ArticleInternational urology and nephrology2022
Nomogram to predict the progression of patients with primary membranous nephropathy and nephrotic syndrome.
Article in International urology and nephrology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed, 15 citations in OpenAlex.
- Prognostic Stratification in Primary Glomerulonephritis: Integrating Histology, Biomarkers, and Risk Prediction Models.Life (Basel, Switzerland) · 2026Review
- Identification and validation of feature genes using a ferroptosis-informed analytical framework in medulloblastoma.Frontiers in pediatrics · 2026Article
- A Novel Model for Predicting Post-Craniotomy Meningitis Using Early Postoperative Risk Stratification: A Multi-Center Retrospective Study.Infection and drug resistance · 2026Article
- Impact of Time-To-Treatment on Outcomes in Autoimmune Membranous Nephropathy.Kidney international reports · 2025Article
- Prognostic Factors of Proteinuria Remission in Primary Membranous Nephropathy.Journal of clinical medicine · 2025Review
- Prognostic value of serum complement cleavage factor Bb in idiopathic membranous nephropathy and establishment of nomogram model.Scientific reports · 2024Article
- Article
- A dynamic online nomogram for predicting renal outcomes of idiopathic membranous nephropathy.BMC medical informatics and decision making · 2024Article
- Fractional excretion of total protein predicts renal prognosis in Japanese patients with primary membranous nephropathy.Clinical kidney journal · 2024Article
- Risk factors and nomogram to predict skip metastasis in papillary thyroid carcinoma.Gland surgery · 2024Article
- Development of a nomogram for membranous nephropathy prediction in patients with primary Sjögren's syndrome: a 6-year retrospective study.Frontiers in immunology · 2024Article
- A prediction model for prognosis of nephrotic syndrome with tuberculosis in intensive care unit patients: a nomogram based on the MIMIC-IV v2.2 database.Frontiers in medicine · 2024Article
- A Dynamic Prediction Model for Renal Progression in Primary Membranous Nephropathy.International journal of medical sciences · 2024Article
- Development and validation of a simple-to-use nomogram for predicting minimal change disease based on quantification of color Doppler sonography data from a region of interest.Abdominal radiology (New York) · 2023Article
- Prediction Models of Primary Membranous Nephropathy: A Systematic Review and Meta-Analysis.Journal of clinical medicine · 2023Review
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6 authors at 1 institution in 1 country.
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Abstract
backgroundThe outcome of patients with primary membranous nephropathy (pMN) who present with nephrotic syndrome (NS) is variable and difficult to predict. The goal of this study was to develop a nomogram to predict the risk of progression for specific individuals.
methodsThis retrospective study involved biopsy-proven patients with pMN and NS treated between January 2012 and June 2018. The primary outcome of our investigation was progression, defined as a reduction of estimated glomerular filtration rate (eGFR) that was equal to or over 20% compared with baseline at the end of follow-up or the onset of end-stage renal disease (ESRD). We used backwards stepwise logistic regression analysis to create a nomogram to predict prognosis. The model was validated internally using bootstrap resampling.
resultsA total of 111 patients were enrolled. After a median follow-up of 40.0 months (range 12-92 months), 18.9% (21/111) patients showed progression. Backwards stepwise selection using the Akaike information criterion (AIC) identified the following four variables as independent risk factors for progression, which were all used in the nomogram: age ≥ 65 years [odds ratio (OR) 7.004; 95% confidence interval (CI) 1.783-27.505; p = 0.005], Ln (sPLA2R-Ab) (OR 2.150; 95% CI 1.293-3.577; p = 0.003), Ln (proteinuria) (OR 5.939; 95% CI 1.055-33.436; p = 0.043) and Ln (Uα1m/Cr) (OR 2.808; 95% CI 1.035-7.619; p = 0.043). The discriminative ability and calibration of the nomogram revealed good predictive ability, as indicated by a C-index of 0.888 (95% CI 0.814-0.940) and a bootstrap-corrected C-index of 0.869; calibration curves were also well fitted. A receiver operating characteristic (ROC) curve for the nomogram score revealed significantly better discrimination than each of the three risk factors alone, including Ln (sPLA2R-Ab) [area under the curve (AUC) 0.769], Ln (proteinuria) (AUC 0.653) and Ln (Uα1m) (AUC 0.781) in the prediction of progression (p < 0.05). The optimal cutoff value of the nomogram score was 117.8 with a positive predictive value of 44.4% and a negative predictive value of 98.5%.
conclusionThe nomogram successfully achieved good predictive ability of progression for patients with pMN who present with NS. It can therefore help clinicians to individualize treatment plans and improve the outcome of pMN.
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