Subgroup analyses in cost-effectiveness analyses to support health technology assessments.

Fletcher, C; Chuang-Stein, C; Paget, MA; Reid, C; Hawkins, N; (2014) Subgroup analyses in cost-effectiveness analyses to support health technology assessments. Pharmaceutical statistics, 13 (4). pp. 265-74. ISSN 1539-1604 DOI:

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: 'Success' in drug development is bringing to patients a new medicine that has an acceptable benefit-risk profile and that is also cost-effective. Cost-effectiveness means that the incremental clinical benefit is deemed worth paying for by a healthcare system, and it has an important role in enabling manufacturers to obtain new medicines to patients as soon as possible following regulatory approval. Subgroup analyses are increasingly being utilised by decision-makers in the determination of the cost-effectiveness of new medicines when making recommendations. This paper highlights the statistical considerations when using subgroup analyses to support cost-effectiveness for a health technology assessment. The key principles recommended for subgroup analyses supporting clinical effectiveness published by Paget et al. are evaluated with respect to subgroup analyses supporting cost-effectiveness. A health technology assessment case study is included to highlight the importance of subgroup analyses when incorporated into cost-effectiveness analyses. In summary, we recommend planning subgroup analyses for cost-effectiveness analyses early in the drug development process and adhering to good statistical principles when using subgroup analyses in this context. In particular, we consider it important to provide transparency in how subgroups are defined, be able to demonstrate the robustness of the subgroup results and be able to quantify the uncertainty in the subgroup analyses of cost-effectiveness.<br/>

Item Type: Article
Keywords: cost-effectiveness, health technology assessment, subgroups, uncertainty, Cost-Benefit Analysis, methods, Humans, Technology Assessment, Biomedical, economics, Uncertainty
Faculty and Department: Faculty of Public Health and Policy > Dept of Health Services Research and Policy
Research Centre: Centre for Statistical Methodology
PubMed ID: 24931490
Web of Science ID: 340596500008


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