Cited by 239Statistical Methods in Clinical TrialsAdvanced Causal Inference TechniquesMeta-analysis and systematic reviews

Single-patient (n-of-1) trials: A pragmatic clinical decision methodology for patient-centered comparative effectiveness research

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Duan, Naihua, Kravitz, Richard L., Schmid, Christopher H.·2013·Journal of Clinical Epidemiology

Abstract

OBJECTIVE: To raise awareness among clinicians and epidemiologists that single-patient (n-of-1) trials are potentially useful for informing personalized treatment decisions for patients with chronic conditions. STUDY DESIGN AND SETTING: We reviewed the clinical and statistical literature on methods and applications of single-patient trials and then critically evaluated the needs for further methodological developments. RESULTS: Existing literature reports application of 2,154 single-patient trials in 108 studies for diverse clinical conditions; various recent commentaries advocate for wider application of such trials in clinical decision making. Preliminary evidence from several recent pilot acceptability studies suggests that single-patient trials have the potential for widespread acceptance by patients and clinicians as an effective modality for increasing the therapeutic precision. Bayesian and adaptive statistical methods hold promise for increasing the informational yield of single-patient trials while reducing participant burden, but are not widely used. Personalized applications of single-patient trials can be enhanced through further development and application of methodologies on adaptive trial design, stopping rules, network meta-analysis, washout methods, and methods for communicating trial findings to patients and clinicians. CONCLUSIONS: Single-patient trials may be poised to emerge as an important part of the methodological armamentarium for comparative effectiveness research and patient-centered outcomes research. By permitting direct estimation of individual treatment effects, they can facilitate finely graded individualized care, enhance therapeutic precision, improve patient outcomes, and reduce costs.

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References 44 · Cited by 239

Authors
Duan, N., Kravitz, R. L., & Schmid, C. H.
Affiliations
  • Columbia University (US)
  • University of California, Davis (US)
  • Brown University (US)
Corresponding author
Duan, Naihua
Venue
Journal of Clinical Epidemiology
Publisher
Elsevier BV
Published
2013-08
Volume
66
Issue
8
Pages
S21-S28
ISSN
0895-4356 (ISSN-L)
OpenAlex
W1974781686
Cited by
239
References
44
Citations by year
2026: 13 · 2025: 18 · 2024: 12 · 2023: 11 · 2022: 36 · 2021: 20 · 2020: 17 · 2019: 23 · 2018: 20 · 2017: 18 · 2016: 13 · 2015: 23 · 2014: 12 · 2013: 2
FWCI
3.24
Type
journal article
Language
en
Open access
Locations
  • Journal of Clinical Epidemiology (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
National Institutes of Health (P30 MH090322, R01 MH079387, R01 CA140419, 1 R01 NR013938, UL1TR000002)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Keywords
single-patient trials, N-of-1 trials, personalized medicine, individual treatment effects, clinical decision-making, chronic disease, Bayesian analysis, adaptive trial design, stopping rules, network meta-analysis, patient-centered outcomes research, comparative effectiveness research
MeSH terms
Bayes Theorem, Chronic Disease, Decision Support Techniques, Humans, Patient Participation, Pilot Projects, Randomized Controlled Trials as Topic, Outcome Assessment, Health Care, Patient Selection, Cross-Over Studies, Evidence-Based Medicine, Comparative Effectiveness Research

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