A methodological review of population-adjusted indirect comparisons reveals inconsistent reporting and suggests publication bias.

Clinical research Health technology assessment Matching-adjusted indirect comparisons Methodological review Population-adjusted indirect comparisons Simulated treatment comparisons

Journal

Journal of clinical epidemiology
ISSN: 1878-5921
Titre abrégé: J Clin Epidemiol
Pays: United States
ID NLM: 8801383

Informations de publication

Date de publication:
Nov 2023
Historique:
received: 24 05 2023
revised: 07 09 2023
accepted: 11 09 2023
pubmed: 18 9 2023
medline: 18 9 2023
entrez: 17 9 2023
Statut: ppublish

Résumé

Population-adjusted indirect comparisons (PAICs) were developed in the 2010s to allow for comparisons between two treatments evaluated in different trials while accounting for differences in patient characteristics if individual patient data (IPD) are available for only one trial. Such comparisons are increasingly used in market access applications when a pharmaceutical company compares its new treatment (with IPD available) to another treatment developed by a competitor (with only aggregated data available). This study aimed to describe the characteristics of these PAICs, assess their methodology, and describe the reported results. Original articles reporting the use of at least one PAIC were searched on PubMed between January 1, 2010 and April 2, 2022. Two reviewers independently selected articles and extracted data. We included 133 publications reporting the results of 288 PAICs. Half of the articles were published on or after May 7, 2020, and 71 (53%) pertained to onco-hematology. The pharmaceutical industry was involved in 130 (98%) articles. Key methodological aspects were reported inconsistently, with only three articles adequately reporting all aspects. A total of 161 (56%) articles reported a statistically significant benefit for the treatment evaluated on IPD. Conversely, only one PAIC significantly favored the treatment evaluated on aggregated data. Although the number of published PAICs is increasing, the methodology and transparency need to be improved. Moreover, our study strongly suggests a reporting bias. This situation calls for strengthening guidelines to improve trust in PAIC results and thus their reliability in market access applications.

Identifiants

pubmed: 37717707
pii: S0895-4356(23)00237-8
doi: 10.1016/j.jclinepi.2023.09.004
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1-10

Informations de copyright

Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no competing interest.

Auteurs

Arnaud Serret-Larmande (A)

INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique, AP-HP, Hôpital Pitié-Salpêtrière, Département de Santé Publique, Centre de Pharmacoépidémiologie, Sorbonne Université, Paris, France; ECSTRRA Team UMR-1153 INSERM, AP-HP Saint Louis Hospital, Université Paris Cité, Paris, France. Electronic address: Arnaud.serret-larmande@u-paris.fr.

Belkacem Zenati (B)

INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique, AP-HP, Hôpital Pitié-Salpêtrière, Département de Santé Publique, Centre de Pharmacoépidémiologie, Sorbonne Université, Paris, France.

Agnès Dechartres (A)

INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique, AP-HP, Hôpital Pitié-Salpêtrière, Département de Santé Publique, Centre de Pharmacoépidémiologie, Sorbonne Université, Paris, France.

Jérôme Lambert (J)

ECSTRRA Team UMR-1153 INSERM, AP-HP Saint Louis Hospital, Université Paris Cité, Paris, France.

David Hajage (D)

INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique, AP-HP, Hôpital Pitié-Salpêtrière, Département de Santé Publique, Centre de Pharmacoépidémiologie, Sorbonne Université, Paris, France.

Classifications MeSH