{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T04:38:00Z","timestamp":1783399080448,"version":"3.54.6"},"reference-count":28,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2024,7,4]],"date-time":"2024-07-04T00:00:00Z","timestamp":1720051200000},"content-version":"vor","delay-in-days":1,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100013120","name":"European Medicines Agency","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100013120","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,1,8]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>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\u00a0= 1.09; 95% CI 1.01-1.09). The QBA suggested that even the strongest literature-reported confounder (COVID-19; RR for myocarditis\u00a0= 18.3) could only explain away part of the observed effect, from IRR\u00a0= 3 to IRR\u00a0= 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.<\/jats:p>\n               <jats:p>This article is part of a Special Collection on Pharmacoepidemiology.<\/jats:p>","DOI":"10.1093\/aje\/kwae172","type":"journal-article","created":{"date-parts":[[2024,7,4]],"date-time":"2024-07-04T01:30:52Z","timestamp":1720056652000},"page":"208-219","source":"Crossref","is-referenced-by-count":5,"title":["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"],"prefix":"10.1093","volume":"194","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4483-5582","authenticated-orcid":false,"given":"Sophie H","family":"Bots","sequence":"first","affiliation":[{"name":"Utrecht University Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, , 3508 TB, Utrecht,","place":["The Netherlands"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Svetlana","family":"Belitser","sequence":"additional","affiliation":[{"name":"Utrecht University Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, , 3508 TB, Utrecht,","place":["The Netherlands"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rolf H H","family":"Groenwold","sequence":"additional","affiliation":[{"name":"Leiden University Medical Centre Department of Clinical Epidemiology, , 2333 ZA, Leiden,","place":["the Netherlands"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carlos E","family":"Dur\u00e1n","sequence":"additional","affiliation":[{"name":"University Medical Center Utrecht Department of Data Science and Biostatistics, Julius Center for Health Sciences and Primary Health, , 3584 CG, Utrecht,","place":["The 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