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Activity Number: 144
Type: Contributed
Date/Time: Monday, August 10, 2015 : 8:30 AM to 10:20 AM
Sponsor: Biopharmaceutical Section
Abstract #317488 View Presentation
Title: Modeling Framework for Longitudinal Tumor Size in Oncology Clinical Trials
Author(s): Tianle Hu* and Honglu Liu
Companies: Eli Lilly and Company and Eli Lilly and Company
Keywords: mixture model ; oncology clinical trials ; longitudinal data ; change in tumor size ; tumor growth profile
Abstract:

Change in tumor size (CTS) has been used in oncology studies as an endpoint for anti-tumor activity in patients with solid tumors. Typically, tumor size is measured at a fixed time interval until disease progression, generating longitudinal tumor size data. However, most analysis for CTS in practice has been focused on a single time point, say 8-week landmark CTS, resulting in a potential loss of information. In this presentation, we illustrate three modeling frameworks of tumor size: 1) Mixed Model Repeated Measures (MMRM); 2) tumor growth inhibition (TGI) model 3) Bayesian mixture piecewise linear model. Their performance is assessed through simulation and their applications in clinical trials are discussed and demonstrated through data from a large multi-center cancer trial in non-small cell lung cancer.


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

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