Program

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To Adjust or Not to Adjust for Effect Modifiers in HTA Submissions; Considerations in Population-Adjusted Indirect Treatment Comparisons

Speaker(s)

Moderator: Matthew Bryan, PhD, CADTH, Gatineau, QC, Canada
Panelists: Bart Heeg, MSc, PhD, Cytel, Rotterdam, ZH, Netherlands; Kirsty Rhodes, MSc, AstraZeneca, Cambridge, CAM, UK; Nicky Welton, PhD, social and community medicine, University of Bristol, Bristol, UK

Presentation Documents

ISSUE:

In HTA submissions, obtaining reliable relative treatment effect estimates (RTEs) for the technology under appraisal is critical for decision-making. Standard indirect treatment comparisons (ITCs) and network meta-analyses for estimating RTEs are based on aggregated data and assume that effect modifiers (EMs) are balanced between trials. When there are differences in the distribution of EMs across the trials, effect modification results in biased RTEs, and population-adjusted indirect comparison methods may be considered.

The panel will provide case-studies and debate on the considerations for selecting population adjustment methods, the circumstances when their assumptions can be justified and what to do when these are not met. The panel will also debate when EMs should not be adjusted for.

OVERVIEW:

Population adjustment methods such as matching-adjusted indirect comparison [MAIC] and simulated treatment comparisons [STC] use available individual patient data to adjust for differences in EMs through reweighting or regression adjustment. Recently, the NICE Decision Support Unit advocated a preference for the use of multilevel network meta-regression [ML-NMR] in HTA submissions, whereas MAIC should be avoided. Others have advocated that for time-to-event data, MAIC may result in less biased estimates than STC.

The debate on preferred population adjustment methods to inform RTEs is still ongoing. The moderator will introduce the topic by discussing how to identify if a covariate is a true EM for a decision problem; and how to ensure that the relationship between EMs and outcomes in ITCs are relatively unbiased (5min). Following, each panellist will present from a different background (research, consultancy, industry) the opportunities and challenges applying these ITC methods in decision-making and considerations on the way EMs are accounted for (15 min each). The session will conclude with an interactive discussion with the audience and the use of online polling questions. Stakeholders from industry, HTA bodies and researcher bodies will benefit.

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