Observer Agreement in the Scoring of the Activity and Chronicity Indexes of Lupus Nephritis

Abstract

The present study was designed to evaluate the observer reliability in the scoring of the activity and chronicity indexes, among three experienced pathologists, in renal biopsies from lupus nephritis (LN). Twenty-five renal biopsies of LN, were evaluated independently by three pathologists to assess the interobserver variability. For the intraobserver agreement, 5 biopsies were evaluated twice by each pathologist. The interobserver agreement for the scoring of the activity and chronicity indexes was 0.81 and 0.86, respectively. In the intraobserver agreement the same results were: for the pathologist 1,0.95 and 0.70; for the pathologist 2,0.91 and 0.55; for the pathologist 3,0.89 and 0.82. In conclusion the agreement for the scoring of the activity and chronicity indexes in biopsies from LN was excellent.

Evaluation of activity, chronicity and tubulointerstitial indices for childhood lupus nephritis

“…Our findings that clinicopathologic correlations were similar at biopsies 1 and 2 does suggest that biopsy interpretation was performed in a consistent manner, especially given that the pathologist was blind to the patients' clinical status. However, given the controversy in the literature as to inter-and intra-observer reliability of the NIH scoring system [30][31][32], future pediatric studies should evaluate these characteristics of the NIH index and the TIAI.…”

Concise semiquantitative histological scoring system for immunoglobulin A nephropathy

“…Kappa statistics were used to assess intra‐ and inter‐observer reproducibility of each pathological index. A value of κ greater than 0.75 was taken as an arbitrary index of excellent agreement beyond chance expectation, while a value of κ between 0.4 and 0.75 was regarded as fair to good concordance 19 . P < 0.05 was considered statistically significant.…”

Evaluation of the Classification Accuracy of the Kidney Biopsy Direct Immunofluorescence through Convolutional Neural Networks

“…Indeed, any medical imaging technique involving human reporting is conditioned by a significant interpretative subjectivity. This poor reproducibility has been repeatedly documented in the old kidney histopathological literature [26][27][28][29] and has been recently confirmed in studies concerning the application of Deep Learning in kidney pathology 1,2 . The indices of agreement between human pathologists vary according to the metrics used, the preparation of the specimen, the histological parameters assessed, and the kidney disease considered; overall, reported agreement rate between human kidney pathologists is fair to moderate with agreement ratio ranging between 0.3 and 0.6.…”