Statistics and Data Science Seminar
Dr. Kooros Mahjoob
FDA
Dealing With Missing Values in Clinical Trials From Regulatory Perspectives
Abstract: In some randomized clinical trials, missing values arise due to patients'
discontinuation before the end of the trial. As a result, there will be no
value/measurement for those patients who dropped out for assessing efficacy at
the end of the trial. Such a phenomenon is typical in neurological and
psychiatric clinical trials; in fact, in some cases, there are over 40%
dropouts. Clearly, analyzing trials data sets that have missing values and then
drawing conclusions from the analysis results is a challenging task for FDA
statisticians. Dealing with missing values in clinical trials has a long
history, which goes back for over two decades. Lots of work, published papers
and technical notes have suggested methods to deal with the issue and have
talked about the utility of one method over the others. Nevertheless, the
reality is that there is no clear-cut solution to the problem. Often, in some
trials, missing values is a real problem from the regulatory perspective as to
how to make a decision on the drug approval.
This presentation will focus on framing the problem, discussing common
statistical methods used and the FDA's views on the methods. I will also discuss
the result of simulations, bootstrapping using data of actual trials, conducted
by FDA colleagues, in comparing the performances of different methods, and the
outlines of some new methods.
Wednesday November 7, 2007 at 3:30 PM in SEO 712