni Dávalos; Donata Guidetti; Vincent Larrue; Kennedy R Lees; Zakaria Medeghri; Thomas Machnig; Dietmar Schneider; Rüdiger von Kummer; Nils Wahlgren; Danilo Toni Journal: N Engl J Med Date: 2008-09-25 Impact factor: 91.245
Authors: W Hacke; M Kaste; C Fieschi; R von Kummer; A Davalos; D Meier; V Larrue; E Bluhmki; S Davis; G Donnan; D Schneider; E Diez-Tejedor; P Trouillas Journal: Lancet Date: 1998-10-17 Impact factor: 79.321
Authors: Werner Hacke; Geoffrey Donnan; Cesare Fieschi; Markku Kaste; Rüdiger von Kummer; Joseph P Broderick; Thomas Brott; Michael Frankel; James C Grotta; E Clarke Haley; Thomas Kwiatkowski; Steven R Levine; Chris Lewandowski; Mei Lu; Patrick Lyden; John R Marler; Suresh Patel; Barbara C Tilley; Gregory Albers; Erich Bluhmki; Manfred Wilhelm; Scott Hamilton Journal: Lancet Date: 2004-03-06 Impact factor: 79.321
Authors: G P Samsa; D B Matchar; L Goldstein; A Bonito; P W Duncan; J Lipscomb; C Enarson; D Witter; P Venus; J E Paul; M Weinberger Journal: Am Heart J Date: 1998-10 Impact factor: 4.749
Authors: W Hacke; M Kaste; C Fieschi; D Toni; E Lesaffre; R von Kummer; G Boysen; E Bluhmki; G Höxter; M H Mahagne Journal: JAMA Date: 1995-10-04 Impact factor: 56.272
Authors: Maarten G Lansberg; Martin J O'Donnell; Pooja Khatri; Eddy S Lang; Mai N Nguyen-Huynh; Neil E Schwartz; Frank A Sonnenberg; Sam Schulman; Per Olav Vandvik; Frederick A Spencer; Pablo Alonso-Coello; Gordon H Guyatt; Elie A Akl Journal: Chest Date: 2012-02 Impact factor: 9.410
Authors: Maarten G Lansberg; Jun Lee; Soren Christensen; Matus Straka; Deidre A De Silva; Michael Mlynash; Bruce C Campbell; Roland Bammer; Jean-Marc Olivot; Patricia Desmond; Stephen M Davis; Geoffrey A Donnan; Gregory W Albers Journal: Stroke Date: 2011-04-14 Impact factor: 7.914
Authors: D Sacks; B Baxter; B C V Campbell; J S Carpenter; C Cognard; D Dippel; M Eesa; U Fischer; K Hausegger; J A Hirsch; M S Hussain; O Jansen; M V Jayaraman; A A Khalessi; B W Kluck; S Lavine; P M Meyers; S Ramee; D A Rüfenacht; C M Schirmer; D Vorwerk Journal: AJNR Am J Neuroradiol Date: 2018-05-17 Impact factor: 3.825
Authors: Felipe de Los Ríos la Rosa; Jane Khoury; Brett M Kissela; Matthew L Flaherty; Kathleen Alwell; Charles J Moomaw; Pooja Khatri; Opeolu Adeoye; Daniel Woo; Simona Ferioli; Dawn O Kleindorfer Journal: Stroke Date: 2012-03-22 Impact factor: 7.914
Authors: Jeffrey L Saver; Eric E Smith; Gregg C Fonarow; Mathew J Reeves; Xin Zhao; Daiwai M Olson; Lee H Schwamm Journal: Stroke Date: 2010-06-03 Impact factor: 7.914
Authors: Sunil A Sheth; Reza Jahan; Jan Gralla; Vitor M Pereira; Raul G Nogueira; Elad I Levy; Osama O Zaidat; Jeffrey L Saver Journal: Ann Neurol Date: 2015-08-17 Impact factor: 10.422
Authors: Guillaume Bouchoux; Kenneth B Bader; Joseph J Korfhagen; Jason L Raymond; Ravishankar Shivashankar; Todd A Abruzzo; Christy K Holland Journal: Phys Med Biol Date: 2012-11-15 Impact factor: 3.609