Why the study?
Data on eGFR slopes have primarily been reported in cohorts enriched for fast progression, leaving the heterogeneity of eGFR slopes across the spectrum of CKD poorly defined.
In a large CKD cohort, the average eGFR slope was low but varied considerably depending on CKD etiology and UACR, providing context for individual patient slope estimates.
eGFR slope heterogeneity by etiology and UACR warrants cautious individual interpretation; extends prior fast-progressor data to broad CKD spectrum.
Introduction The rate of decline in eGFR is increasingly recognized as a quantitative marker of chronic kidney disease (CKD) progression. However, data on eGFR slopes have mainly been reported in cohorts enriched for fast progression and the heterogeneity of eGFR slopes across the spectrum of CKD remains poorly defined. Methods In 5,214 participants of the German CKD (GCKD) study, we modeled eGFR slopes using per-protocol and clinical measurements. We used linear-mixed effects models, with eGFR slope as the outcome and baseline demographics as independent variables, to (i) describe eGFR slope heterogeneity, (ii) assess differences by CKD etiology, eGFR and UACR categories, sex and age, and (iii) determine associations of slopes with estimated eGFR decline (30%, 40%, and 57%) and observed endpoints (kidney failure with replacement therapy, mortality). Results On average 9 eGFR values/participant (IQR 7-12) over 6.5 years were used for slope calculation. The adjusted mean annual eGFR slope was -1.43mL/min/1.73m 2 . Slopes were similar across eGFR categories, but steeper with higher UACR. Faster eGFR decline was observed in participants of younger age and in those with polycystic or diabetic kidney disease. While eGFR slopes did not consistently differ by sex, women with diabetes as the leading cause of CKD had lower slopes than their male counterparts. A rapid annual decline (> 5 mL/min/1.73m 2 ) occurred in 4.3%, with variation in frequency by CKD cause and UACR. Conclusion In conclusion, while the average eGFR slope was low, it varied considerably, depending on CKD etiology and UACR. This data may help to put slope estimates in individual patients and defined subpopulations into perspective.
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Behning et al. (2025) studied this question.
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