title: Information time scales for interim analyses of randomized clinical trials.
abstract: Interim monitoring is a key component of randomized clinical trial design from both ethical and efficiency perspectives. In studies with time-to-event endpoints, timing of interim analyses is typically based on observing a pre-specified proportion of the total number of events required for the final analysis. While most randomized clinical trial designs pool events over the experimental and control arms in determining the analysis times, some designs use only the control-arm events for scheduling interim looks.
  
  
  
  To evaluate the performance of the pooled and control-arm-based interim monitoring approaches and to propose a new procedure, the earliest information time procedure, that combines the benefits of the two approaches.
  
  
  
  The analytical and logistical considerations for the procedures are presented. The methodology is illustrated on data from three published randomized clinical trials. The procedures are compared in a simulation study.
  
  
  
  The control-arm approach results in a slight inflation of the study type I error in one-sided randomized clinical trial designs. When the new treatment is no better than the control treatment, the pooled-arm approach results in, on average, earlier stopping times than the control-arm approach. When the new treatment works exceptionally well, the average stopping times under the control-arm approach are earlier than those under the pooled approach. The proposed earliest information time procedure is shown to result in stopping times corresponding to the best (earliest) of the two approaches over the entire range of alternatives.
  
  
  
  The earliest information time procedure may result in a slight inflation of the type I error (especially in small trials); when exact control of the type I error is required, it is necessary to use a simulation-based method to correct the inflation.
  
  
  
  In time-to-event settings, the earliest information time procedure is an attractive alternative to the pooled and control-arm approaches. Improving the timing of interim analyses helps to minimize patient exposure to inferior treatments and to accelerate dissemination of the study results.
authors.affiliation: Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA freidlinb@ctep.nci.nih.gov.
authors.forename: Boris
authors.initials: B
authors.lastname: Freidlin
authors.affiliation: SWOG Statistical Center, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
authors.forename: Megan
authors.initials: M
authors.lastname: Othus
authors.affiliation: Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA.
authors.forename: Edward L
authors.initials: EL
authors.lastname: Korn
mesh_terms: D016022:Case-Control Studies; D003627:Data Interpretation, Statistical; D003657:Decision Making; D057239:Early Termination of Clinical Trials; D023381:Endpoint Determination / Q000592:standards*; D006801:Humans; D018447:Medical Futility; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data; D012107:Research Design; D013997:Time Factors; D016896:Treatment Outcome
keywords: Futility; group sequential design; interim monitoring; maximum information design; spending function