Literature DB >> 15911727

Decisions on drug therapies by numbers needed to treat: a randomized trial.

Peder Andreas Halvorsen1, Ivar Sønbø Kristiansen.   

Abstract

BACKGROUND: The number needed to treat (NNT) has been promoted as the preferred effect measure when patients and physicians share decision making. Our aim was to explore the impact of the NNT on laypeople's decisions about preventive drug therapies.
METHODS: Two thousand subjects were selected for the survey; 1201 (60%) responded for a representative sample of the Norwegian population. Respondents were allocated to scenarios with random combinations of a disease to be prevented, drug treatment costs, and effect size in terms of NNT. They were interviewed about their hypothetical consent to the therapy, then randomized to different interpretations of NNT and asked to reconsider their initial responses.
RESULTS: The proportions consenting varied from 76% when the NNT was 50 to 67% when the NNT was 1600 (P for trend = .06). When faced with the prospect of avoiding lethal disease, stroke, myocardial infarction, or hip fracture, the proportions consenting were 84%, 76%, 68%, and 53%, respectively (P<.01). Across different treatment costs ($37, $68, $162, and $589) the proportions consenting varied from 78% to 61% (P for trend <.01). Twenty-four percent of the respondents changed their decision when informed about how to interpret the NNT, and 93% of those switched from positive to negative decisions, regardless of the magnitude of NNT.
CONCLUSIONS: Respondents' decisions were influenced by the type of disease to be prevented and the cost of the intervention, but not by the effect size in terms of NNT. This suggests that NNT is difficult to understand and that other effect formats should be considered for shared decision making.

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Year:  2005        PMID: 15911727     DOI: 10.1001/archinte.165.10.1140

Source DB:  PubMed          Journal:  Arch Intern Med        ISSN: 0003-9926


  16 in total

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

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3.  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
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4.  Do invitations for cervical screening provide sufficient information to enable informed choice? A cross-sectional study of invitations for publicly funded cervical screening.

Authors:  Sie Karen Kolthoff; Mie Sara Hestbech; Karsten Juhl Jørgensen; John Brodersen
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6.  A decade of controversy: balancing policy with evidence in the regulation of prescription drug advertising.

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7.  Impact of effectiveness information format on patient choice of therapy and satisfaction with decisions about chronic disease medication: the "Influence of intervention Methodologies on Patient Choice of Therapy (IMPACT)" cluster-randomised trial in general practice.

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8.  Personalized prediction of lifetime benefits with statin therapy for asymptomatic individuals: a modeling study.

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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.

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