|
Abstract:
|
In the analysis of adverse events of therapeutic treatments, often we would like to understand if different types of events tend to occur together within the same patients more or less frequently than the random occurrence, or less frequently. In risk and benefit evaluation, we are interested in evaluating if patients are more likely to be responders for in terms of both efficacy and safety in for certain therapies. In setting of multiple endpoints, treatment benefit could can also be evaluated by understanding if patients are more likely to respond to all or some endpoints simultaneously than independently. The current available statistical metrics may not be adequate for such quantification, such as the Venn Diagrams, conditional probabilities, as well as some metrics found in psychometrics. In this paper, we propose a simple statistical metrics that can quantify the dependency of events and has clear interpretation. We also present the estimation of the confidence intervals and evaluate the properties such as bias, variability and sample size requirement using simulations. Illustration of the use in clinical trial data will be provided.
|
