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Cited by 1,646Advanced Causal Inference TechniquesStatistical Methods in EpidemiologyMenopause: Health Impacts and Treatments

Evaluating medication effects outside of clinical trials: new-user designs

Ray, W. A.·2003·American Journal of Epidemiology
DOI 10.1093/aje/kwg231
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Abstract

Recent clinical trials demonstrating that hormone replacement therapy (HRT) does not prevent coronary heart disease in women have again raised doubts concerning observational studies. Although much of the explanation probably lies in what might be called the "healthy HRT user" effect, another contributing factor may be that most observational studies included many prevalent users: women taking HRT for some time before study follow-up began. This practice can cause two types of bias, both of which plausibly may have contributed to the discrepancy between observational and randomized studies. First, prevalent users are "survivors" of the early period of pharmacotherapy, which can introduce substantial bias if risk varies with time, just as in studies of operative procedures that enroll patients after they have survived surgery. This article provides several examples of medications for which the hazard function varies with time and thus would be subject to prevalent user bias. Second, covariates for drug users at study entry often are plausibly affected by the drug itself. Investigators often do not adjust for these factors on the causal pathway, which may introduce confounding. A new-user design eliminates these biases by restricting the analysis to persons under observation at the start of the current course of treatment. This article thus argues that such designs should be used more frequently in pharmacoepidemiology.

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Crossref · 10.1093/aje/kwg231

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  • The prevalent user design used in that study may be associated with bias and may account for the non-detection of fibrate effect on pain.

    “used a prevalent user design (i.e. included participants who used fibrates at baseline) [62] that may be associated with bias [63] and may account for the non-detection of fibrate effect on pain.”

    From Fibrates as drugs with senolytic and autophagic activity for osteoarthritis therapy (2019) · cites this paper as [63]

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Authors
Ray, W. A.
Affiliations
Vanderbilt University (US)
Corresponding author
Ray, W. A.
ORCID
Ray, W. A.
Venue
American Journal of Epidemiology
Publisher
Oxford University Press (OUP)
Published
2003-11-01
Volume
158
Issue
9
Pages
915-920
ISSN
0002-9262 (ISSN-L)
DOI
10.1093/aje/kwg231
OpenAlex
W2164595809
Cited by
1,646
References
55
Citations by year
2026: 85 · 2025: 53 · 2024: 78 · 2023: 78 · 2022: 94 · 2021: 95 · 2020: 85 · 2019: 121 · 2018: 95 · 2017: 109 · 2016: 100 · 2015: 113 · 2014: 104 · 2013: 96 · 2012: 86
FWCI
16.77
Type
journal article
Language
en
Open access
closed
Locations
  • American Journal of Epidemiology (publishedVersion)
  • PubMed (publishedVersion)
Funders
Agency for Healthcare Research and Quality (HS 10384)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Menopause: Health Impacts and Treatments
Keywords
new-user design, hormone replacement therapy, coronary artery disease, bias in observational studies, pharmacoepidemiology
MeSH terms
Clinical Trials as Topic, Humans, Epidemiologic Research Design, Bias, Confounding Factors, Epidemiologic, Pharmacoepidemiology, Hormone Replacement Therapy

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