Abstract
Diabetic kidney disease (DKD) represents a leading complication of diabetes, frequently progressing to end-stage renal disease (ESRD), which significantly impairs patients' quality of life and imposes substantial healthcare burdens. Consequently, early detection and intervention in DKD are paramount. The incorporation of surrogate endpoints in clinical trials has emerged as a pivotal strategy for assessing the efficacy of novel therapies, facilitating the reduction of trial duration and associated costs. Currently, the rate of change in estimated glomerular filtration rate (eGFR) and urinary albumin excretion, either independently or in combination, serve as reliable surrogate endpoints for evaluating DKD progression. Although novel biomarkers such as KIM-1 and TNFR2 are not yet recommended as standalone surrogate endpoints for DKD, they hold potential when used in combination with established markers, such as eGFR slope and urinary albumin change rate, to improve the prediction of ESRD risk. While omics-based indicators demonstrate promise in DKD research, their utility requires further validation, particularly through long-term follow-up and dynamic monitoring, to establish their effectiveness and clinical applicability. Future research should prioritize the validation and optimization of potential surrogate endpoints through long-term follow-up studies and large-scale cohorts.