Modeling Biomarker Variability in Joint Analysis of Longitudinal and Survival Data

报告题目:Modeling Biomarker Variability in Joint Analysis of Longitudinal and Survival Data

报告专家:Professor Jianxin Pan (Beijing Normal University and BNU-HKBU United International College)




The role of visit-to-visit variability of biomarker in predicting related disease has been recently recognized in medical science. Existing measures of biological variability are criticized for being entangled with random variability resulted from measurement error or being unreliable due to a limited number of measurements for each individual. We propose a new measure to quantify the biological variability of biomarker by evaluating the fluctuation of each individual-specific trajectory behind longitudinal processes. Given a mixed-effects model for longitudinal data with the mean function over time specified by cubic splines, the proposed variability measure can be expressed mathematically as a quadratic form of random effects. A Cox-type model is proposed for time-to-event data by incorporating the defined variability as well as the current level of the underlying longitudinal trajectory as covariates, which constitutes the joint modelling framework. Asymptotic properties of maximum likelihood estimators are established for the new joint model. Parameter estimation is implemented via an EM algorithm with fully exponential Laplace approximation to reduce the computation burden due to the increasing dimension of random effects. Simulation studies are conducted to reveal the advantage of the joint modelling method over the two-stage method. We apply the proposed model to investigate the effects of systolic blood pressure variability on cardiovascular events by analyzing an elderly trial data, which motivates actually this research work.


Professor Jianxin Pan holds a joint Chair Professorship of Beijing Normal University and Beijing Normal University-Hong Kong Baptist University United International College. He was a Chair Professor of Statistics in the University of Manchester, United Kingdom, between 2006 and 2021. 

Professor Jianxin Pan’s research interests include statistical modeling, statistical learning and data science, with application to medicine, public health, finance, and industry. He has published over 130 research articles in journals of statistical sciences and multidisciplinary research fields, and 3 research monographs with Springer and Science Press. He was awarded funding from various research councils of the UK and EU.

Professor Jianxin Pan is a Turing Fellow of the Alan Turing Institute for Data Science and Artificial Intelligence in the UK, Fellow of the Royal Statistical Society, and Elected Member of the International Statistical Institute. He was the Chair of the Royal Statistical Society Manchester Group and has been serving as Associate Editor for several statistical journals, including Biometrics (2008-2018), Biostatistics and Epidemiology (2013-), Biometrical Journal (2016-), Journal of Multivariate Analysis (2019-) and Electronic Journal of Statistics (2022-).