ReviewDrug safety2011
Is the large simple trial design used for comparative, post-approval safety research? A review of a clinical trials registry and the published literature.
Review in Drug safety, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Trial designs using real-world data: The changing landscape of the regulatory approval process.Pharmacoepidemiology and drug safety · 2020Review
- Tools and Methods for Real-World Evidence Generation: Pragmatic Trials, Electronic Consent, and Data Linkages.Rheumatic diseases clinics of North America · 2019Review
- Postmarketing studies for novel drugs approved by both the FDA and EMA between 2005 and 2010: a cross-sectional study.BMJ open · 2017Article
- Summarising the Evidence for Drug Safety: A Methodological Discussion of Different Meta-Analysis Approaches.Drug safety · 2017Article
- Causal inference methods to assess safety upper bounds in randomized trials with noncompliance.Clinical trials (London, England) · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Post-approval, observational drug safety studies face well known difficulties in controlling for confounding, particularly confounding by indication for drug use. A study design that addresses confounding by indication is the large simple trial (LST). LSTs are characterized by large sample sizes, often in the thousands; broad entry criteria consistent with the approved medication label; randomization based on equipoise, i.e. neither physician nor patient believes that one treatment option is superior; minimal, streamlined data collection requirements; objectively-measured endpoints (e.g. death, hospitalization); and follow-up that minimizes interventions or interference with normal clinical practice. In theory then, the LST is a preferred study design for drug and vaccine safety research because it controls for biases inherent to observational research while still providing results that are generalizable to 'real-world' use. To evaluate whether LSTs are used for comparative safety evaluation and if the design is, in fact, advantageous compared with other designs, we conducted a review of the published literature (1949 through 31 December 2010) and the ClinicalTrials.gov registry (2000 through 31 December 2010). Thirteen ongoing or completed safety LSTs were identified. The design has rarely been used in comparative drug safety research, which is due to the operational, financial and scientific hurdles of implementing the design. The studies that have been completed addressed important clinical questions and, in some cases, led to re-evaluation of medical practice. We conclude the design has demonstrated utility for comparative safety research of medicines and vaccines if the necessary scientific and operational conditions for its use are met.
Indexed as
Identifiers
21879776What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.