Multilevel Mixed-Effects Survival Parametrics Models: A Study of Cohorts from Brazil, Argentina and Italy of time to event from chronic diseases in elderly people

OSELLA ALBERTO; DÍAZ MP.; VAZ DE ARRUDA SILVEIRA L

Roma

Conferencia; 28 International Conference of the Int Society Environmental Epidemiology; 2016

International Society of Epidemiology

Ageing of populations has made the study of the elderly of great importance for social and health planning purposes. The aim of this study was to comparatively analyze time to event of populations coming from different cohort studies conducted in Brazil (Botucatu), Argentina (Córdoba) and Italy (Castellana Grotte). Chronic diseases such as diabetes mellitus, cardiovascular disease, obesity and cancer are prevalent diseases worldwide and are associated with aging. First, Kaplan-Meier (1958) method was applied in order to explore survival probabilities for each country and provide estimates of the net probability of death due to each variable studied. Second, as proportional hazard strong assumption of classical Cox model was not satisfied in the three cohorts, flexible parametric survival models (Royston and Parmar, 2002) were chosen and fitted separately for each country in order to estimate the effect of each variable studied. This survival model framework use natural cubic splines to model baseline. Finally, the structure of variability from each cohort was taken into account by using a multilevel survival model. The random-effects approach coupled with RP flexible models allowed us to experiment with several levels of random effects, including random coefficients of covariates. Conditional hazard ratios were estimated for continuous covariates and conditional predictions (specific to each group) means were compared. In Brazil, survival to death was associated with Cardiovascular Diseases (CVD), hazard ratio (HR) estimate equal to 1.68 (CI: 1.05, 2.69); no proportional-hazards (p=0.0158). In Argentina, time to cancer occurrence was associated with High Blood Pressure (HBP), HR estimate equal to 1.71 (CI:1.06,2.77); no proportional hazards for HBP. In Italy, HR estimates for Gender and Physical Activity were significant, no proportional hazards for Physical Activity. In all countries but in Italy, HBP was associated significantly with a shorter time to death. Whereas RP flexible models are suitable when proportional hazard are not satisfied, multilevel structure should be used when considering the survival time of different studies.