Considerations in testing treatment effects on transient event driven health status changes measured by patient...

Many treatments and drugs are intended to reduce the occurrence of negative events of interest, control the severity of the events, accelerate recovery from the events, or a combination of these effects. While assessing the clinical effect is typically the primary objective of a trial, testing the treatment effect on the health status of patients based on patient reported outcome (PRO) can be a useful component in determining the value of a treatment. Analysis of PROs in this setting, however, face the following challenges: the PRO value immediately after the event occurrence is often not captured, and the effect of the event on health status measured by the PRO is transient as subjects recover over time. Therefore, traditional statistical methods used to assess treatment effects suffer from low power for PROs. In this manuscript, we apply a kernel smoothing technique to estimate before- and after-event PRO values. We also propose new test outcomes based on observed and estimated PRO values and evaluate tests that focus on the tail distributions. We demonstrate that the tail distribution tests using the new outcomes can achieve high power under certain conditions.