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Published in: Lifetime Data Analysis 2/2019

08-06-2018

New approaches for censored longitudinal data in joint modelling of longitudinal and survival data, with application to HIV vaccine studies

Authors: Tingting Yu, Lang Wu, Peter Gilbert

Published in: Lifetime Data Analysis | Issue 2/2019

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Abstract

In HIV vaccine studies, longitudinal immune response biomarker data are often left-censored due to lower limits of quantification of the employed immunological assays. The censoring information is important for predicting HIV infection, the failure event of interest. We propose two approaches to addressing left censoring in longitudinal data: one that makes no distributional assumptions for the censored data—treating left censored values as a “point mass” subgroup—and the other makes a distributional assumption for a subset of the censored data but not for the remaining subset. We develop these two approaches to handling censoring for joint modelling of longitudinal and survival data via a Cox proportional hazards model fit by h-likelihood. We evaluate the new methods via simulation and analyze an HIV vaccine trial data set, finding that longitudinal characteristics of the immune response biomarkers are highly associated with the risk of HIV infection.

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Metadata
Title
New approaches for censored longitudinal data in joint modelling of longitudinal and survival data, with application to HIV vaccine studies
Authors
Tingting Yu
Lang Wu
Peter Gilbert
Publication date
08-06-2018
Publisher
Springer US
Published in
Lifetime Data Analysis / Issue 2/2019
Print ISSN: 1380-7870
Electronic ISSN: 1572-9249
DOI
https://doi.org/10.1007/s10985-018-9434-7

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