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N-of-1 Trials, Their Reporting Guidelines, and the Advancement of Open Science Principles.
- Source :
-
Harvard data science review [Harv Data Sci Rev] 2022; Vol. 4 (SI3). Date of Electronic Publication: 2022 Sep 08. - Publication Year :
- 2022
-
Abstract
- N-of-1 trials are multiple crossover trials done over time within a single person; they can also be done with a series of individuals. Their focus on the individual as the unit of analysis maintains statistical power while accommodating greater differences between patients than most standard clinical trials. This makes them particularly useful in rare diseases, while also being applicable across many health conditions and populations. Best practices recommend the use of reporting guidelines to publish research in a standardized and transparent fashion. N-of-1 trials have the SPIRIT extension for N-of-1 protocols (SPENT) and the CONSORT extension for N-of-1 trials (CENT). Open science is a recent movement focused on making scientific knowledge fully available to anyone, increasing collaboration, and sharing of scientific efforts. Open science goals increase research transparency, rigor, and reproducibility, and reduce research waste. Many organizations and articles focus on specific aspects of open science, for example, open access publishing. Throughout the trajectory of research (idea, development, running a trial, analysis, publication, dissemination, knowledge translation/reflection), many open science ideals are addressed by the individual-focused nature of N-of-1 trials, including issues such as patient perspectives in research development, personalization, and publications, enhanced equity from the broader inclusion criteria possible, and easier remote trials options. However, N-of-1 trials also help us understand areas of caution, such as monitoring of post hoc analyses and the nuances of confidentiality for rare diseases in open data sharing. The N-of-1 reporting guidelines encourage rigor and transparency of N-of-1 considerations for key aspects of the research trajectory.
Details
- Language :
- English
- ISSN :
- 2644-2353
- Volume :
- 4
- Issue :
- SI3
- Database :
- MEDLINE
- Journal :
- Harvard data science review
- Publication Type :
- Academic Journal
- Accession number :
- 38031562
- Full Text :
- https://doi.org/10.1162/99608f92.a65a257a