Methodological Considerations for Novel Approaches to Covariate-Adjusted Indirect Treatment Comparisons

Autor/inn/en	Remiro-Azócar, Antonio; Heath, Anna; Baio, Gianluca
Titel	Methodological Considerations for Novel Approaches to Covariate-Adjusted Indirect Treatment Comparisons
Quelle	In: Research Synthesis Methods, 14 (2023) 4, S.652-658 (7 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Remiro-Azócar, Antonio)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1759-2879
DOI	10.1002/jrsm.1645
Schlagwörter	Medical Research; Outcomes of Treatment; Comparative Analysis; Barriers; Data Analysis; Models + Suchen Sie Ihr Suchwort? Auswertung; Analogiemodell
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. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01