title: Single-patient (n-of-1) trials: a pragmatic clinical decision methodology for patient-centered comparative effectiveness research.
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.
  
  
  METHODS
  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.
authors.affiliation: Division of Biostatistics, Department of Psychiatry, Columbia University, 1051 Riverside Drive, Unit 48, New York, NY 10032, USA. Naihua.Duan@Columbia.Edu
authors.forename: Naihua
authors.initials: N
authors.lastname: Duan
authors.forename: Richard L
authors.initials: RL
authors.lastname: Kravitz
authors.forename: Christopher H
authors.initials: CH
authors.lastname: Schmid
mesh_terms: D001499:Bayes Theorem; D002908:Chronic Disease / Q000628:therapy; D057186:Comparative Effectiveness Research / Q000379:methods*; D018592:Cross-Over Studies; D003661:Decision Support Techniques; D019317:Evidence-Based Medicine; D006801:Humans; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data*; D010358:Patient Participation; D018579:Patient Selection; D010865:Pilot Projects; D016032:Randomized Controlled Trials as Topic / Q000379:methods* / Q000706:statistics & numerical data
keywords: Adaptive trial; Bayesian method; Borrow from strength; Carryover effect; Crossover trial; Sequential trial; Washout