Literature DB >> 18767899

Subgroups and heterogeneity in cost-effectiveness analysis.

Mark Sculpher1.   

Abstract

The National Institute for Health and Clinical Excellence (NICE) is required to consider cost effectiveness when issuing guidance about the use of health technologies within the UK NHS. Cost effectiveness is a means of supporting a system objective of maximizing population health gain from the available budget. There is a range of sources of variation between individuals in disease prognosis, and in the costs and effects of health technologies. It is often possible to explain some of this variation on the basis of the clinical and sociodemographic characteristics of patients. This facilitates subgroup-specific estimates of parameters in decision analytic models and provides a means of assessing heterogeneity in cost effectiveness between different types of patient. Given the objective of the NHS, there is a clear need for NICE, and similar decision makers in other systems, to reflect this heterogeneity by being as specific as possible about the characteristics of the recipients of new treatments. The use of subgroup analysis in cost-effectiveness analysis raises a number of methodological questions that have been given little consideration in the literature. They include a need to define the possible sources of heterogeneity that exist, which extends beyond relative treatment effect (which is the focus of clinical trial analysis) to include, for example, sources relating to baseline event rates. There is also the issue of how heterogeneity in model parameters should be estimated and how uncertainty should be appropriately quantified. A major issue also exists concerning the appropriateness, in terms of equity, of using all or some of the subgroup analyses as a basis of decision making. NICE needed to consider these and other issues when updating its methods guidance.

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Year:  2008        PMID: 18767899     DOI: 10.2165/00019053-200826090-00009

Source DB:  PubMed          Journal:  Pharmacoeconomics        ISSN: 1170-7690            Impact factor:   4.981


  18 in total

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Journal:  Stat Med       Date:  1997-12-15       Impact factor: 2.373

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8.  Cost effectiveness of perindopril in reducing cardiovascular events in patients with stable coronary artery disease using data from the EUROPA study.

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9.  Testing for qualitative interactions between treatment effects and patient subsets.

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10.  Searching for a threshold, not setting one: the role of the National Institute for Health and Clinical Excellence.

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  46 in total

1.  Population- versus cohort-based modelling approaches.

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Journal:  Pharmacoeconomics       Date:  2012-03       Impact factor: 4.981

Review 2.  International comparison of comparative effectiveness research in five jurisdictions: insights for the US.

Authors:  Adrian R Levy; Craig Mitton; Karissa M Johnston; Brian Harrigan; Andrew H Briggs
Journal:  Pharmacoeconomics       Date:  2010       Impact factor: 4.981

3.  Choice of statistical model for cost-effectiveness analysis and covariate adjustment: empirical application of prominent models and assessment of their results.

Authors:  Theodoros Mantopoulos; Paul M Mitchell; Nicky J Welton; Richard McManus; Lazaros Andronis
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4.  NICE Methodology for Technology Appraisals: cutting edge or tried and trusted?

Authors:  Louise Longworth; Carole Longson
Journal:  Pharmacoeconomics       Date:  2008       Impact factor: 4.981

Review 5.  Use of indirect and mixed treatment comparisons for technology assessment.

Authors:  Alex Sutton; A E Ades; Nicola Cooper; Keith Abrams
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6.  NICE's 2008 Methods Guide: sensible consolidation or opportunities missed?

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7.  Exploring uncertainty in cost-effectiveness analysis.

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Journal:  Pharmacoeconomics       Date:  2008       Impact factor: 4.981

8.  NICE Guide to the Methods of Technology Appraisal: pharmaceutical industry perspective.

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9.  Racial variation in the cost-effectiveness of chemotherapy for prostate cancer.

Authors:  Michael Grabner; Eberechukwu Onukwugha; Rahul Jain; C Daniel Mullins
Journal:  J Oncol Pract       Date:  2011-05       Impact factor: 3.840

Review 10.  Acknowledging patient heterogeneity in economic evaluation : a systematic literature review.

Authors:  Janneke P C Grutters; Mark Sculpher; Andrew H Briggs; Johan L Severens; Math J Candel; James E Stahl; Dirk De Ruysscher; Albert Boer; Bram L T Ramaekers; Manuela A Joore
Journal:  Pharmacoeconomics       Date:  2013-02       Impact factor: 4.981

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