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Activity Number: 130 - Statistical Methods for Time-To-Event Data and Applications
Type: Contributed
Date/Time: Monday, July 29, 2019 : 8:30 AM to 10:20 AM
Sponsor: Biopharmaceutical Section
Abstract #304739
Title: Modeling the Impact of Dose Intervention on Time-To-Event Outcomes
Author(s): Amir Nikooienejad* and Yongming Qu
Companies: Eli Lilly and Company and Eli Lilly and Company
Keywords: Dose Intervention; Time-to-Event Outcome; Survival Data; Hazard Rate; Dose Tolerability
Abstract:

Dose titration is a common practice in clinical trials to improve tolerability for the drug. The idea is that by gradually increasing the dose at specific time points, the body may adapt itself to potential adverse effects of the molecule, such as nausea, vomiting and diarrhea. Different methods have been proposed for analyzing the impact of dose titration on the outcome of interest. However, most of them do not consider the dynamic effect of the dose titration over time but focus on the outcome at the end of the study. There is recent work that takes into account the longitudinal trend of the dose titration for a continuous outcome. In this research, we propose a method that investigates the same concept for time-to-event outcomes. In the proposed method, the titration concept is generalized to dose intervention and combination drugs, where the impact is modeled through hazard rate in proportional hazards model. Various simulation scenarios are used to evaluate the proposed method and its advantages.


Authors who are presenting talks have a * after their name.

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