Population Adjustment Methods for Indirect Comparisons: A Review of National Institute for Health and Care Excellence Technology Appraisals

Indirect comparisons via a common comparator (anchored comparisons) are commonly used in health technology assessment. However, common comparators may not be available, or the comparison may be biased due to differences in effect modifiers between the included studies. Recently proposed population a...

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Vydáno v:International journal of technology assessment in health care Ročník 35; číslo 3; s. 221 - 228
Hlavní autoři: Phillippo, David M., Dias, Sofia, Elsada, Ahmed, Ades, A. E., Welton, Nicky J.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York, USA Cambridge University Press 01.01.2019
Témata:
Appraisals
Comparators
Cost analysis
Cost effectiveness
Cost-Benefit Analysis
Data Interpretation, Statistical
Decision making
Health
Hepatitis
Humans
Kidney cancer
Leukemia
Lymphoma
Meta-analysis
Metastasis
Method
Methods
Multiple myeloma
Oncology
Population (statistical)
Population studies
Quality-Adjusted Life Years
State Medicine
Technology assessment
Technology Assessment, Biomedical - methods
TNF inhibitors
United Kingdom
Variables
United Kingdom
United Kingdom > UK
Comparative effectiveness research
Network meta-analysis
Effect modifier
Bias
Technology assessment
ISSN:0266-4623, 1471-6348, 1471-6348
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Shrnutí:Indirect comparisons via a common comparator (anchored comparisons) are commonly used in health technology assessment. However, common comparators may not be available, or the comparison may be biased due to differences in effect modifiers between the included studies. Recently proposed population adjustment methods aim to adjust for differences between study populations in the situation where individual patient data are available from at least one study, but not all studies. They can also be used when there is no common comparator or for single-arm studies (unanchored comparisons). We aim to characterise the use of population adjustment methods in technology appraisals (TAs) submitted to the United Kingdom National Institute for Health and Care Excellence (NICE). We reviewed NICE TAs published between 01/01/2010 and 20/04/2018. Population adjustment methods were used in 7 percent (18/268) of TAs. Most applications used unanchored comparisons (89 percent, 16/18), and were in oncology (83 percent, 15/18). Methods used included matching-adjusted indirect comparisons (89 percent, 16/18) and simulated treatment comparisons (17 percent, 3/18). Covariates were included based on: availability, expert opinion, effective sample size, statistical significance, or cross-validation. Larger treatment networks were commonplace (56 percent, 10/18), but current methods cannot account for this. Appraisal committees received results of population-adjusted analyses with caution and typically looked for greater cost effectiveness to minimise decision risk. Population adjustment methods are becoming increasingly common in NICE TAs, although their impact on decisions has been limited to date. Further research is needed to improve upon current methods, and to investigate their properties in simulation studies.
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All authors conceived the manuscript, revised the draft, gave final approval of the version to be published, and are accountable for all aspects of the work. DMP was responsible for data extraction and analysis and drafted the manuscript. AE drafted part of the manuscript. DMP and NJW are the guarantors.
Author contributions
ISSN:0266-4623
1471-6348
1471-6348
DOI:10.1017/S0266462319000333