Specifying a target trial prevents immortal time bias and other self-inflicted injuries in observational analyses
Open accessAbstract
Many analyses of observational data are attempts to emulate a target trial. The emulation of the target trial may fail when researchers deviate from simple principles that guide the design and analysis of randomized experiments. We review a framework to describe and prevent biases, including immortal time bias, that result from a failure to align start of follow-up, specification of eligibility, and treatment assignment. We review some analytic approaches to avoid these problems in comparative effectiveness or safety research.
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- Authors
- Hernán, M. A., Sauer, B. C., Hernández-Díaz, S., Platt, R., & Shrier, I.
- Affiliations
- University of Utah (US)
- McGill University Health Centre (CA)
- Jewish General Hospital (CA)
- Venue
- Journal of Clinical Epidemiology
- Publisher
- Elsevier BV
- Published
- 2016-11
- Volume
- 79
- Pages
- 70-75
- ISSN
- 0895-4356 (ISSN-L)
- PMC
- PMC5124536
- OpenAlex
- W2404984931
- Cited by
- 1,097
- References
- 3
- Citations by year
- 2026: 272 · 2025: 197 · 2024: 181 · 2023: 138 · 2022: 100 · 2021: 89 · 2020: 54 · 2019: 28 · 2018: 13 · 2017: 20 · 2016: 4
- FWCI
- 21.95
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Clinical Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (5ul1tr001067-05)
- National Cancer Institute (P01CA134294, R35CA197449)
- National Center for Advancing Translational Sciences (UL1-TR001067)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- immortal time bias, target trial emulation, observational study design, treatment allocation, comparative effectiveness research, bias prevention
- MeSH terms
- Humans, Time Factors, Epidemiologic Research Design, Bias, Selection Bias, Comparative Effectiveness Research, Observational Studies as Topic
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