Academic Journal
A critical look at observational studies.
| Τίτλος: | A critical look at observational studies. |
|---|---|
| Συγγραφείς: | Torgutalp M; Department of Rheumatology and Clinical Immunology, Charité - Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany; Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Berlin, Germany; Department of Gastroenterology, Infectiology and Rheumatology (including Nutrition Medicine), Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany., Sahin D; Department of Gastroenterology, Infectiology and Rheumatology (including Nutrition Medicine), Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany., Tascilar K; Department of Internal Medicine 3 Rheumatology and Immunology, Friedrich-Alexander University Erlangen-Nuremberg Universitätsklinikum, Erlangen, Germany; Deutsches Zentrum für Immuntherapie (DZI), Friedrich-Alexander University Erlangen-Nuremberg Universitätsklinikum Erlangen, Erlangen, Germany. Electronic address: Koray.Tascilar@uk-erlangen.de. |
| Πηγή: | Current opinion in immunology [Curr Opin Immunol] 2026 Jun; Vol. 100, pp. 102778. Date of Electronic Publication: 2026 Apr 16. |
| Τύπος έκδοσης: | Journal Article; Review |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Elsevier Country of Publication: England NLM ID: 8900118 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-0372 (Electronic) Linking ISSN: 09527915 NLM ISO Abbreviation: Curr Opin Immunol Subsets: MEDLINE |
| Imprint Name(s): | Publication: 1999- : London : Elsevier Original Publication: Philadelphia, PA, USA : Current Science, c1988- |
| Ιατρικοί όροι (MeSH): | Observational Studies as Topic*/methods, Humans ; Bias |
| Περίληψη: | Observational studies serve as a critical alternative when randomized trials are precluded by ethical concerns, high costs, or the need for rapid evidence-based hypothesis generation. Increasing reliance on routinely collected observational data (electronic health records, registries, and claims) has been accompanied by an increase in the risk of systematic errors that might threaten the validity. In this review, we focus on a selected set of common and crucial issues, confounding, and the use of directed acyclic graphs to describe and analyze causal relationships. We also highlight selection processes that can induce collider bias and create spurious associations between exposure and outcome. Time-varying confounding, where prior treatment affects future confounders, necessitates the use of specific estimation methods. We discuss measurement error and misclassification in routinely collected data and time-to-event pitfalls, the handling of competing events, and missing data. (Copyright © 2026 The Author(s). Published by Elsevier Ltd.. All rights reserved.) |
| Competing Interests: | Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. |
| Entry Date(s): | Date Created: 20260418 Date Completed: 20260715 Latest Revision: 20260715 |
| Update Code: | 20260715 |
| DOI: | 10.1016/j.coi.2026.102778 |
| PMID: | 42000174 |
| Βάση Δεδομένων: | MEDLINE |
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