Sample size determination for controlling the upper confidence limit of incidence rate of a binomial endpoint.
Assume that in a comparative clinical study the primary endpoint is a binary event, such as life or death. A new treatment or therapy is tested for a significant reduction of the incidence of the binary event compared with a control group. Another objective is to ensure that the incidence in the new treatment group is below some clinically acceptable value. This is done by calculating the exact upper 95% confidence limit for the probability of the event. The study is considered successful if the upper confidence limit is lower than a historical threshold, as well as if there is a significant reduction in the incidence of the event by the new treatment. In this article, we provide an exact method for calculating the sample size so that there will be adequate power to ensure that the exact upper confidence limit is below the threshold. Based on this we can design a study to achieve both objectives.
Shen
L Z
LZ
Biostatistics, Amylin Pharmaceuticals, Inc., San Diego, California, USA.
D016010:Binomial Distribution; D002986:Clinical Trials as Topic / Q000379:methods*; D016001:Confidence Intervals; D015994:Incidence; D008432:Mathematical Computing; D018401:Sample Size; D013223:Statistics as Topic / Q000379:methods*