Literature DB >> 17715257

Clinical decision making and the expected value of information.

Andrew R Willan1.   

Abstract

BACKGROUND: The results of the HOPE study, a randomized clinical trial, provide strong evidence that 1) ramipril prevents the composite outcome of cardiovascular death, myocardial infarction or stroke in patients who are at high risk of a cardiovascular event and 2) ramipril is cost-effective at a threshold willingness-to-pay of $10,000 to prevent an event of the composite outcome. In this report the concept of the expected value of information is used to determine if the information provided by the HOPE study is sufficient for decision making in the US and Canada.
METHODS: and results Using the cost-effectiveness data from a clinical trial, or from a meta-analysis of several trials, one can determine, based on the number of future patients that would benefit from the health technology under investigation, the expected value of sample information (EVSI) of a future trial as a function of proposed sample size. If the EVSI exceeds the cost for any particular sample size then the current information is insufficient for decision making and a future trial is indicated. If, on the other hand, there is no sample size for which the EVSI exceeds the cost, then there is sufficient information for decision making and no future trial is required. Using the data from the HOPE study these concepts are applied for various assumptions regarding the fixed and variable cost of a future trial and the number of patients who would benefit from ramipril.
CONCLUSIONS: Expected value of information methods provide a decision-analytic alternative to the standard likelihood methods for assessing the evidence provided by cost-effectiveness data from randomized clinical trials.

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Year:  2007        PMID: 17715257     DOI: 10.1177/1740774507079237

Source DB:  PubMed          Journal:  Clin Trials        ISSN: 1740-7745            Impact factor:   2.486


  9 in total

Review 1.  Sample size determination for cost-effectiveness trials.

Authors:  Andrew R Willan
Journal:  Pharmacoeconomics       Date:  2011-11       Impact factor: 4.981

2.  The value of value of information: best informing research design and prioritization using current methods.

Authors:  Simon Eckermann; Jon Karnon; Andrew R Willan
Journal:  Pharmacoeconomics       Date:  2010       Impact factor: 4.981

3.  Value of information and pricing new healthcare interventions.

Authors:  Andrew R Willan; Simon Eckermann
Journal:  Pharmacoeconomics       Date:  2012-06-01       Impact factor: 4.981

4.  Using value-of-information methods when the disease is rare and the treatment is expensive--the example of hemophilia A.

Authors:  Lusine Abrahamyan; Andrew R Willan; Joseph Beyene; Marjorie Mclimont; Victor Blanchette; Brian M Feldman
Journal:  J Gen Intern Med       Date:  2014-08       Impact factor: 5.128

Review 5.  A systematic and critical review of the evolving methods and applications of value of information in academia and practice.

Authors:  Lotte Steuten; Gijs van de Wetering; Karin Groothuis-Oudshoorn; Valesca Retèl
Journal:  Pharmacoeconomics       Date:  2013-01       Impact factor: 4.981

6.  Personalized medicine and genomics: challenges and opportunities in assessing effectiveness, cost-effectiveness, and future research priorities.

Authors:  Rena Conti; David L Veenstra; Katrina Armstrong; Lawrence J Lesko; Scott D Grosse
Journal:  Med Decis Making       Date:  2010-01-04       Impact factor: 2.583

7.  Pharmacist-led management of chronic pain in primary care: costs and benefits in a pilot randomised controlled trial.

Authors:  Aileen R Neilson; Hanne Bruhn; Christine M Bond; Alison M Elliott; Blair H Smith; Philip C Hannaford; Richard Holland; Amanda J Lee; Margaret Watson; David Wright; Paul McNamee
Journal:  BMJ Open       Date:  2015-04-01       Impact factor: 2.692

8.  Sample Size Estimation for Non-Inferiority Trials: Frequentist Approach versus Decision Theory Approach.

Authors:  A C Bouman; A J ten Cate-Hoek; B L T Ramaekers; M A Joore
Journal:  PLoS One       Date:  2015-06-15       Impact factor: 3.240

9.  Developing appropriate methods for cost-effectiveness analysis of cluster randomized trials.

Authors:  Manuel Gomes; Edmond S-W Ng; Richard Grieve; Richard Nixon; James Carpenter; Simon G Thompson
Journal:  Med Decis Making       Date:  2011-10-19       Impact factor: 2.583

  9 in total

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