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Activity Number: 29 - Statistical Issues Specific to Therapeutic Areas, Power and Sample Size Calculations, and Trial Monitoring
Type: Contributed
Date/Time: Sunday, August 8, 2021 : 1:30 PM to 3:20 PM
Sponsor: Biopharmaceutical Section
Abstract #318308
Title: A Bayesian Network Meta-Analysis on Treatments of Brain Metastases in Patients with Non-Small Cell Lung Cancer
Author(s): Uma Siangphoe*
Companies: Johnson and Johnson
Keywords: Brain Metastases; Non-Small Cell Lung Cancer; Bayesian Network Meta-Analysis; Multiple Treatment Comparisons
Abstract:

Studies suggest brain metastases are a severe incident in patients with non-small cell lung cancer. Once the patients develop brain metastases, the tumor is not curable. With current treatments, patients live longer depending on numbers of brain metastases and types of tumors. Current options for treating brain metastases include surgery, radiotherapy alone, or in combination with chemotherapy or targeted therapy. Due to limited availabilities of control studies and small sample sizes of individual studies, several meta-analysis studies have been conducted. However, classical meta-analyses generally aim to assess direct comparisons between an intervention and a control. In this study, we conducted a Bayesian network meta-analysis to assess the effect of multiple treatment comparisons on the disease, the diagnosis, and the prognosis of brain metastases. Key assumptions, advantages, and limitations of the analyses will be evaluated and explored.


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

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