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Registry-based randomized clinical trials—a new clinical trial paradigm
Abstract
Randomized clinical trials provide the foundation of clinical evidence to guide physicians in their selection of treatment options. Importantly, randomization is the only reliable method to control for confounding factors when comparing treatment groups. However, randomized trials have limitations, including the increasingly prohibitive costs of conducting adequately powered studies. Local and national regulatory requirements, delays in approval, and unnecessary trial processes have led to increased costs and decreased efficiency. Another limitation is that clinical trials involve selected patients who are treated according to protocols that might not represent real-world practice. A possible solution is registry-based randomized clinical trials. By including a randomization module in a large inclusive clinical registry with unselected consecutive enrolment, the advantages of a prospective randomized trial can be combined with the strengths of a large-scale all-comers clinical registry. We believe that prospective registry-based randomized clinical trials are a powerful tool for conducting studies efficiently and cost-effectively.
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Metadata
- Authors
- James, S., Rao, S. V., & Granger, C. B.
- Affiliations
- Uppsala University Hospital (SE)
- Duke Medical Center (US)
- Corresponding author
- James, Stefan
- Venue
- Nature Reviews Cardiology
- Published
- 2015-03-17
- Volume
- 12
- Issue
- 5
- Pages
- 312-316
- ISSN
- 1759-5002 (ISSN-L)
- 1759-5010
- OpenAlex
- W2056697517
- Cited by
- 331
- References
- 29
- Citations by year
- 2026: 12 · 2025: 29 · 2024: 33 · 2023: 34 · 2022: 32 · 2021: 46 · 2020: 33 · 2019: 36 · 2018: 35 · 2017: 20 · 2016: 17 · 2015: 3
- FWCI
- 4.19
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Reviews Cardiology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Keywords
- clinical registries, randomization, confounding adjustment, real-world practice, trial design limitations
- MeSH terms
- Cardiology, Humans, Registries, Research Design, Randomized Controlled Trials as Topic
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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