Properties of multiple intersection-union tests for multiple endpoints in combination therapy trials.
We consider intersection-union tests involving multiple endpoints in a combination drug trial, for which we control the familywise error rate in the strong sense using closed testing methods. Bonferroni-Holm, Simes-Hommel, and Resampling-Based methods all are considered in this context. Familywise error rate control heuristics are developed and evaluated using a simulation study that is specifically tailored to the intersection-union setting. Both Resampling-Based and Simes-Hommel uniformly outperform the Bonferroni-Holm. Using simulations of power, the choice of Simes-Hommel versus Resampling-Based is seen to depend on the particular alternative of interest. Because it is simpler and has generally good power, we recommend the Simes-Hommel intersection-union tests. The techniques are illustrated using real data from a clinical trial to evaluate a combination asthma therapy.
Westfall
P H
PH
Texas Tech University, Lubbock, USA.
Ho
S Y
SY
Prillaman
B A
BA
D000465:Algorithms; D018927:Anti-Asthmatic Agents / Q000627:therapeutic use; D001249:Asthma / Q000188:drug therapy; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004338:Drug Combinations; D004358:Drug Therapy / Q000706:statistics & numerical data*; D023381:Endpoint Determination / Q000706:statistics & numerical data*; D012107:Research Design
D018927:Anti-Asthmatic Agents; D004338:Drug Combinations