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Supplementary Material for: A Validation of the 2018 Revision of International Society of Nephrology/Renal Pathology Society Classification for Lupus Nephritis: A Cohort Study from China

posted on 22.04.2020, 06:26 by Tao J., Wang H., Yu X.-J., Tan Y., Yu F., Wang S.-X., Haas M., Glassock R.J., Zhao M.-H.
Background: A revision of the International Society of Nephrology/Renal Pathology Society (ISN/RPS) classification for lupus nephritis has been published in 2018. The current study aimed to verify the utility of this system. Materials and Methods: A total of 101 lupus nephritis patients from a large Chinese cohort who underwent renal biopsy in Peking University First Hospital were reevaluated by 2 renal pathologists, who had no knowledge of the clinical findings. The association between clinical data at the time of initial renal biopsy and follow-up and pathological features were further analyzed on all patients selected. Results: The mean age of the cohort was 33 years with a male/female ratio of 1:9, and a median follow-up period of 128 months. The presence and extent of mesangial hypercellularity, endocapillary hypercellularity, global and segmental glomerulosclerosis, neutrophil exudation/karyorrhexis, glomerular hyaline deposits, extracapillary proliferation (crescents), tubular atrophy/interstitial fibrosis, and interstitial inflammation were significantly correlated with several clinical renal injury indices (systemic lupus erythematosus disease activity index, serum creatinine value, proteinuria, and C3 level) at the time of biopsy. By multivariable Cox hazard analysis, fibrous crescents, tubular atrophy/interstitial fibrosis, and the modified National Institutes of Health chronicity index were independent risk factors for patients’ composite renal outcomes (hazard ratio [HR] 4.100 [95% CI 1.544–10.890], p = 0.005; HR 8.584 [95% CI 2.509–29.367], p = 0.001; and HR 3.218 [95% CI 1.138–9.099], p = 0.028; respectively). Conclusions: The 2018 revision of the ISN/RPS classification for lupus nephritis has utility for prediction of clinical renal outcomes.