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Regression modelling of overall survival and progression-free survival

Authors: Chen, Yi;

Regression modelling of overall survival and progression-free survival

Abstract

There are three endpoints commonly used in oncology clinical trials, which are known as overall survival (OS), time to progression (TTP) and progression-free survival (PFS). Recently, PFS has become an important alternative endpoint to OS. In this thesis, both exponential and Weibull distributions are used to investigate the joint model of OS and PFS. Regression modelling will be introduced to investigate the effect of a treatment indicator on the distribution parameters for OS, TTP, and PFS. Both simulated data and real data will be used to investigate and demonstrate methods. The parameters of the models will be estimated by the maximum likelihood estimation. Furthermore, Wald tests will be performed to investigate covariate effects.

Country
Canada
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Keywords

regression model, overall survival, progression-free survival, joint model

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
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