title: Preference-adaptive randomization in comparative effectiveness studies.
abstract: BACKGROUND
  Determination of comparative effectiveness in a randomized controlled trial requires consideration of an intervention's comparative uptake (or acceptance) among randomized participants and the intervention's comparative efficacy among participants who use their assigned intervention. If acceptance differs across interventions, then simple randomization of participants can result in post-randomization losses that introduce bias and limit statistical power.
  
  
  METHODS
  We develop a novel preference-adaptive randomization procedure in which the allocation probabilities are updated based on the inverse of the relative acceptance rates among randomized participants in each arm. In simulation studies, we determine the optimal frequency with which to update the allocation probabilities based on the number of participants randomized. We illustrate the development and application of preference-adaptive randomization using a randomized controlled trial comparing the effectiveness of different financial incentive structures on prolonged smoking cessation.
  
  
  RESULTS
  Simulation studies indicated that preference-adaptive randomization performed best with frequent updating, accommodated differences in acceptance across arms, and performed well even if the initial values for the allocation probabilities were not equal to their true values. Updating the allocation probabilities after randomizing each participant minimized imbalances in the number of accepting participants across arms over time. In the smoking cessation trial, unexpectedly large differences in acceptance among arms required us to limit the allocation of participants to less acceptable interventions. Nonetheless, the procedure achieved equal numbers of accepting participants in the more acceptable arms, and balanced the characteristics of participants across assigned interventions.
  
  
  CONCLUSIONS
  Preference-adaptive randomization, coupled with analysis methods based on instrumental variables, can enhance the validity and generalizability of comparative effectiveness studies. In particular, preference-adaptive randomization augments statistical power by maintaining balanced sample sizes in efficacy analyses, while retaining the ability of randomization to balance covariates across arms in effectiveness analyses.
  
  
  BACKGROUND
  ClinicalTrials.gov, NCT01526265; 31 January 2012.
authors.affiliation: Department of Biostatistics and Epidemiology, University of Pennsylvania, 423 Guardian Drive, Philadelphia, 19104, PA, USA. bcfrench@upenn.edu.
authors.forename: Benjamin
authors.initials: B
authors.lastname: French
authors.affiliation: Department of Statistics, University of Pennsylvania, 3730 Walnut Street, Philadelphia, 19104, PA, USA. dsmall@wharton.upenn.edu.
authors.forename: Dylan S
authors.initials: DS
authors.lastname: Small
authors.affiliation: Department of Statistics, University of Pennsylvania, 3730 Walnut Street, Philadelphia, 19104, PA, USA. julnovak@wharton.upenn.edu.
authors.forename: Julie
authors.initials: J
authors.lastname: Novak
authors.affiliation: Department of Biostatistics and Epidemiology, University of Pennsylvania, 423 Guardian Drive, Philadelphia, 19104, PA, USA. kasau@upenn.edu.
authors.forename: Kathryn A
authors.initials: KA
authors.lastname: Saulsgiver
authors.affiliation: Department of Biostatistics and Epidemiology, University of Pennsylvania, 423 Guardian Drive, Philadelphia, 19104, PA, USA. mharhay@upenn.edu.
authors.forename: Michael O
authors.initials: MO
authors.lastname: Harhay
authors.affiliation: Department of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, 19104, PA, USA. asch@wharton.upenn.edu.|Department of Health Care Management, University of Pennsylvania, 3641 Locust Walk, Philadelphia, 19104, PA, USA. asch@wharton.upenn.edu.|Department of Medical Ethics and Health Policy, University of Pennsylvania, 3401 Market Street, Philadelphia, 19104, PA, USA. asch@wharton.upenn.edu.|Center for Health Equity Research and Promotion, Philadelphia Veterans Affairs Medical Center, 3900 Woodland Avenue, Philadelphia, 19104, PA, USA. asch@wharton.upenn.edu.
authors.forename: David A
authors.initials: DA
authors.lastname: Asch
authors.affiliation: Department of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, 19104, PA, USA. volpp70@exchange.upenn.edu.|Department of Health Care Management, University of Pennsylvania, 3641 Locust Walk, Philadelphia, 19104, PA, USA. volpp70@exchange.upenn.edu.|Department of Medical Ethics and Health Policy, University of Pennsylvania, 3401 Market Street, Philadelphia, 19104, PA, USA. volpp70@exchange.upenn.edu.|Center for Health Equity Research and Promotion, Philadelphia Veterans Affairs Medical Center, 3900 Woodland Avenue, Philadelphia, 19104, PA, USA. volpp70@exchange.upenn.edu.
authors.forename: Kevin G
authors.initials: KG
authors.lastname: Volpp
authors.affiliation: Department of Biostatistics and Epidemiology, University of Pennsylvania, 423 Guardian Drive, Philadelphia, 19104, PA, USA. shalpern@exchange.upenn.edu.|Department of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, 19104, PA, USA. shalpern@exchange.upenn.edu.|Department of Medical Ethics and Health Policy, University of Pennsylvania, 3401 Market Street, Philadelphia, 19104, PA, USA. shalpern@exchange.upenn.edu.
authors.forename: Scott D
authors.initials: SD
authors.lastname: Halpern
mesh_terms: D006801:Humans; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D016540:Smoking Cessation