International Journal of Nephrology (Jan 2020)

Value of Urinary Neutrophil Gelatinase-Associated Lipocalin versus Conventional Biomarkers in Predicting Response to Treatment of Active Lupus Nephritis

  • Mohamed Abd El-Mohsen,
  • Ahmed Tawfik,
  • Walid Bichari,
  • Sahar Shawky,
  • Gamal Mady,
  • Mohamed Hassan

DOI
https://doi.org/10.1155/2020/8855614
Journal volume & issue
Vol. 2020

Abstract

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Introduction. Lupus nephritis (LN) affects almost two-thirds of systemic lupus erythematosus (SLE) patients. Despite initial aggressive therapy, up to 25% of patients with LN will progress to permanent renal damage. Conventional serum markers for LN lack the sensitivity of an ideal biomarker. Urinary neutrophil gelatinase-associated lipocalin (UNGAL) is an excellent biomarker for early diagnosis of acute kidney injury and predicting renal outcomes. Objective. To measure UNGAL among LN patients to correlate its levels with renal disease activity and to investigate its predictive performance in response to induction therapy. Patients and Methods. 40 SLE patients with biopsy-proven LN class III, IV, or V were randomly selected. The study was conducted in the internal medicine department and outpatient clinic in Ain Shams University Hospitals and completed after six months. UNGAL was measured at baseline, three-month follow-up, and after complete induction therapy. Results. In LN patients at baseline, the mean serum creatinine was 2.57 ± 0.96 mg/dL and the mean UNGAL was 33.50 ± 18.34 ng/dL. Mean UNGAL levels of complete response, partial response, and nonresponse groups were 14.48 ± 2.99 ng/mL, 34.49 ± 4.09 ng/mL, and 62.07 ± 14.44 ng/mL, respectively. Based on the ROC curve, we found a better performance of baseline UNGAL to discriminate the complete response group from partial and nonresponse groups to predict response to induction, outperforming conventional biomarkers. The area under the curve was 0.943, and the best cutoff level was 26.5 ng/mL (92.31% sensitivity and 88.89% specificity). Conclusion. UNGAL performed better than conventional biomarkers in predicting response to treatment of active LN.