TY - JOUR
T1 - Joint Models of Longitudinal and Time-to-Event Data with More Than One Event Time Outcome: A Review
AU - Hickey, Graeme L.
AU - Philipson, Pete
AU - Jorgensen, Andrea
AU - Kolamunnage-dona, Ruwanthi
PY - 2018/1/31
Y1 - 2018/1/31
N2 - Methodological development and clinical application of joint models of longitudinal and time-to-event outcomes have grown substantially over the past two decades. However, much of this research has concentrated on a single longitudinal outcome and a single event time outcome. In clinical and public health research, patients who are followed up over time may often experience multiple, recurrent, or a succession of clinical events. Models that utilise such multivariate event time outcomes are quite valuable in clinical decision-making. We comprehensively review the literature for implementation of joint models involving more than a single event time per subject. We consider the distributional and modelling assumptions, including the association structure, estimation approaches, software implementations, and clinical applications. Research into this area is proving highly promising, but to-date remains in its infancy.
AB - Methodological development and clinical application of joint models of longitudinal and time-to-event outcomes have grown substantially over the past two decades. However, much of this research has concentrated on a single longitudinal outcome and a single event time outcome. In clinical and public health research, patients who are followed up over time may often experience multiple, recurrent, or a succession of clinical events. Models that utilise such multivariate event time outcomes are quite valuable in clinical decision-making. We comprehensively review the literature for implementation of joint models involving more than a single event time per subject. We consider the distributional and modelling assumptions, including the association structure, estimation approaches, software implementations, and clinical applications. Research into this area is proving highly promising, but to-date remains in its infancy.
KW - Joint models
KW - multivariate data
KW - longitudinal data
KW - time-to-event data
KW - recurrent events
UR - https://www.scopus.com/pages/publications/85041642890
U2 - 10.1515/ijb-2017-0047
DO - 10.1515/ijb-2017-0047
M3 - Article
SN - 1557-4679
VL - 14
JO - International Journal of Biostatistics
JF - International Journal of Biostatistics
IS - 1
ER -