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Construction of a Nomogram Discriminating Malignancy-Associated Membranous Nephropathy From Idiopathic Membranous
1Department of Nephrology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Background:
Based on the etiology, membranous nephropathy (MN) can be categorized into idiopathic membranous nephropathy (IMN) and secondary membranous nephropathy. Malignancy-associated membranous nephropathy (MMN) is a common type of secondary MN. Its incidence is only second to that of lupus nephritis. As the treatment and prognosis of MMN differ significantly from those of other MNs, the identification of MMN is crucial for clinical practice. The purpose of this study was to develop a model that could efficiently discriminate MMN, to guide more precise selection of therapeutic strategies.
Methods:
A total of 385 with IMN and 62 patients with MMN, who were hospitalized at the First Affiliated Hospital of Zhengzhou University between January 2017 and December 2020 were included in this study. We constructed a discriminant model based on demographic information and laboratory parameters for distinguishing MMN and IMN. To avoid an increased false positivity rate resulting from the large difference in sample numbers between the two groups, we matched MMN and IMN in a 1:3 ratio according to gender. Regression analysis was subsequently performed and a discriminant model was constructed. The calibration ability and clinical utility of the model were assessed via calibration curve and decision curve analysis.
Results:
We constructed a discriminant model based on age, CD4+ T cell counts, levels of cystatin C, albumin, free triiodothyronine and body mass index, with a diagnostic power of 0.860 and 0.870 in the training and test groups, respectively. The model was validated to demonstrate good calibration capability and clinical utility.
Conclusion:
In clinical practice, patients demonstrating higher scores after screening with this model should be carefully monitored for the presence of tumors in order to improve their outcome.
Insights
This study developed a model to distinguish malignancy-associated membranous nephropathy (MMN) from idiopathic membranous nephropathy (IMN). The model aids in early tumor detection for improved patient outcomes in MMN cases.
Area of Science:
- Nephrology
- Oncology
- Diagnostic Medicine
Background:
- Membranous nephropathy (MN) is classified as idiopathic (IMN) or secondary.
- Malignancy-associated membranous nephropathy (MMN) is a prevalent secondary form requiring distinct management.
- Accurate differentiation of MMN is critical for appropriate treatment and prognosis.
Purpose of the Study:
- To develop a predictive model for discriminating MMN from IMN.
- To guide precise therapeutic strategies by identifying MMN early.
- To enhance clinical practice through improved diagnostic accuracy.
Main Methods:
- A discriminant model was constructed using demographic and laboratory data from 385 IMN and 62 MMN patients.
- Patient data were collected between January 2017 and December 2020.
- A 1:3 gender-matched ratio was used to balance sample sizes, followed by regression analysis and validation via calibration curves and decision analysis.
Main Results:
- A discriminant model incorporating age, CD4+ T cell counts, cystatin C, albumin, free triiodothyronine, and BMI was developed.
- The model achieved diagnostic powers of 0.860 in the training set and 0.870 in the test set.
- The model demonstrated good calibration and clinical utility.
Conclusions:
- The developed model effectively discriminates MMN from IMN.
- Higher scores from this model warrant vigilant tumor screening in patients.
- Early identification and monitoring of MMN can significantly improve patient outcomes.
