Literature DB >> 12393076

Number needed to treat: easily understood and intuitively meaningful? Theoretical considerations and a randomized trial.

Ivar Sønbø Kristiansen1, Dorte Gyrd-Hansen, Jørgen Nexøe, Jesper Bo Nielsen.   

Abstract

Graphic representation was used to explore to what extent the number needed to treat (NNT) conveys the appropriate notion of benefit for the individual patient in interventions aimed at delaying adverse events. A sample of the Danish population (n = 675) was interviewed face to face, and asked whether they would consent to a hypothetical drug that reduces the risk of heart attack. The benefit of the drug was expressed in terms of NNT and was randomly set at 10, 25, 50, 100, 200, and 400. NNT does not convey information on the proportion of patients being helped by an intervention or the size of the delay of the adverse event intended to be prevented. The proportion of people consenting to the hypothetical drug was about 80%, irrespective of NNT, and some of those who rejected the drug misinterpreted the meaning of NNT. Lay people may have difficulties in understanding the meaning of NNT, and clinicians may do well to use the NNT with caution until more is known about how patients comprehend it.

Entities:  

Mesh:

Year:  2002        PMID: 12393076     DOI: 10.1016/s0895-4356(02)00432-8

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


  15 in total

Review 1.  Communicating risks at the population level: application of population impact numbers.

Authors:  Richard F Heller; Iain Buchan; Richard Edwards; Georgios Lyratzopoulos; Patrick McElduff; Selwyn St Leger
Journal:  BMJ       Date:  2003-11-15

2.  Evaluation of benefit-risk.

Authors:  Silvio Garattini
Journal:  Pharmacoeconomics       Date:  2010       Impact factor: 4.981

3.  Communicating risk using absolute risk reduction or prolongation of life formats: cluster-randomised trial in general practice.

Authors:  Charlotte Gry Harmsen; Ivar Sønbø Kristiansen; Pia Veldt Larsen; Jørgen Nexøe; Henrik Støvring; Dorte Gyrd-Hansen; Jesper Bo Nielsen; Adrian Edwards; Dorte Ejg Jarbøl
Journal:  Br J Gen Pract       Date:  2014-04       Impact factor: 5.386

4.  The "number needed to treat" turns 20--and continues to be used and misused.

Authors:  Finlay A McAlister
Journal:  CMAJ       Date:  2008-09-09       Impact factor: 8.262

5.  Therapeutic decisions by number needed to treat and survival gains: a cross-sectional survey of lipid-lowering drug recommendations.

Authors:  Peder A Halvorsen; Torbjørn F Wisløff; Henrik Støvring; Olaf Aasland; Ivar Sønbø Kristiansen
Journal:  Br J Gen Pract       Date:  2011-08       Impact factor: 5.386

6.  A proposal for an additional clinical trial outcome measure assessing preventive effect as delay of events.

Authors:  Per Lytsy; Lars Berglund; Johan Sundström
Journal:  Eur J Epidemiol       Date:  2012-12-07       Impact factor: 8.082

7.  Numeracy and communication with patients: they are counting on us.

Authors:  Andrea J Apter; Michael K Paasche-Orlow; Janine T Remillard; Ian M Bennett; Elana Pearl Ben-Joseph; Rosanna M Batista; James Hyde; Rima E Rudd
Journal:  J Gen Intern Med       Date:  2008-10-02       Impact factor: 5.128

8.  Re-interpreting conventional interval estimates taking into account bias and extra-variation.

Authors:  Michael Höfler; Shaun R Seaman
Journal:  BMC Med Res Methodol       Date:  2006-10-16       Impact factor: 4.615

Review 9.  Calculation of NNTs in RCTs with time-to-event outcomes: a literature review.

Authors:  Mandy Hildebrandt; Elke Vervölgyi; Ralf Bender
Journal:  BMC Med Res Methodol       Date:  2009-03-20       Impact factor: 4.615

10.  Can postponement of an adverse outcome be used to present risk reductions to a lay audience? A population survey.

Authors:  Rasmus Dahl; Dorte Gyrd-Hansen; Ivar Sønbø Kristiansen; Jørgen Nexøe; Jesper Bo Nielsen
Journal:  BMC Med Inform Decis Mak       Date:  2007-03-29       Impact factor: 2.796

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