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具有多个事件时间结局的纵向数据和事件发生时间数据的联合模型:综述

Joint Models of Longitudinal and Time-to-Event Data with More Than One Event Time Outcome: A Review.

作者信息

Hickey Graeme L, Philipson Pete, Jorgensen Andrea, Kolamunnage-Dona Ruwanthi

机构信息

Department of Biostatistics,University of Liverpool, Waterhouse Building, 1-5 Brownlow Street, Liverpool, L69 3GL, UK.

Department of Mathematics,Physics and Electrical Engineering, Northumbria University, Ellison Place, Newcastle upon Tyne, NE1 8ST, UK.

出版信息

Int J Biostat. 2018 Jan 31;14(1):ijb-2017-0047. doi: 10.1515/ijb-2017-0047.

Abstract

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.

摘要

在过去二十年中,纵向和事件发生时间结局的联合模型在方法学发展和临床应用方面有了显著增长。然而,这项研究大多集中在单一的纵向结局和单一的事件发生时间结局上。在临床和公共卫生研究中,随着时间推移接受随访的患者可能经常经历多种、反复或一系列临床事件。利用此类多变量事件发生时间结局的模型在临床决策中非常有价值。我们全面回顾了关于实施每个受试者涉及多个事件发生时间的联合模型的文献。我们考虑了分布和建模假设,包括关联结构、估计方法、软件实现和临床应用。该领域的研究已证明极具前景,但迄今为止仍处于起步阶段。

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