ArticleStatistics in biosciences2017
N-of-1 Design and Its Applications to Personalized Treatment Studies.
Article in Statistics in biosciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Article
- A Discussion on Different Approaches for Prescribing Physical Interventions - Four Roads Lead to Rome, but Which One Should We Choose?Journal of personalized medicine · 2020Article
- Citizen Health Science: Foundations of a New Data Science Arena.International journal of population data science · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
N-of-1 trial is a type of clinical trial which has been applied in chronic recurrent conditions that require long-term non-curative treatment. In this type of trials, each patient will be randomly assigned to one of the treatment sequences and repeatedly crossed over two or more treatments of interests. Through this cross-comparing method (cross-over phase), investigator can identify an optimal treatment (medicine or therapy) for the patient and treat the patient with the optimal treatment in an extension phase. This design could efficiently reduce the placebo effect, which is often seen in clinical trials, and maximize the true treatment effect. This type of design has been used in some traditional Chinese medicine (TCM) clinical trials lately. However, it brings some challenges for collecting and analyzing the data. Research on statistical methodology of this type of design is rarely found in the literature. The goal of this research is to discuss the application of the N-of-1 design to personalized treatment studies. We will demonstrate a real study conducted in TCM and present some theoretical and simulation results.
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What 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.