Adaptive increase in sample size when interim results are promising: a practical guide with examples

Stat Med. 2011 Dec 10;30(28):3267-84. doi: 10.1002/sim.4102. Epub 2010 Nov 30.


This paper discusses the benefits and limitations of adaptive sample size re-estimation for phase 3 confirmatory clinical trials. Comparisons are made with more traditional fixed sample and group sequential designs. It is seen that the real benefit of the adaptive approach arises through the ability to invest sample size resources into the trial in stages. The trial starts with a small up-front sample size commitment. Additional sample size resources are committed to the trial only if promising results are obtained at an interim analysis. This strategy is shown through examples of actual trials, one in neurology and one in cardiology, to be more advantageous than the fixed sample or group sequential approaches in certain settings. A major factor that has generated controversy and inhibited more widespread use of these methods has been their reliance on non-standard tests and p-values for preserving the type-1 error. If, however, the sample size is only increased when interim results are promising, one can dispense with these non-standard methods of inference. Therefore, in the spirit of making adaptive increases in trial size more widely appealing and readily implementable we here define those promising circumstances in which a conventional final inference can be performed while preserving the overall type-1 error. Methodological, regulatory and operational issues are examined.

MeSH terms

  • Acute Coronary Syndrome / drug therapy
  • Algorithms
  • Bias
  • Clinical Trials, Phase III as Topic / statistics & numerical data*
  • Computer Simulation
  • Endpoint Determination
  • Epidemiologic Research Design*
  • Humans
  • Models, Statistical*
  • Randomized Controlled Trials as Topic / statistics & numerical data
  • Sample Size
  • Schizophrenia / drug therapy
  • United States
  • United States Food and Drug Administration