title: A threshold sample-enrichment approach in a clinical trial with heterogeneous subpopulations.
abstract: BACKGROUND
  Large comparative clinical trials usually target a wide-range of patients population in which subgroups exist according to certain patients' characteristics. Often, scientific knowledge or existing empirical data support the assumption that patients' improvement is larger among certain subgroups than others. Such information can be used to design a more cost-effective clinical trial.
  
  
  OBJECTIVE
  The goal of the article is to use such information to design a more cost-effective clinical trial.
  
  
  METHODS
  A two-stage sample-enrichment design strategy is proposed that begins with enrollment from certain subgroup of patients and allows the trial to be terminated for futility in that subgroup.
  
  
  RESULTS
  Simulation studies show that the two-stage sample-enrichment strategy is cost-effective if indeed the null hypothesis of no treatment improvement is true, as also so illustrated with data from a completed trial of calcium to prevent preeclampsia.
  
  
  CONCLUSIONS
  Feasibility of the proposed enrichment design relies on the knowledge prior to the start of the trial that certain patients can benefit more than others from the treatment. Prolonged accrual and longer-waited outcomes may hinder utilization of the proposed design.
  
  
  CONCLUSIONS
  The two-stage sample-enrichment approach borrows strength from treatment heterogeneity among target patients in a large-scale comparative clinical trial, and is more cost-effective if the treatment arms are indeed of no difference.
authors.affiliation: Biostatistics and Bioinformatics Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Rockville, MD 20852, USA. liua@mail.nih.gov
authors.forename: Aiyi
authors.initials: A
authors.lastname: Liu
authors.forename: Chunling
authors.initials: C
authors.lastname: Liu
authors.forename: Qizhai
authors.initials: Q
authors.lastname: Li
authors.forename: Kai F
authors.initials: KF
authors.lastname: Yu
authors.forename: Vivian W
authors.initials: VW
authors.lastname: Yuan
mesh_terms: D006801:Humans; D015233:Models, Statistical; D018579:Patient Selection; D011336:Probability; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D018401:Sample Size; D013223:Statistics as Topic / Q000379:methods*; D016896:Treatment Outcome