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The active comparator, new user study design in pharmacoepidemiology: historical foundations and contemporary application.
Open accessAbstract
Better understanding of biases related to selective prescribing of, and adherence to, preventive treatments has led to improvements in the design and analysis of pharmacoepidemiologic studies. One influential development has been the "active comparator, new user" study design, which seeks to emulate the design of a head-to-head randomized controlled trial. In this review, we first discuss biases that may affect pharmacoepidemiologic studies and describe their direction and magnitude in a variety of settings. We then present the historical foundations of the active comparator, new user study design and explain how this design conceptually mitigates biases leading to a paradigm shift in pharmacoepidemiology. We offer practical guidance on the implementation of the study design using administrative databases. Finally, we provide an empirical example in which the active comparator, new user study design addresses biases that have previously impeded pharmacoepidemiologic studies.
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Metadata
- Authors
- Lund, J. L., Richardson, D. B., & Stürmer, T.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- Corresponding author
- Lund, Jennifer L.
- Venue
- Current Epidemiology Reports
- Published
- 2015-09-30
- Volume
- 2
- Issue
- 4
- Pages
- 221-228
- ISSN
- 2196-2995 (ISSN-L)
- PMC
- PMC4778958
- OpenAlex
- W1849521086
- Cited by
- 739
- References
- 42
- Citations by year
- 2026: 103 · 2025: 125 · 2024: 94 · 2023: 79 · 2022: 98 · 2021: 72 · 2020: 61 · 2019: 44 · 2018: 34 · 2017: 19 · 2016: 10
- FWCI
- 18.69
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Current Epidemiology Reports (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (2k12ca120780-16)
- National Institute on Aging (R01AG023178)
- National Cancer Institute (K12-CA120780)
- National Institute of Diabetes and Digestive and Kidney Diseases (P30DK124723)
- 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
- bias in observational studies, head-to-head comparison, administrative databases
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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