THE PERFORMANCE OF RANDOMIZATION METHODS IN CONSIDERATION OF PROGNOSTIC FACTORS FOR SMALL-SIZE CLINICAL TRIALS: A SIMULATION STUDY

The performance of randomization methods in consideration of the impact of a prognostic factor that has an interaction and baseline characteristics that have no effect on the outcome has not been clarified, especially for small sized clinical trials. We conducted numerical simulations to identify the difference in behaviour of the empirical power and the empirical type 1 error rate among some randomization methods and statistical analyses when we use a prognostic factor that has an interaction or baseline characteristics that have no effect on the outcome for small sized randomized controlled trials. The empirical power was higher when using a prognostic factor that had an interaction. Also, by using stratified blocked randomization (ST) or minimization (MI) with the multiple regression, the empirical power was further increased. On the other hand, the empirical power was lower when using baseline characteristics that had no effect on the outcome. We recommend conducting ST or MI, multiple regression and using a prognostic factor that has an interaction in small-size randomized controlled trials.