616BMI and SBP impact on survival of dialytic patients: multivariate joint model approach

Abstract

Abstract Background Studies on impact of routine clinical parameters on mortality of patients on peritoneal dialysis (PD), especially among elderly, are inconsistent. Although association between body mass index (BMI) and systolic blood pressure (SBP) is well known, their joint role on PD patient evolution is not clear. We aimed to model the joint impact of BMI and SBP trajectories on a cohort of incident elderly PD patients. Methods Prospective multicenter cohort study with 674 patients. Repeated measurements were modeled by random effects multivariate linear model. For the time-to-event outcome, used Cox proportional hazards model with log-Gaussian frailty. Stochastic dependence is captured by allowing random effects of the linear model to be correlated with the frailty term of the survival model, allowing for different clinical interpretations. All sub-models were adjusted for age in years. Results Isolated current values effects of increased BMI and BPS showed both as protective factors (1% and 2% risk reduction, respectively, for each unitary increase). When jointly modeled BMI changed its effect to 5% risk reduction while BPS remained the same, showing great impacts on survival depending on the combination of trajectories. Conclusions Clinical parameters association and its impact on survival is complex, and estimation of isolated effects may provide biased survival curves leading to unrealistic prognosis. A multivariate joint modeling can be seen as a valuable tool for clinical protocols on patient evolution. Key message Modern clinical epidemiology must foster use of modern statistics