ArticleJournal of clinical and translational hepatology2022
Development and Validation of a Nomogram for Prediction of the Risk of MAFLD in an Overweight and Obese Population.
Article in Journal of clinical and translational hepatology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 10 citations in OpenAlex.
- Association between TyG-related parameters and NAFLD risk in Japanese non-obese population.Scientific reports · 2025Article
- Value of a multi-indicator model combining Elast PQ technology, blood lipids, liver function, and uric acid for early diagnosis of alcoholic fatty liver disease.American journal of translational research · 2025Article
- Psoas Muscle Index, Systemic Inflammation, and Liver Fibrosis in MAFLD: A Case-Control Study.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025Article
- A nomogram for predicting metabolic-associated fatty liver disease in non-obese newly diagnosed type 2 diabetes patients.Frontiers in endocrinology · 2025Article
- Development and validation of a nomogram model for predicting the risk of MAFLD in the young population.Scientific reports · 2024Article
- Institutional Nomogram for Estimating Risk of Metabolic Associated Fatty Liver Disease (MAFLD).Diabetes, metabolic syndrome and obesity : targets and therapy · 2024Article
- Development and validation of a nomogram for predicting metabolic-associated fatty liver disease in the Chinese physical examination population.Lipids in health and disease · 2023Article
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and Aims: Metabolic associated fatty liver disease (MAFLD) is a serious condition, and a simple method is needed for practitioners to identify patients with the disease and have a high risk of disease progression. Methods: We developed and validated a nomogram for fatty liver disease and reclassified the risk factors for MAFLD. The development cohort had 335 patients who received bioelectrical impedance analysis and liver ultrasound attenuation measurements at Shenzhen People's Hospital between September 2020 and June 2021. The validation cohort had 200 patients from other hospitals who received the same evaluation. A random forest procedure and binary logistic analysis were used to screen for risk factors, establish a fatty liver disease predictive model, and forecast the risk of MAFLD. The performance of the nomogram was evaluated by measurement of discrimination, calibration, and clinical usefulness. Results: The nomogram provided good predictions in a model that included body mass index (BMI) and waist circumference. The areas under the curve of the nomogram were 0.793 in the development cohort and 0.774 in the validation cohort. The nomogram performed well for calibration, category-free net reclassification improvement, and integrated discrimination improvement. Decision curve analysis indicated the nomogram performed better than BMI for predicting net outcome. Conclusions: The nomogram was an effective screening tool for fatty liver disease, and for those overweight individuals, may help physicians make appropriate decisions regarding treatment of MAFLD.
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