Remiro-Azócar, Antonio;
Heath, Anna;
Baio, Gianluca;
(2023)
Methodological considerations for novel approaches to covariate-adjusted indirect treatment comparisons.
Research Synthesis Methods
, 14
(4)
pp. 652-658.
10.1002/jrsm.1645.
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Abstract
We examine four important considerations in the development of covariate adjustment methodologies for indirect treatment comparisons. First, we consider potential advantages of weighting versus outcome modeling, placing focus on bias-robustness. Second, we outline why model-based extrapolation may be required and useful, in the specific context of indirect treatment comparisons with limited overlap. Third, we describe challenges for covariate adjustment based on data-adaptive outcome modeling. Finally, we offer further perspectives on the promise of doubly robust covariate adjustment frameworks.
| Type: | Article |
|---|---|
| Title: | Methodological considerations for novel approaches to covariate-adjusted indirect treatment comparisons |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1002/jrsm.1645 |
| Publisher version: | https://doi.org/10.1002/jrsm.1645 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions. |
| Keywords: | covariate adjustment, health technology assessment, indirect treatment comparison, matching-adjusted indirect comparison, model misspecification, parametric G-computation |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10171767 |
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