Modelling heterogeneity in the progression of chronic kidney disease

Abstract

Cohort studies with comprehensive follow-up periods that track patients with chronic kidney disease (CKD) and gather extensive health data are important for understanding the diverse progression patterns of CKD. This review explores the potential of emerging analytical techniques that can be applied in addition to conventional analysis approaches to enhance CKD research by offering more detailed insights into disease progression. To maximize the insights available from CKD cohort data with extended follow-up, we examined two advanced approaches: analysis of disease trajectories and analysis of recurrent events. The analysis of trajectories examines the timing and relationships between events, uncovering progression patterns and identifying key events that could signal future outcomes. In contrast, the application of recurrent event analysis facilitates the examination of repeated occurrences of significant events, thereby providing a more nuanced understanding of the evolution of risk over time. Using data from the German Chronic Kidney Disease study, this review illustrates how these approaches can enhance conventional analyses. The application of these supplementary methodologies to CKD research has the potential to facilitate a transition towards a more personalized approach to patient care. The insights gained may inform the development of tailored treatment strategies and contribute to enhanced overall patient outcomes.