Download click here and type title

International Biometric Society
A MODEL FOR THE JOINT EVOLUTION OF A LONGITUDINAL MARKER AND SURVIVAL;
APPLICATION TO GERONTOLOGY
Diklah M Geva1, Danit R Shahar1, Tamara B. Harris2, Sigal Tepper1,
Geert Molenberghs3, Michael Friger1
1. Dep.of Epidemiology, Faculty of Health Science, Ben Gurion Univ. of the Negev, Israel
2. Laboratory of Epidemiology, Demography, and Biometry,Bethesda, MD 20892, USA
3. Center for Statistics (CenStat), Univ. Hasselt, Agoralaan 1, B-3590 Diepenbeek, Belgium
Background: The growing interest in studies of longitudinal markers rather than survival per
se in gerontology along recent software developments makes Joint Longitudinal and Time to
Event Models (JM) a natural approach to the analysis of geriatric cohort studies. The aim of
this research was to apply such joint model to study strength-mobility association in the
presence of survival and to study the possible impact of different longitudinal-survival
structures on estimates.
Materials and methods: The Health-Aging-and-Body-Composition (HealthABC) study has
over 10 year follow-up of men and women aged 70-79. Analysis subset focused on muscle
strength and walking speed of n=2025 participants with 12099 observations having year2
and at least one additional measurements.
First we have grouped mobility trajectories according to heterogeneous mixed models of
muscle-strength and then, the R JM-Package was applied to model the joint distributions of
walking speed (longitudinal marker) and time to event (death or censoring) as function of
demographics (age, gender) and muscle strength class (MSC). A sensitivity analysis was
carried out by comparison of 10 models with different structures for the time survival
associations; linear-regression, glm-GEE, and JM with association forms of: value, lag
value, value & slope and slope alone, random effects of value & slope and random effects.
Results: The association under 10 different structures of longitudinal-survival-association
virtually had no difference in magnitude of resulted estimates. There is one important
exception, of smaller coverage of the parameter estimates by the linear regression and glmGEE. It appears that the association between MSC and walking speed is insensitive to the
form of the longitudinal-survival structure.
Concluding remarks: Our example shows that the longitudinal-survival association can be
modelled and explored using JM. We saw that although this association is highly significant
it had little or no impact on the longitudinal process parameter estimates of the main
predictor, MSC, on walking speed. Although, these types of models are somewhat complex
to apply, they offer many advantages in gerontology research because they relax
requirements of rigid longitudinal measurement timing, and it does account for the survival
process along the longitudinal evolution. Moreover, JM does not regard the survival process
merely as nuisance but actually allows studying the linkage of the two processes. In the
future, more examples and simulation work may shed further light on the boundaries of the
longitudinal-survival association within the JM framework.
Keywords: Joint Model, longitudinal analysis, survival analysis, gerontology, muscle
strength, walking speed
International Biometric Conference, Florence, ITALY, 6 – 11 July 2014