The cholesterol, high-density lipoprotein, and glucose index and its derived indices predict diabetic kidney disease development and progression: evidence from two nationwide cohorts and a biopsy-proven clinical cohort

The Cholesterol, High-Density Lipoprotein, and Glucose (CHG) index is a recently proposed composite metric, but its utility in predicting the development and progression of diabetic kidney disease (DKD) remains insufficiently explored. This study aimed to evaluate the predictive value of the CHG index and its anthropometric-adjusted derivatives for DKD development and progression, comparing their performance with traditional surrogate markers of insulin resistance. We analyzed 10-year longitudinal data from the China Health and Retirement Longitudinal Study (CHARLS, 2011–2020), including 984 diabetic patients without baseline renal injury. Incident DKD risk was evaluated using Cox proportional hazards models and Kaplan–Meier analysis, while restricted cubic splines (RCS) assessed non-linear dose–response relationships. External validation utilized the cross-sectional National Health and Nutrition Examination Survey (NHANES 1999–2018). Furthermore, disease progression (estimated glomerular filtration rate eGFR < 60 mL/min/1.73 m2) was evaluated in an independent clinical cohort of 217 patients with biopsy-proven DKD. Discriminative ability was evaluated via Receiver Operating Characteristic (ROC) analyses. Subgroup and interaction analyses evaluated prognostic consistency across patient profiles. In CHARLS, elevated CHG-BMI independently predicted incident DKD in fully adjusted models (Quartile 3 HR = 2.19, P = 0.020), showing significant integrated discrimination improvement (IDI, P = 0.030) over traditional markers. Subgroup analyses revealed higher risk estimates for CHG-BMI in non-overweight and normolipidemic individuals (P for interaction < 0.05). NHANES analysis replicated these associations, identifying significant J-shaped trajectories for CHG and CHG-BMI. In the biopsy-proven cohort, CHG and CHG-BMI were independently associated with reduced eGFR (P < 0.05), unlike traditional markers. They yielded adjusted AUCs of 0.733 and 0.730 for predicting DKD progression. E-value analysis for unmeasured confounding was 4.81 for CHG-BMI (Q3). Significant interactions emerged between CHG-BMI and Renal Pathology Society (RPS) grades, with significant associations in classes IIa and IIb. The CHG index and CHG-BMI independently predict DKD development and progression, outperforming traditional insulin resistance markers. Both indices aid clinical risk stratification, with CHG-BMI specifically identifying elevated risks in early pathological stages and among individuals without overt metabolic comorbidities.