A dynamic online nomogram for predicting renal outcomes of idiopathic membranous nephropathy

Abstract

Abstract Background Idiopathic membranous nephropathy (IMN) is the most common cause of nephrotic syndrome in nondiabetic adults. The natural course of IMN is variable, 30% of patients may progress to end-stage renal disease in 10 years. Hence there is an increasing need to develop a dynamic online nomogram for predicting the prognosis of IMN. Methods All the data were obtained from the newly diagnosed IMN patients enrolled in 3 hospitals in Liaoning Province. The nomogram prognostic model was developed by independent risk factors of multivariate logistic regression. The prognostic performance was evaluated using the ROC, calibration and decision curves. Results A total of 130 patients were in the training cohort and 102 patients in the validation cohort. Course ≥ 6 months (OR, 0.225; 95% confidence interval (CI) 0.081, 0.628; P = .004), UTP (OR, 1.140; 95% CI 1.029, 1.262; P = .012), D-Dimer (OR, 1.001; 95% CI 1.000, 1.002; P = .009), and sPLA2R-Ab (OR, 1.005; 95% CI 1.001, 1.008; P = .006) were independently associated with the IMN progression. The nomogram model showed good calibration with a concordance index (C-index) of 0.835 in the training cohort and 0.874 in the validation cohort, with excellent calibration ability and clinical utility. Conclusions We developed a dynamic online nomogram model that can be used to predict the risk of progression in IMN, showing good discrimination and calibration ability.