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

ABSTRACT: OBJECTIVES: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). METHODS:We reviewed NICE TAs published between 01/01/2010 and 20/04/2018. RESULTS: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. CONCLUSIONS: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.

SUBMITTER: Phillippo DM

PROVIDER: S-EPMC6650293 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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

Phillippo David M DM Dias Sofia S Elsada Ahmed A Ades A E AE Welton Nicky J NJ

International journal of technology assessment in health care 20190101 3

<h4>Objectives</h4>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. ...[more]

PMID: 31190671

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Project description:Standard methods for indirect comparisons and network meta-analysis are based on aggregate data, with the key assumption that there is no difference between the trials in the distribution of effect-modifying variables. Methods which relax this assumption are becoming increasingly common for submissions to reimbursement agencies, such as the National Institute for Health and Care Excellence (NICE). These methods use individual patient data from a subset of trials to form population-adjusted indirect comparisons between treatments, in a specific target population. Recently proposed population adjustment methods include the Matching-Adjusted Indirect Comparison (MAIC) and the Simulated Treatment Comparison (STC). Despite increasing popularity, MAIC and STC remain largely untested. Furthermore, there is a lack of clarity about exactly how and when they should be applied in practice, and even whether the results are relevant to the decision problem. There is therefore a real and present risk that the assumptions being made in one submission to a reimbursement agency are fundamentally different to-or even incompatible with-the assumptions being made in another for the same indication. We describe the assumptions required for population-adjusted indirect comparisons, and demonstrate how these may be used to generate comparisons in any given target population. We distinguish between anchored and unanchored comparisons according to whether a common comparator arm is used or not. Unanchored comparisons make much stronger assumptions, which are widely regarded as infeasible. We provide recommendations on how and when population adjustment methods should be used, and the supporting analyses that are required to provide statistically valid, clinically meaningful, transparent and consistent results for the purposes of health technology appraisal. Simulation studies are needed to examine the properties of population adjustment methods and their robustness to breakdown of assumptions.

Project description:ObjectiveTo investigate the prevalence of financial interests among patient organisations contributing to health technology assessment at the National Institute for Health and Care Excellence (NICE) in England and the extent to which NICE's disclosure policy ensures that decision making committees are aware of these interests.DesignPolicy review using accounts, annual reports, and websites of patient organisations; payments declared by pharmaceutical manufacturers on their websites and a centralised database (Disclosure UK); declarations of interests by nominated representatives of patient organisations; and responses from patient organisations.SettingAppraisals of medicines and treatments (technologies) for use in the English and Welsh National Health Service.Participants53 patient organisations contributing to 41 NICE technology appraisals published in 2015 and 2016, with 117 separate occasions that a patient organisation contributed to the appraisal of a technology.Main outcome measuresPrevalence of specific interests (that is, funding from manufacturer(s) of a technology under appraisal or competitor products); proportion of specific interests of which NICE's decision making committees were aware; proportion of unknown specific interests for which disclosure was not required by NICE's policy RESULTS: 38/53 (72%) patient organisations had accepted funding from the manufacturer(s) of a technology or a competitor product in the same year that they had contributed to the appraisal of that technology or the previous year. Specific interests were present on 92/117 (79%) occasions that patient organisations contributed to appraisals in 2015 and 2016. NICE's decision making committees were aware of less than a quarter of specific interests (30/144; 21%). For nearly two thirds of the specific interests not known to committees (71/114; 62%), disclosure by patient organisations was not required by NICE's policy.ConclusionsFinancial interests are highly prevalent among patient organisations contributing to health technology assessment. NICE should review its disclosure policy to ensure that decision making committees are aware of all relevant interests.

Dataset Information

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

Publications

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

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