Population-adjusted indirect comparisons (MAIC and STC)
A technical support document about population-adjusted indirect comparisons produced by the Nice DSU.
Appendix D: Worked example of MAIC and STC (PDF, 295KB)
Code for R (.zip, 3KB)
The documents above are also available in a zip file (.zip, 1.3MB).
A standard methodology for indirect comparisons is now used routinely in submissions to NICE. This allows estimates on the relative effect of C vs B to be estimated from an AB trial and an AC trial.
Recently, publications have appeared on “Matching-adjusted Indirect Comparisons” (MAICs) and on “Simulated Treatment Comparisons” (STCs). The aim of these methods is to hold out the promise of improving on standard indirect comparisons by using individual patient data (IPD) in a subset of trials to control for imbalances in “baseline characteristics” in the trial evidence.
These methods are now being used increasingly in STA submissions to NICE, particularly when the manufacturer has access to individual patient data on its own AB trial, but only aggregate data on the competitor’s AC trial.
The purpose of this TSD is to comment on the reliability of these methods and to provide recommendations on their use in the context of NICE appraisals.
Related technical support documents on evidence synthesis
Phillipo D, Ades A, Dias S, Palmer S, Abrams K and Welton N (2018) Methods for population-adjusted indirect comparisons in health technology appraisal. Medical Decision Making, 38(2), pp. 200-211.
A global reputation
Sheffield is a research university with a global reputation for excellence. We're a member of the Russell Group: one of the 24 leading UK universities for research and teaching.