Longitudinal analysis identifies eGFR slope as a predictor of kidney outcomes in IgA nephropathy, suggesting clinical utility.
Background and hypothesis In IgA nephropathy (IgAN), early surrogate markers that reflect disease progression are critical for understanding long-term outcomes. While prior studies have suggested a potential role for eGFR slope, its validity as a surrogate endpoint requires further validation. We here investigated the association between longitudinal changes in eGFR and kidney outcomes in a large Japanese IgAN cohort. Methods Patients with biopsy-confirmed IgAN enrolled in the Japan IgA Nephropathy Cohort Study (J-IGACS) were analyzed. Individual eGFR slopes were estimated using a linear mixed-effects model. The association between eGFR slope and a composite kidney outcome, defined as a ≥ 40% decline in eGFR or the initiation of kidney replacement therapy, was assessed using joint modeling of longitudinal and survival data, adjusting for clinical and histopathological covariates, including current eGFR levels. Results During a median follow-up of 6 years in 937 patients (mean age 39 years; 51% male), 78 patients (8.3%) reached the composite kidney endpoint. Joint modeling analysis demonstrated that a steeper decline in eGFR slope was significantly associated with a higher risk of adverse kidney outcomes (hazard ratio per 1-standard deviation eGFR slope decrease [i.e. 0.31 mL/min/1.73 m²/year steeper decline], 1.82; P < 0.001). The association remained statistically significant in sensitivity analyses restricted to patients who had already received treatment at baseline, although the effect size was modestly attenuated. Similar results were observed in an additional sensitivity analysis restricted to patients with at least five available eGFR measurements. Conclusion Using joint modeling, we demonstrated that eGFR slope provides prognostic information beyond current eGFR levels in patients with IgAN. Our findings support the use of eGFR slope as a reliable surrogate endpoint for clinical trials and risk stratification in IgAN.
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Sasaki et al. (2026) studied this question.
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