Review of the recommendations from the Decision Support Unit for the use of Population-Adjusted Indirect Comparisons in submissions to NICE

Research output: Contribution to conferenceConference Abstract

Abstract

We present the findings and recommendations of a recent NICE Technical Support Document (available from http://www.nicedsu.org.uk/) regarding the use of population-adjusted indirect comparisons in health technology appraisal.
Standard methods for indirect comparisons and network meta-analysis are based on aggregate data, with the key assumption that there is no difference between trials in the distribution of effect-modifying variables. Two methods which relax this assumption, Matching-Adjusted Indirect Comparison (MAIC) and Simulated Treatment Comparison (STC), are becoming increasingly common in industry-sponsored treatment comparisons, where a company has access to individual patient data (IPD) from its own trials but only aggregate data from competitor trials. Both methods use IPD to adjust for between-trial differences in covariate distributions. Despite their increasing popularity, there is a distinct lack of clarity about how and when these methods should be applied. We review the properties of these methods, and identify the key assumptions. Notably, there is a fundamental distinction between “anchored” and “unanchored” forms of indirect comparison, where a common comparator arm is or is not utilised to control for between-trial differences in prognostic variables, with the unanchored comparison making assumptions that are very hard to meet. Furthermore, both MAIC and STC as currently applied can only produce estimates that are valid for the populations in the competitor trials, which do not necessarily represent the decision population. We provide recommendations on how and when population adjustment methods should be used to provide statistically valid, clinically meaningful, transparent and consistent results for the purposes of health technology appraisal.
Original languageEnglish
Publication statusUnpublished - 30 Aug 2017
EventCEN-ISBS Joint Conference on Biometrics & Biopharmaceutical Statistics - Medical University of Vienna, Vienna, Austria
Duration: 29 Aug 20171 Sep 2017
http://www.cenisbs2017.org/

Conference

ConferenceCEN-ISBS Joint Conference on Biometrics & Biopharmaceutical Statistics
CountryAustria
CityVienna
Period29/08/171/09/17
Internet address

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    Student Theses

    Calibration of Treatment Effects in Network Meta-Analysis using Individual Patient Data

    Author: Phillippo, D. M., 28 Nov 2019

    Supervisor: Welton, N. (Supervisor) & Dias, S. (Supervisor)

    Student thesis: Doctoral ThesisDoctor of Philosophy (PhD)

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    • 1 Participation in conference

    CEN-ISBS Joint Conference on Biometrics & Biopharmaceutical Statistics

    David M Phillippo (Speaker)

    30 Aug 2017

    Activity: Participating in or organising an event typesParticipation in conference

    Cite this

    Phillippo, D. (2017). Review of the recommendations from the Decision Support Unit for the use of Population-Adjusted Indirect Comparisons in submissions to NICE. Abstract from CEN-ISBS Joint Conference on Biometrics & Biopharmaceutical Statistics, Vienna, Austria.