Applying two approaches to detect unmeasured confounding due to time-varying variables in a self-controlled risk interval design evaluating COVID-19 vaccine safety signals, using myocarditis as a case example
Bots, Sophie H (Utrecht University)
Belitser, Svetlana (Utrecht University)
Groenwold, Rolf (Leiden University Medical Centre (Leiden, Països Baixos))
Durán, Carlos E (University Medical Center Utrecht)
Riera-Arnau, Judit (Universitat Autònoma de Barcelona. Departament de Farmacologia, de Terapèutica i de Toxicologia)
Schultze, Anna (London School of Hygiene and Tropical Medicine)
Messina, Davide (Agenzia Regionale di Sanità)
Segundo, Elena (Institut Universitari d'Investigació en Atenció Primària Jordi Gol)
Douglas, Ian (London School of Hygiene and Tropical Medicine)
Carreras, Juan José (Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana)
Garcia-Poza, Patricia (Spanish Agency for Medicines and Medical Devices (AEMPS))
Gini, Rosa (Agenzia Regionale di Sanità)
Huerta, Consuelo (Spanish Agency for Medicines and Medical Devices (AEMPS))
Martín-Pérez, Mar (Spanish Agency for Medicines and Medical Devices (AEMPS))
Martin, Ivonne (University Medical Center Utrecht)
Paoletti, Olga (Agenzia Regionale di Sanità)
Bissacco, Carlo Alberto (Institut Universitari d'Investigació en Atenció Primària Jordi Gol)
Correcher-Martínez, Elisa (Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana)
Souverein, Patrick (Utrecht University)
Urchueguía-Fornes, Arantxa (Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana)
Villalobos, Felipe (Institut Universitari d'Investigació en Atenció Primària Jordi Gol)
Sturkenboom, Miriam C J M (University Medical Center Utrecht)
Klungel, Olaf H (Utrecht University)

Fecha:	2024
Resumen:	We test the robustness of the self-controlled risk interval (SCRI) design in a setting where time between doses may introduce time-varying confounding, using both negative control outcomes (NCOs) and quantitative bias analysis (QBA). All vaccinated cases identified from 5 European databases between September 1, 2020, and end of data availability were included. Exposures were doses 1-3 of the Pfizer, Moderna, AstraZeneca, and Janssen COVID-19 vaccines; outcomes were myocarditis and, as the NCO, otitis externa. The SCRI used a 60-day control window and dose-specific 28-day risk windows, stratified by vaccine brand and adjusted for calendar time. The QBA included two scenarios: (1) baseline probability of the confounder was higher in the control window and (2) vice versa. The NCO was not associated with any of the COVID-19 vaccine types or doses except Moderna dose 1 (IRR = 1. 09; 95% CI 1. 01-1. 09). The QBA suggested that even the strongest literature-reported confounder (COVID-19; RR for myocarditis = 18. 3) could only explain away part of the observed effect, from IRR = 3 to IRR = 1. 40. The SCRI seems robust to unmeasured confounding in the COVID-19 setting, although a strong unmeasured confounder could bias the observed effect upward. Replication of our findings for other safety signals would strengthen this conclusion. This article is part of a Special Collection on Pharmacoepidemiology.
Derechos:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Lengua:	Anglès
Documento:	Article ; recerca ; Versió publicada
Materia:	Pharmacoepidemiology ; Negative controls ; Quantitative bias analysis ; COVID-19 vaccine safety ; Self-controlled risk interval design
Publicado en:	American Journal of Epidemiology, Vol. 194 Núm. 1 (July 2024) , p. 208-219, ISSN 1476-6256

DOI: 10.1093/aje/kwae172
PMID: 38960670

12 p, 1.0 MB

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