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Nomogram for thromboembolic events in primary membranous nephropathy associated with PLA2R antibody
Zihan Zhai1, Yanhong Guo1, Lu Yu1
1Department of Nephropathy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, People's Republic of China.
Abstract:
Patients with nephrotic syndrome, particularly those with primary membranous nephropathy (pMN), are at a heightened risk of thromboembolic events. The presence of phospholipase A2 receptor (PLA2R) antibody serves as an indicator of active primary membranous nephropathy. Identifying high-risk patients for thromboembolic events is crucial for facilitating effective communication between healthcare providers and patients, evaluating treatment outcomes, and assessing medical costs. This study aimed to develop a practical model for predicting the probability of thromboembolic events in patients with PLA2R-related primary membranous nephropathy. A total of 1384 patients diagnosed with PLA2R antibody-related primary membranous nephropathy were included in this study. The model group included 969 patients enrolled before August 2020, while the external validation group consisted of 415 patients enrolled later. Patients in the modeling group were divided into the thromboembolic and non-thromboembolic subgroups. Logistic regression analysis was performed, and a nomogram was established based on the results. The predictive performance of the nomogram was evaluated by the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCAs). The modeling group comprised 126 (13.0%) patients with thromboembolism, and significant differences were observed between the thromboembolism and non-thromboembolism subgroups. The risk factors included in the nomogram included age, Anti-PLA2R antibody, and 24-hour urine protein quantification. The AUC value of the nomogram was 0.741 (95% CI 0.695-0.788, P < 0.001). In addition, the calibration curves demonstrated acceptable agreement between the predicted outcomes by the nomogram and the actual values. DCA curves showed good positive net benefits in the predictive model. The external validation also confirmed the reliability of the prediction nomogram. This predictive nomogram including Anti-PLA2R antibody, age, and 24-hour urine protein quantification may facilitate the prediction of the thromboembolic risk in patients with PLA2R-related pMN.
Insights
Patients with phospholipase A2 receptor (PLA2R) antibody-related primary membranous nephropathy face high thromboembolic risk. A new nomogram using age, PLA2R antibody levels, and urine protein accurately predicts this risk.
Area of Science:
- Nephrology
- Thrombosis
- Predictive Modeling
Background:
- Patients with nephrotic syndrome, especially primary membranous nephropathy (pMN), have an increased risk of thromboembolic events.
- PhospholipasA2 receptor (PLA2R) antibody presence indicates active pMN and is crucial for risk stratification.
- Accurate identification of high-risk patients is essential for clinical management, patient communication, and resource allocation.
Purpose of the Study:
- To develop and validate a practical predictive model for thromboembolic events in patients with PLA2R antibody-related pMN.
- To identify key clinical factors contributing to thromboembolic risk in this patient population.
Main Methods:
- A cohort of 1384 patients with PLA2R antibody-related pMN was analyzed.
- A predictive model (nomogram) was developed using logistic regression on a modeling group (969 patients) and validated externally on 415 patients.
- Model performance was assessed using AUC, calibration curves, and decision curve analysis (DCAs).
Main Results:
- The nomogram incorporated age, Anti-PLA2R antibody levels, and 24-hour urine protein quantification.
- The model demonstrated good predictive performance with an AUC of 0.741.
- Calibration curves and DCAs confirmed the nomogram's reliability and clinical utility in predicting thromboembolic events.
Conclusions:
- A validated nomogram incorporating age, Anti-PLA2R antibody, and 24-hour urine protein can effectively predict thromboembolic risk in patients with PLA2R-related pMN.
- This tool can aid clinicians in identifying at-risk individuals, guiding treatment decisions, and improving patient outcomes.
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