Segmental Glomerulosclerosis Subclassification in the Oxford Classification System (MEST-C) Improves the...

Background: Early external validation studies demonstrated the robust and consistent predictive performance of the International IgA Nephropathy Prediction Tool (IIgAN-PT) across diverse ethnic populations. However, emerging evidence suggests that, in contemporary cohorts of patients with IgA nephropathy, the IIgAN-PT increasingly tends to overestimate the risk of adverse renal outcomes. Subclassification of segmental glomerulosclerosis (S lesions) in the Oxford Classification system (MEST-C) could identify high-risk IgAN patients, with evidence that different S subclassifications respond differently to treatment. Our study aimed to evaluate the predictive performance of the IIgAN-PT in a contemporary Chinese external validation cohort and to optimize its prognostic accuracy by incorporating the most severe and prevalent pathological subclassification of S lesions, NOS⁺Adh⁺, into the original model. Methods: A total of 746 Chinese patients were included with biopsy-proven IgAN in this study. Major adverse kidney events (MAKEs) were defined as death from any cause, initiation of renal replacement therapy, or a 50% decline in eGFR. This study evaluated the discrimination and model fit of three predictive models. The performance of the original and modified IIgAN-PT models was compared and evaluated through reclassification, survival analysis, calibration, decision curve analyses and subgroup analyses. Results: In the study cohort, the median follow-up duration was 4.2 years, during which 77 patients experienced MAKEs. The discriminative ability of the three original models was relatively limited. In contrast, the modified IIgAN-PT incorporating the NOS⁺Adh⁺ subtype of S subclassification demonstrated improved global performance for predicting 5-year risk, achieving a C-index of 0.808 (95% CI, 0.756-0.861). Kaplan-Meier survival curves showed clear risk stratification, particularly between low- and intermediate-risk categories. Reclassification analyses (continuous NRI and IDI) and decision curve analysis further supported enhanced predictive performance, while calibration curves corrected the original model's risk overestimation. The modified model maintained stable performance across clinically relevant subgroups, including patients with hypertension, proteinuria, or receiving immunosuppression. Conclusions: This study further confirms the independent and clinically relevant prognostic value of the S pathological subclassification. The modified IIgAN-PT model, incorporating the NOS⁺Adh⁺ subtype of S subclassification, demonstrated consistent performance in individualized risk assessment for patients with IgA nephropathy.