Population-Level Risk Factors for Kidney Outcomes in IgA Nephropathy: The CURE-CKD Registry.

RATIONALE & OBJECTIVE: Although IgA nephropathy (IgAN) therapies are advancing quickly, therapeutic interventions are hampered by a lack of kidney disease identification and risk assessment. The study aim was to use population-level data from health systems to identify IgAN and assess risks.

STUDY DESIGN

A longitudinal and real-world cohort study.

SETTING & PARTICIPANTS: Electronic health record data for patients ≥18 years old with IgAN at Providence and University of California Los Angeles health systems during 2016-2022.

PREDICTORS

Health insurance and care utilization along with age, gender, race, ethnicity, estimated glomerular filtration rate (eGFR), urine albumin/creatinine ratio (UACR) or urine protein/creatinine ratio (UPCR), diabetes, hypertension, and medications.

OUTCOMES

Time to first major adverse kidney event (MAKE): ≥40% eGFR decline; eGFR <15 mL/min/1.73 m2; administrative codes for kidney failure, dialysis, or transplant; and death.

ANALYTICAL APPROACH

Kaplan-Meier survival curves and Cox proportional hazards models.

RESULTS

Patients with IgAN (n = 2,571) were 50% (n = 1,277) women and 58 ± 18 (mean ± SD) years old. At baseline, eGFR was 78 ± 27 mL/min/1.73 m (chronic kidney disease epidemiologic 2021 equation); median UACR and UPCR were 166 (interquartile range 25-795) mg/g and 0.7 (0.2-1.8) g/g, respectively, among those with baseline measurements (n = 669). MAKE occurred in 22% of the cohort by 3 years. In Cox proportional hazards models, MAKE was predicted by noncommercial (Medicare or Medicaid) health insurance, hospitalization, more frequent outpatient encounters, lower eGFR, and a higher UACR or UPCR.

LIMITATIONS

Missingness, miscoding, and retrospective data.

CONCLUSIONS

Substantial loss of kidney function, kidney failure, and death were common events over a short period of time in patients with IgAN. Within health system populations, noncommercial health insurance and greater care utilization augmented risk prediction and could help to identify those who may benefit from closer monitoring and implementation of therapeutic interventions.