[Progress in research of risk prediction model for chronic kidney disease]

Chronic kidney disease (CKD) is an important global public health problem that greatly threatens population health. Application of risk prediction model is a crucial way for the primary prevention of CKD, which can stratify the risk for developing CKD and identify high-risk individuals for more intensive interventions. By now, more than twenty risk prediction models for CKD have been developed worldwide. There are also four domestic risk prediction models developed for Chinese population. However, none of these models have been recommended in clinical guidelines yet. The existing risk prediction models have some limitations in terms of outcome definition, predictors, strategies for handling missing data, and model derivation. In the future, the applications of emerging biomarkers and polygenic risk scores as well as advances in machine learning methods will provide more possibilities for the further improvement of the model.

[Prevalence of chronic kidney disease and its association with lifestyle factors in adults from 10 regions of China]

Objective: To investigate the distribution of chronic kidney disease (CKD) in participants from the China Kadoorie Biobank (CKB) study and evaluate the association between lifestyle risk factors and CKD. Methods: Based on the baseline survey data and follow-up data (as of December 31, 2018) of the CKB study, the differences in CKD cases' area and population distributions were described. Cox proportional hazards regression model was used to estimate the association between lifestyle risk factors and the risk of CKD. Results: A total of 505 147 participants, 4 920 cases of CKD were recorded in 11.26 year follow up with a incidence rate of 83.43/100 000 person-years. Glomerulonephropathy was the most common type. The incidence of CKD was higher in the urban area, men, and the elderly aged 60 years and above (87.83/100 000 person-years, 86.37/100 000 person-years, and 132.06/100 000 person-years). Current male smokers had an increased risk for CKD compared with non-smokers or occasional smokers (HR=1.18, 95%CI: 1.05-1.31). The non-obese population was used as a control group, both general obesity determined by BMI (HR=1.19, 95%CI: 1.10-1.29) and central obesity determined by waist circumference (HR=1.27, 95%CI: 1.19-1.35) were associated with higher risk for CKD. Conclusion: The risks for CKD varied with area and population in the CKB cohort study, and the risk was influenced by multiple lifestyle factors.