Cure Glomerulonephropathy Pathology Classification and Core Scoring Criteria, Reproducibility, and Clinicopathologic Correlations

INTRODUCTION: Cure Glomerulonephropathy (CureGN) is an observational cohort study of patients with minimal change disease (MCD), focal segmental glomerulosclerosis (FSGS), membranous nephropathy (MN), or IgA nephropathy. We developed a conventional, consensus-based scoring system to document pathologic features for application across multiple pathologists and herein describe the protocol, reproducibility, and correlation with clinical parameters at biopsy. METHODS: Definitions were established for glomerular, tubular, interstitial, and vascular lesions evaluated semiquantitatively using digitized light microscopy slides and electron micrographs, and reported immunofluorescence. Cases with curated pathology materials as of April 2019 were scored by a randomly assigned pathologist, with at least 10% of cases scored by a second pathologist. Scoring reproducibility was assessed using Gwet’s agreement coefficient (AC)1 statistic and correlations with clinical variables were performed. RESULTS: Of 800 scored biopsies (134 MCD, 194 FSGS, 206 MN, 266 IgA), 94 were scored twice (11.8%). Of 60 pathology features, 46 (76.7%) demonstrated excellent (AC1>0.8), and 12 (20.0%) had good (AC1 0.6–0.8) reproducibility. Mesangial hypercellularity scored as absent, focal, or diffuse had moderate reproducibility (AC1 = 0.58), but good reproducibility (AC1 = 0.71) when scored as absent or focal versus diffuse. The percent glomeruli scored as no lesions had fair reproducibility (AC1 = 0.34). Strongest correlations between pathologic features and clinical characteristics at biopsy included interstitial inflammation, interstitial fibrosis, and tubular atrophy with estimated glomerular filtration rate, foot process effacement with urine protein/creatinine ratio, and active crescents with hematuria. CONCLUSIONS: Most scored pathology features showed excellent reproducibility, demonstrating consistency for these features across multiple pathologists. Correlations between certain pathologic features and expected clinical characteristics show the value of this approach for future studies on clinicopathologic correlations and biomarker discovery.