Propensity score methods for comparative-effectiveness analysis: a case study of direct oral anticoagulants in the atrial fibrillation population

Ciminata, G., Geue, C. , Wu, O. , Deidda, M. , Kreif, N. and Langhorne, P. (2022) Propensity score methods for comparative-effectiveness analysis: a case study of direct oral anticoagulants in the atrial fibrillation population. PLoS ONE, 17(1), e0262293. (doi: 10.1371/journal.pone.0262293) (PMID:35073380) (PMCID:PMC8786176)

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Abstract

Objective: To explore methodological challenges when using real-world evidence (RWE) to estimate comparative-effectiveness in the context of Health Technology Assessment of direct oral anticoagulants (DOACs) in Scotland. Methods: We used linkage data from the Prescribing Information System (PIS), Scottish Morbidity Records (SMR) and mortality records for newly anticoagulated patients to explore methodological challenges in the use of Propensity score (PS) matching, Inverse Probability Weighting (IPW) and covariate adjustment with PS. Model performance was assessed by standardised difference. Clinical outcomes (stroke and major bleeding) and mortality were compared for all DOACs (including apixaban, dabigatran and rivaroxaban) versus warfarin. Patients were followed for 2 years from first oral anticoagulant prescription to first clinical event or death. Censoring was applied for treatment switching or discontinuation. Results: Overall, a good balance of patients’ covariates was obtained with every PS model tested. IPW was found to be the best performing method in assessing covariate balance when applied to subgroups with relatively large sample sizes (combined-DOACs versus warfarin). With the IPTW-IPCW approach, the treatment effect tends to be larger, but still in line with the treatment effect estimated using other PS methods. Covariate adjustment with PS in the outcome model performed well when applied to subgroups with smaller sample sizes (dabigatran versus warfarin), as this method does not require further reduction of sample size, and trimming or truncation of extreme weights. Conclusion: The choice of adequate PS methods may vary according to the characteristics of the data. If assumptions of unobserved confounding hold, multiple approaches should be identified and tested. PS based methods can be implemented using routinely collected linked data, thus supporting Health Technology decision-making.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Ciminata, Dr Giorgio and Wu, Professor Olivia and Geue, Dr Claudia and Langhorne, Professor Peter and Deidda, Dr Manuela
Creator Roles:
Ciminata, G.Conceptualization, Formal analysis, Methodology, Writing – original draft, Writing – review and editing
Geue, C.Conceptualization, Methodology, Supervision, Writing – original draft, Writing – review and editing
Wu, O.Conceptualization, Funding acquisition, Methodology, Supervision, Writing – original draft, Writing – review and editing
Deidda, M.Conceptualization, Methodology, Writing – original draft, Writing – review and editing
Langhorne, P.Conceptualization, Methodology, Supervision, Writing – original draft, Writing – review and editing
Authors: Ciminata, G., Geue, C., Wu, O., Deidda, M., Kreif, N., and Langhorne, P.
College/School:College of Medical Veterinary and Life Sciences > School of Cardiovascular & Metabolic Health
College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Health Economics and Health Technology Assessment
Journal Name:PLoS ONE
Publisher:Public Library of Science
ISSN:1932-6203
ISSN (Online):1932-6203
Copyright Holders:Copyright © 2022 Ciminata et al
First Published:First published in PLoS ONE 17(1):e0262293
Publisher Policy:Reproduced under a Creative Commons Licence

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
190658The Scottish eHealth Informatics Research Centre (E-HIRCs).Jill PellMedical Research Council (MRC)MR/K007017/1HW - Public Health