ABSTRACT
In clinical trials, selection of appropriate study endpoints is critical for an accurate and reliable evaluation of effectiveness of a test treatment under investigation. In practice, however, there are usually multiple endpoints available for measurement of disease status and/or therapeutic effect of the test treatment under study. For example, in cancer clinical trials, overall survival, response rate, and/or time to disease progression are usually considered as primary clinical endpoints for evaluation of effectiveness of the test treatment under investigation. Once the study endpoints have been selected, sample size requirement for achieving a desired power can then be determined. However, different study endpoints may result in different sample size requirement. In practice, it is usually not clear which study endpoint can best inform the disease status and measure the treatment effect. Moreover, different study endpoints may not translate one another although they may be highly correlated one another. In this chapter, a therapeutic index based on a utility function to combine all study endpoints is proposed. The developed therapeutic index will fully utilize all the information collected via the available study endpoints for an overall assessment of the effectiveness of the test treatment under investigation. Statistical properties and performances of the proposed therapeutic index are evaluated both theoretically and via clinical trial simulations.
