title: Adaptive designs for dose-finding in non-cancer phase II trials: influence of early unexpected outcomes.
abstract: BACKGROUND
  In non-cancer phase II trials, dose-finding trials are usually carried out using fixed designs, in which several doses including a placebo are randomly distributed to patients. However, in certain vulnerable populations, such as neonates or infants, there is an heightened requirement for safety, precluding randomization.
  
  
  OBJECTIVE
  To estimate the minimum effective dose of a new drug from a non-cancer phase II trial, we propose the use of adaptive designs like the Continual Reassessment Method (CRM). This approach estimates the dose closest to some target response, and has been shown to be unbiased and efficient in cancer phase I trials.
  
  
  METHODS
  Based on a motivating example, we point out the individual influence of first outliers in this setting. A weighted version of the CRM is proposed as a theoretical benchmark to control for these outliers. Using simulations, we illustrate how this approach provides further insight into the behavior of the CRM.
  
  
  RESULTS
  When dealing with low targets like a 10% failure rate, the CRM appears unable to rapidly overcome an early unexpected outcome. This behavior persisted despite changing the inference (Bayesian or likelihood), underlying dose-response model (though slightly improved using the power model), and the number of patients enrolled at each dose level.
  
  
  CONCLUSIONS
  The choices for initial guesses of failure rates, the vague prior for the model parameter, and the log-log shape of weights can appear somewhat arbitrary.
  
  
  CONCLUSIONS
  In phase II dose-finding studies in which failure targets are below 20%, the CRM appears quite sensitive to first unexpected outcomes. Using a power model for dose-response improves some behavior if the trial is started at the first dose level and includes at least three to five patients at the starting dose before applying the CRM allocation rule.
authors.affiliation: Biostatistical Department, U717 Inserm, AP-HP, Paris 7 University, Saint-Louis Hospital, 1 Avenue Claude Vellefaux, 75475 Paris Cedex 10, France. matthieu.resche-rigon@univ-paris-diderot.fr
authors.forename: Matthieu
authors.initials: M
authors.lastname: Resche-Rigon
authors.forename: Sarah
authors.initials: S
authors.lastname: Zohar
authors.forename: Sylvie
authors.initials: S
authors.lastname: Chevret
mesh_terms: D000732:Androstanols / Q000008:administration & dosage; D001499:Bayes Theorem; D015982:Bias; D017322:Clinical Trials, Phase II as Topic; D004305:Dose-Response Relationship, Drug; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D007442:Intubation, Intratracheal; D016013:Likelihood Functions; D016015:Logistic Models; D003473:Neuromuscular Nondepolarizing Agents / Q000008:administration & dosage; D016311:Outliers, DRG; D015203:Reproducibility of Results; D012107:Research Design; D000077123:Rocuronium; D017211:Treatment Failure
chemical_list: D000732:Androstanols; D003473:Neuromuscular Nondepolarizing Agents; D000077123:Rocuronium