Nomogram for thromboembolic events in primary membranous nephropathy associated with PLA2R antibody

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.

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Journal
Scientific Reports
Published
2025-04-15
DOI
https://doi.org/10.1038/s41598-025-97203-z
Primary Topic
Renal Diseases and Glomerulopathies
Type
article
Field-Weighted Citation Impact
0.00

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article

Nomogram for thromboembolic events in primary membranous nephropathy associated with PLA2R antibody

Zihan Zhai, Liuwei Wang, Lin Tang, Lu Yu et al.
Scientific Reports
Renal Diseases and Glomerulopathies
article

Nomogram for thromboembolic events in primary membranous nephropathy associated with PLA2R antibody

Zihan Zhai, Liuwei Wang, Lin Tang, Lu Yu, Yanhong Guo, Yulin Wang, Yuhua Yuan, Qiuhong Li
article en

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.

Scientific ReportsVol. 15(1)
First Affiliated Hospital of Zhengzhou University (CN)
National Natural Science Foundation of China, Zhengzhou University
Zero hunger
Openalex Percentile: Top 91%
Renal Diseases and Glomerulopathies
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