Multivariate recurrent events in the presence of multivariate informative censoring with applications to bleeding and transfusion events in myelodysplastic syndrome.

TitleMultivariate recurrent events in the presence of multivariate informative censoring with applications to bleeding and transfusion events in myelodysplastic syndrome.
Publication TypeJournal Article
Year of Publication2014
AuthorsZeng, Donglin, Joseph G. Ibrahim, Ming-Hui Chen, Kuolung Hu, and Catherine Jia
JournalJ Biopharm Stat
Volume24
Issue2
Pagination429-42
Date Published2014
ISSN1520-5711
KeywordsBlood Transfusion, Cohort Studies, Double-Blind Method, Follow-Up Studies, Hemorrhage, Humans, Multivariate Analysis, Myelodysplastic Syndromes, Recurrence
Abstract

We propose a general novel class of joint models to analyze recurrent events that has a wide variety of applications. The focus in this article is to model the bleeding and transfusion events in myelodysplastic syndrome (MDS) studies, where patients may die or withdraw from the study early due to adverse events or other reasons, such as consent withdrawal or required alternative therapy during the study. The proposed model accommodates multiple recurrent events and multivariate informative censoring through a shared random-effects model. The random-effects model captures both within-subject and within-event dependence simultaneously. We construct the likelihood function for the semiparametric joint model and develop an expectation-maximization (EM) algorithm for inference. The computational burden does not increase with the number of types of recurrent events. We utilize the MDS clinical trial data to illustrate our proposed methodology. We also conduct a number of simulations to examine the performance of the proposed model.

DOI10.1080/10543406.2013.860159
Alternate JournalJ Biopharm Stat
Original PublicationMultivariate recurrent events in the presence of multivariate informative censoring with applications to bleeding and transfusion events in myelodysplastic syndrome.
PubMed ID24605978
PubMed Central IDPMC3955007
Grant ListR01 CA082659 / CA / NCI NIH HHS / United States
R01 GM070335 / GM / NIGMS NIH HHS / United States
GM 70335 / GM / NIGMS NIH HHS / United States
P01CA142538 / CA / NCI NIH HHS / United States
P01 CA142538 / CA / NCI NIH HHS / United States
R01CA082659 / CA / NCI NIH HHS / United States
R37 GM047845 / GM / NIGMS NIH HHS / United States