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Published on: December 9, 2015
A preliminary nomogram model for predicting relapse of patients with primary membranous nephropathy
Min Li1, Huifang Wang1, Xiaoying Lai1
1Department of Nephrology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, P. R. China.
Objective:
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 < 0.001), high C-reactive protein (CRP) (HR = 1.147, 95% CI 1.086-1.211, p < 0.001), and treatment with calcineurin inhibitors with or without glucocorticoids (HR = 2.845, 95%CI 1.361-5.946, p = 0.005) were independent risk factors, while complete remission (HR = 0.420, 95%CI 0.270-0.655, p < 0.001) was a protective factor for relapse of PMN according to multivariate Cox regression analysis, then a nomogram model for predicting relapse of PMN was established combining the above indicators. The C-indices of this model were 0.777 (95%CI 0.729-0.825) and 0.778 (95%CI 0.704-0.853) in the development group and validation group respectively. The calibration plots showed that the predicted relapse probabilities of the model were consistent with the actual probabilities at 1, 2 and 3 years, which indicated favorable performance of this model in predicting the relapse probability of PMN.
Conclusions:
Hyperuricemia, remission status, CRP and therapeutic regimen were predictive factors for relapse of PMN. A novel nomogram model with good discrimination and calibration was constructed to predict relapse risk in patients with PMN early.
Insights
This study identified hyperuricemia, high C-reactive protein (CRP), and specific treatments as key predictors of relapse in primary membranous nephropathy (PMN). A new nomogram model accurately predicts PMN relapse risk, aiding early intervention.
Area of Science:
- Nephrology
- Internal Medicine
- Clinical Epidemiology
Background:
- Primary membranous nephropathy (PMN) is a leading cause of nephrotic syndrome in adults.
- Predicting relapse risk in PMN is crucial for optimizing treatment strategies and patient outcomes.
- Existing models may not fully capture the complex factors influencing PMN relapse.
Purpose of the Study:
- To identify independent predictive factors for relapse in patients with primary membranous nephropathy (PMN).
- To develop and validate a nomogram model for predicting the risk of PMN relapse.
- To enhance early risk stratification and management of PMN patients.
Main Methods:
- Retrospective analysis of 400 biopsy-proven PMN patients who achieved remission.
- Development and validation cohorts were used for model construction and evaluation.
- Multivariate Cox regression analysis identified predictive factors; a nomogram was built and assessed using C-index and calibration plots.
Main Results:
- Hyperuricemia, elevated C-reactive protein (CRP), and treatment with calcineurin inhibitors (with or without glucocorticoids) were significant independent risk factors for PMN relapse.
- Complete remission was identified as a protective factor against relapse.
- The developed nomogram demonstrated good discrimination (C-indices of 0.777 and 0.778) and calibration in both development and validation cohorts.
Conclusions:
- Hyperuricemia, remission status, CRP levels, and therapeutic regimens are significant predictors of PMN relapse.
- A novel nomogram model offers reliable prediction of relapse risk in PMN patients.
- This tool can aid clinicians in early identification and management of high-risk individuals.
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