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PMID: 21478771 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't Review Systematic Review

N-of-1 trials in the medical literature: a systematic review.

Medical care ·Vol. 49 ·No. 8 ·2011-08-00 ·Pages 761-8

Gabler NB, Duan N, Vohra S, Kravitz RL

Abstract

N-of-1 trials (multiple crossover studies conducted in single individuals) may be ideal for determining individual treatment effects and as a tool to estimate heterogeneity of treatment effects (HTE) in a population. However, comprehensive data on n-of-1 trial methodology and analysis is lacking. We performed this study to describe n-of-1 trial characteristics, examine treatment changes resulting from n-of-1 trial participation, and to determine if trial reporting is adequate for estimating HTE. We undertook a systematic review of n-of-1 trials published between 1985 and December 2010. Included trials were those having individual treatment episodes as the unit of randomization and reporting individual-specific treatment effects. We abstracted trial characteristics, treatment change information, and analytic methods. We included 108 trials reporting on 2154 participants. Approximately half (49%) of the trials used a statistical cutoff to determine a superior treatment, whereas the remainder used a graphical comparison (25%) or a clinical significance cutoff (20%). Sixty-seven trials, reporting on 488 people, provided treatment change information: 54% of participants had subsequent treatment decisions consistent with the results of the trial, 8% had decisions inconsistent with trial results, and 38% had ambiguous results. Less than half of the trials (45%) reported adequate information to facilitate the calculation of HTE. N-of-1 trials are a useful tool for enhancing therapeutic precision in a range of conditions and should be conducted more often. To facilitate future meta-analysis, and the estimation of HTE, researchers reporting n-of-1 trial results should clearly describe individual data.

MeSH Terms
Clinical Trials as Topic Cross-Over Studies Humans Models, Statistical Research Design
Authors & Affiliations
4 authors, click to expand affiliations / ORCID
Gabler Nicole B
Center for Clinical Epidemiology and Biostatistics and Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104-6021, USA. gabler@upenn.edu
Duan Naihua
Vohra Sunita
Kravitz Richard L
Article Info
Journal
Medical care
Abbr.
Med Care
ISSN
1537-1948
Published
2011-08-00
Pages
761-8
Language
English
Region
United States
NLM ID
0230027
Subset
IM
Analysis Services
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