Histological classification of Japanese IgA nephropathy with a small number of glomeruli using Bayes’ theorem

Abstract

Abstract In Japan an original pathological classification of IgA glomerulonephritis was used for now, while Oxford classification of IgA glomerulonephritis was used in other countries. For proper classification, the Oxford and Japanese classifications require ≥ 8 and ≥ 10 glomeruli per biopsy, respectively. Here, we report how the glomerular count affects the Japanese classification of IgA glomerulonephritis using Bayesian probabilistic analysis in cross-sectional study. Ninety-nine patients diagnosed with IgA nephropathy were included in the study. To determine the accuracy of histological staging, we calculated the posterior probability using Bayes' theorem and adopted three model of prior distribution. First, the actual staging distribution was reclassified using the beta distribution(reclassified distribution). Second a model with the same distribution(actual distribution) as the actual staging was used. Third, a model assuming that all cases are equally distributed(equal distribution) was used. The median number of collected glomeruli was 12 (8–19). There were 33 cases (33%) wherein the glomerular count was ≤ 9. When only cases with ≥ 10 glomeruli were included, the median posterior probability was 91% (74–99) (actual distribution, 90% [74–98]; equal distribution, 85% [73–96]). Even among the 33 cases with ≤ 9 glomeruli, there were approximately 7 cases in which the posterior probability was ≥ 90% for each model. Using Bayesian probabilistic analysis, it was possible to evaluate the histologic classification of IgA nephropathy, even when the number of obtained glomeruli was ≤ 9.