Published in:
Open Access 01-12-2014 | Research article
Fractional excretion of IgG in idiopathic membranous nephropathy with nephrotic syndrome: a predictive marker of risk and drug responsiveness
Published in: BMC Nephrology | Issue 1/2014
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Background
Treatment of idiopathic membranous nephropathy with nephrotic syndrome is still controversial. There is currently little known about the clinical use of renal biomarkers which may explain contradictory results obtained from clinical trials. In order to assess whether IgG-uria can predict the outcome in membranous nephropathy, we examined the value of baseline EF-IgG in predicting remission and progression of nephrotic syndrome.
Methods
In a prospective cohort of 84 (34 female) idiopathic membranous nephropathy patients with nephrotic syndrome we validated the ability of the clinically available urine biomarker, IgG, to predict the risk of kidney disease progression and the beneficial effect of immunosuppression with steroids and cyclophosphamide. The fractional excretion of IgG (FE-IgG) and α1-microglobulin (FE-α1m), urine albumin/creatinine ratio, and eGFR were measured at the time of kidney biopsy. Primary outcome was progression to end stage kidney failure or kidney function (eGFR) decline ≥ 50% of baseline. Patients were followed up for 7.2 ± 4.1 years (range 1–16.8).
Results
High FE-IgG (≥0.02) predicted an increased risk of kidney failure (Hazard Ratio, (HR) 8.2, 95%CI 1.0–66.3, p = 0.048) and lower chance of remission (HR 0.18, 95%CI 0.09–0.38, p < 0.001). The ten-year cumulative risk of kidney failure was 51.7% for patients with high FE-IgG compared to only 6.2% for patients with low FE-IgG. During the study, only 24% of patients with high FE-IgG entered remission compared to 90% of patients with low FE-IgG. Combined treatment with steroids and cyclophosphamide decreased the progression rate (–40%) and increased the remission rate (+36%) only in patients with high FE-IgG.
Conclusion
In idiopathic membranous nephropathy patients with nephrotic syndrome, FE-IgG could be useful for predicting kidney disease progression, remission, and response to treatment.