Literature DB >> 21816576

Number needed to treat is incorrect without proper time-related considerations.

Daniel Suissa1, Paul Brassard, Brielan Smiechowski, Samy Suissa.   

Abstract

The number needed to treat (NNT) is a simple measure of a treatment's impact, increasingly reported in randomized trials and observational studies. Its calculation in studies involving varying follow-up times or recurrent outcomes has been criticized. We discuss the NNT in these contexts, illustrating using several published studies. The computation of the NNT is founded on the cumulative incidence of the outcome. Instead, several published studies use simple proportions that do not account for varying follow-up times, or use incidence rates per person-time. We show that these approaches can lead to erroneous values of the NNT and misleading interpretations. For example, after converting the incidence rate to a cumulative incidence, we show that a trial reporting a NNT of 4 "to prevent one exacerbation in 1 year" should have reported a NNT of 9. A survey of all papers reporting NNT, published in four major medical journals in 2009, found that 6 out of all 10 papers involving varying follow-up times did not correctly estimate the NNT. As the "number needed to treat" becomes increasingly used in complex studies and in the comparative effectiveness of therapies, its accurate estimation and interpretation become crucial to avoid erroneous clinical and public health decisions.
Copyright © 2012 Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Substances:

Year:  2011        PMID: 21816576     DOI: 10.1016/j.jclinepi.2011.04.009

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  14 in total

1.  Impact of a Telephonic Intervention to Improve Diabetes Control on Health Care Utilization and Cost for Adults in South Bronx, New York.

Authors:  Bahman P Tabaei; Renata E Howland; Jeffrey S Gonzalez; Shadi Chamany; Elizabeth A Walker; Clyde B Schechter; Winfred Y Wu
Journal:  Diabetes Care       Date:  2020-03-04       Impact factor: 19.112

2.  The "1-year-death number needed to treat" for comparing the impact of distinct interventions on patient outcomes.

Authors:  Brett N Hryciw; Finlay A McAlister; Meltem Tuna; Carl van Walraven
Journal:  CMAJ       Date:  2019-11-11       Impact factor: 8.262

3.  Patients with Crohn's Disease Are More Likely to Remain on Biologics than Immunomodulators: A Meta-Analysis of Treatment Durability.

Authors:  Eric D Shah; Corey A Siegel; Kelly Chong; Gil Y Melmed
Journal:  Dig Dis Sci       Date:  2015-03-14       Impact factor: 3.199

4.  Renin-Angiotensin-Aldosterone System Inhibitors and Risk of Acute Pancreatitis: A Population-Based Cohort Study.

Authors:  Julie Rouette; Hui Yin; Emily G McDonald; Alan Barkun; Laurent Azoulay
Journal:  Drug Saf       Date:  2021-10-29       Impact factor: 5.606

5.  Impacts of Medicaid Expansion on Health Insurance and Coverage Transitions among Women with or at Risk for HIV in the United States.

Authors:  Andrew Edmonds; Nadya Belenky; Adebola A Adedimeji; Mardge H Cohen; Gina Wingood; Margaret A Fischl; Elizabeth T Golub; Mallory O Johnson; Daniel Merenstein; Joel Milam; Deborah Konkle-Parker; Tracey E Wilson; Adaora A Adimora
Journal:  Womens Health Issues       Date:  2022-05-11

6.  Number needed to benefit from information (NNBI): proposal from a mixed methods research study with practicing family physicians.

Authors:  Pierre Pluye; Roland M Grad; Janique Johnson-Lafleur; Vera Granikov; Michael Shulha; Bernard Marlow; Ivan Luiz Marques Ricarte
Journal:  Ann Fam Med       Date:  2013 Nov-Dec       Impact factor: 5.166

7.  Cost-effectiveness of long-acting insulin analogues vs intermediate/long-acting human insulin for type 1 diabetes: A population-based cohort followed over 10 years.

Authors:  Tsung-Ying Lee; Shihchen Kuo; Chen-Yi Yang; Huang-Tz Ou
Journal:  Br J Clin Pharmacol       Date:  2020-01-23       Impact factor: 4.335

8.  Personalizing Aspirin Use for Targeted Breast Cancer Chemoprevention in Postmenopausal Women.

Authors:  Aditya Bardia; Tanya E Keenan; Jon O Ebbert; DeAnn Lazovich; Alice H Wang; Robert A Vierkant; Janet E Olson; Celine M Vachon; Paul J Limburg; Kristin E Anderson; James R Cerhan
Journal:  Mayo Clin Proc       Date:  2015-12-08       Impact factor: 7.616

9.  The Number Needed to Treat: 25 Years of Trials and Tribulations in Clinical Research.

Authors:  Samy Suissa
Journal:  Rambam Maimonides Med J       Date:  2015-07-30

10.  Quantification of Treatment Effect Modification on Both an Additive and Multiplicative Scale.

Authors:  Nicolas Girerd; Muriel Rabilloud; Philippe Pibarot; Patrick Mathieu; Pascal Roy
Journal:  PLoS One       Date:  2016-04-05       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.