A preliminary nomogram model for predicting relapse of patients with primary membranous nephropathy

AbstractObjective To explore the predictive factors and establish a nomogram model for predicting relapse risk in primary membranous nephropathy (PMN).Methods The clinical, laboratory, pathological and follow-up data of patients with biopsy-proven membranous nephropathy were collected in the Affiliated Hospital of Qingdao University. A total of 400 PMN patients who achieved remission were assigned to the development group (n = 280) and validation group (n = 120) randomly. Cox regression analysis was performed in the development cohort to determine the predictive factors of relapse in PMN patients, a nomogram model was established based on the multivariate Cox regression analysis and validated in the validation group. C-index and calibration plots were used to evaluate the discrimination and calibration performance of the model respectively.Result Hyperuricemia (HR = 2.938, 95% CI 1.875–4.605, p