Clinical epidemiological analysis of cohort studies investigating the pathogenesis of kidney disease

Abstract

In recent years, large cohort studies of patients with chronic kidney disease (CKD) have been established all over the world. These studies have attempted to analyze the pathogenesis of CKD using a large body of published evidence. The design of cohort studies is characterized by the measurement of the exposure prior to the occurrence of the outcome, which has the advantage of clarifying the temporal relationship between predictors and outcomes and estimating the strength of the causal relationship between predictors and multiple outcomes. Recent advances in biostatistical analysis methods, such as propensity scores and risk prediction models, are facilitating causal inference using higher quality evidence with greater precision in observational studies. In this review, we will discuss clinical epidemiological research of kidney disease based on the analysis of observational cohort data sets, with a focus on our previous studies.

Keywords: Causal effect; Epidemiology; Observational study.

Fig. 1

Brief summary of study design. Abbreviations: IgAN immunoglobulin A nephropathy; eGFR estimated glomerular filtration rate; ESKD, end-stage kidney disease

Fig. 2

Graphical representation of NRI (A) and IDI (B) for disease events. The NRI plot shows the proportion of individuals reclassified to higher or lower risk after the addition of biomarkers to the clinical model. The IDI plot shows the mean predicted probability of disease events according to the prior (Model1) and novel (Mode2) models

Fig. 3

Schematic representation of the Instrumental variable method