ArticleJournal of healthcare engineering2021
A PLA2R-IgG4 Antibody-Based Predictive Model for Assessing Risk Stratification of Idiopathic Membranous Nephropathy.
Article in Journal of healthcare engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 16 citations in OpenAlex.
- Early kinetics of anti-PLA2R-IgG4 predicts rituximab response in membranous nephropathy: a prospective biomarker study.Scientific reports · 2026Article
- Time-resolved fluoroimmunoassay improves sensitivity in the diagnosis of primary membranous nephropathy with low phospholipase A2 receptor antibody titer.Scientific reports · 2025Article
- Identification of early predictors of clinical remission in primary membranous nephropathy: aClinical kidney journal · 2025Article
- Telitacicept and Tacrolimus Synergy in Managing Refractory Primary Membranous Nephropathy: Case Insights.The American journal of case reports · 2025Article
- Role of PLA2R domain antibodies and epitope spreading in risk stratification and prediction of proteinuria remission in primary membranous nephropathy.Scientific reports · 2025Article
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- A dynamic online nomogram for predicting renal outcomes of idiopathic membranous nephropathy.BMC medical informatics and decision making · 2024Article
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- Prognostic prediction of idiopathic membranous nephropathy using interpretable machine learning.Renal failure · 2023Article
- Clinical Evaluation of Antiphospholipase A2 Receptor IgG4 level and Its IgG4-to-IgG Ratio Based on Quantitative Immunoassays in Idiopathic Membranous Nephropathy.BioMed research international · 2022Article
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Authors and funding
11 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Known as an autoimmune glomerular disease, idiopathic membranous nephropathy (IMN) is considered to be associated with phospholipase A2 receptor (PLA2R) in terms of the main pathogenesis. The quantitative detection of serum PLA2R-IgG and PLA2R-IgG4 antibodies by time-resolved fluoroimmunoassay (TRFIA) was determined, and the value of them, both in the clinical prediction of risk stratification in IMN, was observed in this study. Methods: 95 patients with IMN proved by renal biopsy were enrolled, who had tested positive for serum PLA2R antibodies by ELISA, and the quantitative detection of serum PLA2R-IgG and PLA2R-IgG4 antibodies was achieved by TRFIA. All the patients were divided into low-, medium-, and high-risk groups, respectively, which were set as dependent variables, according to proteinuria and renal function. Random forest (RF) was used to estimate the value of serum PLA2R-IgG and PLA2R-IgG4 in predicting the risk stratification of progression in IMN. Results: Out-of-bag estimates of variable importance in RF were employed to evaluate the impact of each input variable on the final classification accuracy. The variable of albumin, PLA2R-IgG, and PLA2R-IgG4 had high values (>0.3) of 0.3156, 0.3981, and 0.7682, respectively, which meant that these three were more important for the risk stratification of progression in IMN. In order to further assess the contribution of PLA2R-IgG and PLA2R-IgG4 to the model, we built four different models and found that PLA2R-IgG4 played an important role in improving the predictive ability of the model. Conclusions: In this study, we established a random forest model to evaluate the value of serum PLA2R-IgG4 antibodies in predicting risk stratification of IMN. Compared with PLA2R-IgG, PLA2R-IgG4 is a more efficient biomarker in predicting the risk of progression in IMN.
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