Statistics and Data Science Seminar
Dr. Mohammad F. Huque
CDER, FDA
Statistical Considerations in Planning and Testing for Multiple Endpoints in Clinical Trials
Abstract: In evaluating that a test treatment is safe and effective in treating a disease,
it is often necessary in clinical trials to answer more than one clinically
relevant question or to characterize a treatment effect in two or more
endpoints. This requires framing clinically relevant multiple hypotheses
involving multiple primary and secondary endpoints and treatment comparisons.
These multiple hypotheses can be statistically tested according to a strategy
that depends on the objectives of the trial and clinical considerations of the
disease and the treatment under study. However, such a statistical testing
strategy concerning multiple hypotheses involving multiple endpoints is fraught
with multiplicity issues, which if ignored can increase the chance of spurious
positive findings resulting in false inferences that an effect is shown when
there is really no such an effect. In interpreting results from a situation like
this, one is more likely to make a false conclusion about the benefit of the
test treatment because there are multiple opportunities to choose favorable
results from multiple analyses. Therefore, it is necessary that a study protocol
of the trial include a clear plan for addressing multiplicity issues and a
statistical testing strategy that is appropriate for a given benefit claim of
the study treatment. This presentation will examine some basic principles and
statistical considerations that can be helpful in better planning and testing of
multiple endpoint hypotheses in clinical trials.
Wednesday October 17, 2007 at 3:30 PM in SEO 712