AIMS: A standard metric to estimate absolute treatment effects is numbers-needed-to-treat (NNT), which implicitly assumes that all benefits reverse at trial-end. However, in-trial survival benefits typically do not reverse until long after trial-end, so that NNT will substantially underestimate lifetime benefits. METHODS AND RESULTS: We developed a new concept, years-needed-to-treat (YNT) to add 1 year of life, that quantifies the expected average life expectancy for two treatments including the estimated years of life remaining post-trial. Numbers-needed-to-treat and YNT were calculated in the COMET trial, in which carvedilol vs. metoprolol tartrate resulted in 17% lower mortality over 4.8 years. A multivariate Cox model was used to predict survival. Remaining years of life were estimated using the mortality-life-table method. At trial-end, survival was 9% higher in the carvedilol arm. Assuming that patients remained on the same therapy post-trial, the average total years of life for carvedilol vs. metoprolol were 10.63 +/- 0.19 vs. 9.48 +/- 0.18 (P < 0.0001) or 1.15 (95% confidence interval 0.64-1.66) additional years of life. The YNT was 9.2, indicating that 9.2 person-years of treatment added 1 person-year of life, compared with NNT of 59. CONCLUSION: Compared with NNT, the YNT method more accurately accounts for potential long-term benefits of interventions in randomized trials.
RCT Entities:
AIMS: A standard metric to estimate absolute treatment effects is numbers-needed-to-treat (NNT), which implicitly assumes that all benefits reverse at trial-end. However, in-trial survival benefits typically do not reverse until long after trial-end, so that NNT will substantially underestimate lifetime benefits. METHODS AND RESULTS: We developed a new concept, years-needed-to-treat (YNT) to add 1 year of life, that quantifies the expected average life expectancy for two treatments including the estimated years of life remaining post-trial. Numbers-needed-to-treat and YNT were calculated in the COMET trial, in which carvedilol vs. metoprolol tartrate resulted in 17% lower mortality over 4.8 years. A multivariate Cox model was used to predict survival. Remaining years of life were estimated using the mortality-life-table method. At trial-end, survival was 9% higher in the carvedilol arm. Assuming that patients remained on the same therapy post-trial, the average total years of life for carvedilol vs. metoprolol were 10.63 +/- 0.19 vs. 9.48 +/- 0.18 (P < 0.0001) or 1.15 (95% confidence interval 0.64-1.66) additional years of life. The YNT was 9.2, indicating that 9.2 person-years of treatment added 1 person-year of life, compared with NNT of 59. CONCLUSION: Compared with NNT, the YNT method more accurately accounts for potential long-term benefits of interventions in randomized trials.
Authors: Arthur J Moss; Wojciech Zareba; W Jackson Hall; Helmut Klein; David J Wilber; David S Cannom; James P Daubert; Steven L Higgins; Mary W Brown; Mark L Andrews Journal: N Engl J Med Date: 2002-03-19 Impact factor: 91.245
Authors: M Packer; A J Coats; M B Fowler; H A Katus; H Krum; P Mohacsi; J L Rouleau; M Tendera; A Castaigne; E B Roecker; M K Schultz; D L DeMets Journal: N Engl J Med Date: 2001-05-31 Impact factor: 91.245
Authors: Philip A Poole-Wilson; Karl Swedberg; John G F Cleland; Andrea Di Lenarda; Peter Hanrath; Michel Komajda; Jacobus Lubsen; Beatrix Lutiger; Marco Metra; Willem J Remme; Christian Torp-Pedersen; Armin Scherhag; Allan Skene Journal: Lancet Date: 2003-07-05 Impact factor: 79.321
Authors: Michael Domanski; James Norman; Bertram Pitt; Mark Haigney; Stephen Hanlon; Eliot Peyster Journal: J Am Coll Cardiol Date: 2003-08-20 Impact factor: 24.094
Authors: Marc A Pfeffer; Karl Swedberg; Christopher B Granger; Peter Held; John J V McMurray; Eric L Michelson; Bertil Olofsson; Jan Ostergren; Salim Yusuf; Stuart Pocock Journal: Lancet Date: 2003-09-06 Impact factor: 79.321
Authors: A Hjalmarson; S Goldstein; B Fagerberg; H Wedel; F Waagstein; J Kjekshus; J Wikstrand; D El Allaf; J Vítovec; J Aldershvile; M Halinen; R Dietz; K L Neuhaus; A Jánosi; G Thorgeirsson; P H Dunselman; L Gullestad; J Kuch; J Herlitz; P Rickenbacher; S Ball; S Gottlieb; P Deedwania Journal: JAMA Date: 2000-03-08 Impact factor: 56.272
Authors: Wayne C Levy; Yanhong Li; Shelby D Reed; Michael R Zile; Ramin Shadman; Todd Dardas; David J Whellan; Kevin A Schulman; Stephen J Ellis; Matthew Neilson; Christopher M O'Connor Journal: JACC Clin Electrophysiol Date: 2017-03
Authors: Kenneth C Bilchick; Yongfei Wang; Alan Cheng; Jeptha P Curtis; Kumar Dharmarajan; George J Stukenborg; Ramin Shadman; Inder Anand; Lars H Lund; Ulf Dahlström; Ulrik Sartipy; Aldo Maggioni; Karl Swedberg; Chris O'Conner; Wayne C Levy Journal: J Am Coll Cardiol Date: 2017-05-30 Impact factor: 24.094
Authors: Wayne C Levy; Kerry L Lee; Anne S Hellkamp; Jeanne E Poole; Dariush Mozaffarian; David T Linker; Aldo P Maggioni; Inder Anand; Philip A Poole-Wilson; Daniel P Fishbein; George Johnson; Jill Anderson; Daniel B Mark; Gust H Bardy Journal: Circulation Date: 2009-08-24 Impact factor: 29.690
Authors: Meaghan Lunney; Marinella Ruospo; Patrizia Natale; Robert R Quinn; Paul E Ronksley; Ioannis Konstantinidis; Suetonia C Palmer; Marcello Tonelli; Giovanni Fm Strippoli; Pietro Ravani Journal: Cochrane Database Syst Rev Date: 2020-02-27
Authors: Judith A Finegold; Claire E Raphael; Wayne C Levy; Zachary Whinnett; Darrel P Francis Journal: J Am Coll Cardiol Date: 2013-09-04 Impact factor: 24.094