title: Adaptive designs based on the truncated product method.
abstract: BACKGROUND
  Adaptive designs are becoming increasingly important in clinical research. One approach subdivides the study into several (two or more) stages and combines the p-values of the different stages using Fisher's combination test.
  
  
  METHODS
  Alternatively to Fisher's test, the recently proposed truncated product method (TPM) can be applied to combine the p-values. The TPM uses the product of only those p-values that do not exceed some fixed cut-off value. Here, these two competing analyses are compared.
  
  
  RESULTS
  When an early termination due to insufficient effects is not appropriate, such as in dose-response analyses, the probability to stop the trial early with the rejection of the null hypothesis is increased when the TPM is applied. Therefore, the expected total sample size is decreased. This decrease in the sample size is not connected with a loss in power. The TPM turns out to be less advantageous, when an early termination of the study due to insufficient effects is possible. This is due to a decrease of the probability to stop the trial early.
  
  
  CONCLUSIONS
  It is recommended to apply the TPM rather than Fisher's combination test whenever an early termination due to insufficient effects is not suitable within the adaptive design.
authors.affiliation: Institute for Medical Informatics, Biometry and Epidemiology, University of Duisburg-Essen, Hufelandstr. 55, D-45122 Essen, Germany. markus.neuhaeuser@medizin.uni-essen.de
authors.forename: Markus
authors.initials: M
authors.lastname: Neuhäuser
authors.forename: Frank
authors.initials: F
authors.lastname: Bretz
mesh_terms: D003627:Data Interpretation, Statistical; D004305:Dose-Response Relationship, Drug; D004341:Drug Evaluation / Q000379:methods / Q000706:statistics & numerical data; D023381:Endpoint Determination / Q000379:methods; D006801:Humans; D015233:Models, Statistical; D011336:Probability; D016032:Randomized Controlled Trials as Topic / Q000379:methods* / Q000706:statistics & numerical data; D018401:Sample Size