Establishing of a risk prediction model for metabolic dysfunction-associated steatotic liver disease: a retrospective cohort study
Abstract Objectives Over 30% of people worldwide suffer from metabolic dysfunction-associated steatotic liver disease (MASLD), a significant global health issue. Identifying and preventing high-risk individuals for MASLD early is crucial. The purpose of our study is to investigate the factors relate...
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2025-01-01
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| Online Access: | https://doi.org/10.1186/s12876-025-03598-4 |
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| author | Nan Li Chenbing Liu Zhangfan Lu Wenjian Wu Feng Zhang Lihong Qiu Chao Shen Di Sheng Zhong Liu |
| author_facet | Nan Li Chenbing Liu Zhangfan Lu Wenjian Wu Feng Zhang Lihong Qiu Chao Shen Di Sheng Zhong Liu |
| author_sort | Nan Li |
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| description | Abstract Objectives Over 30% of people worldwide suffer from metabolic dysfunction-associated steatotic liver disease (MASLD), a significant global health issue. Identifying and preventing high-risk individuals for MASLD early is crucial. The purpose of our study is to investigate the factors related to the development of MASLD and develop a risk prediction model for its occurrence. Methods The study included 5107 subjects, divided into training and validation groups in a 7:3 ratio using a random number table method. Collinearity diagnosis and Cox regression were used to identify factors associated with MASLD incidence, and a risk prediction model was created. The model’s accuracy, reliability, and clinical applicability were assessed. Results Our study indicated that male, body mass index (BMI), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), fasting plasma glucose (FPG), serum uric acid to creatinine ratio (SUA/Cr) and white blood cell (WBC) were associated with MASLD incidence. The elements were determined to be crucial for creating a risk prediction model. The model showed strong discriminative potential with a C-index of 0.783 and the time-dependent AUCs of 0.781, 0.789, 0.814 and 0.796 for 1–4 years in the training group, and a C-index of 0.788 and the time-dependent AUCs of 0.798, 0.782, 0.787 and 0.825 for 1–4 years in validation. Calibration curves confirmed the model’s accuracy, and decision curve analysis (DCA) validated its clinical utility. Conclusions The model may provide clinical physicians with a reliable method for identifying high-risk populations for MASLD and serve as a guide for developing prediction models for other diseases. |
| format | Article |
| id | doaj-art-2a49ada8ed814dfeb66bd055c1d3cd17 |
| institution | Kabale University |
| issn | 1471-230X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Gastroenterology |
| spelling | doaj-art-2a49ada8ed814dfeb66bd055c1d3cd172025-02-02T12:27:17ZengBMCBMC Gastroenterology1471-230X2025-01-0125111110.1186/s12876-025-03598-4Establishing of a risk prediction model for metabolic dysfunction-associated steatotic liver disease: a retrospective cohort studyNan Li0Chenbing Liu1Zhangfan Lu2Wenjian Wu3Feng Zhang4Lihong Qiu5Chao Shen6Di Sheng7Zhong Liu8Health Management Center, the First Affiliated Hospital of Zhejiang University School of MedicineHealth Management Center, the First Affiliated Hospital of Zhejiang University School of MedicineHealth Management Center, the First Affiliated Hospital of Zhejiang University School of MedicineHealth Management Center, the First Affiliated Hospital of Zhejiang University School of MedicineHealth Management Center, the First Affiliated Hospital of Zhejiang University School of MedicineHealth Management Center, the First Affiliated Hospital of Zhejiang University School of MedicineHealth Management Center, the First Affiliated Hospital of Zhejiang University School of MedicineHealth Management Center, the First Affiliated Hospital of Zhejiang University School of MedicineHealth Management Center, the First Affiliated Hospital of Zhejiang University School of MedicineAbstract Objectives Over 30% of people worldwide suffer from metabolic dysfunction-associated steatotic liver disease (MASLD), a significant global health issue. Identifying and preventing high-risk individuals for MASLD early is crucial. The purpose of our study is to investigate the factors related to the development of MASLD and develop a risk prediction model for its occurrence. Methods The study included 5107 subjects, divided into training and validation groups in a 7:3 ratio using a random number table method. Collinearity diagnosis and Cox regression were used to identify factors associated with MASLD incidence, and a risk prediction model was created. The model’s accuracy, reliability, and clinical applicability were assessed. Results Our study indicated that male, body mass index (BMI), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), fasting plasma glucose (FPG), serum uric acid to creatinine ratio (SUA/Cr) and white blood cell (WBC) were associated with MASLD incidence. The elements were determined to be crucial for creating a risk prediction model. The model showed strong discriminative potential with a C-index of 0.783 and the time-dependent AUCs of 0.781, 0.789, 0.814 and 0.796 for 1–4 years in the training group, and a C-index of 0.788 and the time-dependent AUCs of 0.798, 0.782, 0.787 and 0.825 for 1–4 years in validation. Calibration curves confirmed the model’s accuracy, and decision curve analysis (DCA) validated its clinical utility. Conclusions The model may provide clinical physicians with a reliable method for identifying high-risk populations for MASLD and serve as a guide for developing prediction models for other diseases.https://doi.org/10.1186/s12876-025-03598-4Metabolic dysfunction-associated steatotic liver diseaseRetrospective cohort studyCox regressionIncidence riskNomogram |
| spellingShingle | Nan Li Chenbing Liu Zhangfan Lu Wenjian Wu Feng Zhang Lihong Qiu Chao Shen Di Sheng Zhong Liu Establishing of a risk prediction model for metabolic dysfunction-associated steatotic liver disease: a retrospective cohort study BMC Gastroenterology Metabolic dysfunction-associated steatotic liver disease Retrospective cohort study Cox regression Incidence risk Nomogram |
| title | Establishing of a risk prediction model for metabolic dysfunction-associated steatotic liver disease: a retrospective cohort study |
| title_full | Establishing of a risk prediction model for metabolic dysfunction-associated steatotic liver disease: a retrospective cohort study |
| title_fullStr | Establishing of a risk prediction model for metabolic dysfunction-associated steatotic liver disease: a retrospective cohort study |
| title_full_unstemmed | Establishing of a risk prediction model for metabolic dysfunction-associated steatotic liver disease: a retrospective cohort study |
| title_short | Establishing of a risk prediction model for metabolic dysfunction-associated steatotic liver disease: a retrospective cohort study |
| title_sort | establishing of a risk prediction model for metabolic dysfunction associated steatotic liver disease a retrospective cohort study |
| topic | Metabolic dysfunction-associated steatotic liver disease Retrospective cohort study Cox regression Incidence risk Nomogram |
| url | https://doi.org/10.1186/s12876-025-03598-4 |
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