Development and validation of a clinical and laboratory-based nomogram to predict nonalcoholic fatty liver disease


Background and aim

Nonalcoholic fatty liver disease (NAFLD) is becoming the leading cause of chronic liver disease in China. The early identification and management of patients at risk are essential. We aimed to develop a novel clinical and laboratory-based nomogram (CLN) model to predict NAFLD with high accuracy.


We designed a retrospective cross-sectional study and enrolled 21,468 participants (16,468 testing and 5000 validation). Clinical information and laboratory/imaging results were retrieved. Significant variables independently associated with NAFLD were identified by a logistic regression model, and a NAFLD prediction CLN was constructed. The CLN was then compared with four existing NAFLD-related prediction models: the fatty liver index (FLI), the hepatic steatosis index (HSI), the visceral adiposity index (VAI) and the triglycerides and glucose (TyG) index. Area under the receiver operator characteristic curve (AUROC) and decision curve analysis (DCA) were performed.


A total of 6261/16,468 (38.02%) and 1759/5000 (35.18%) participants in the testing and validation datasets, respectively, had ultrasound-proven NAFLD. Six variables were selected to build the CLN: body mass index (BMI), diastolic blood pressure (DBP), uric acid (UA), fasting blood glucose (FBG), triglyceride (TG), and alanine aminotransferase (ALT). The diagnostic accuracy of the CLN for NAFLD (AUROC 0.857, 95% CI 0.852–0.863) was significantly superior to that of the FLI (AUROC 0.849, 95% CI 0.843–0.855), the VAI (AUROC 0.752, 95% CI 0.745–0.760), the HSI (AUROC 0.828, 95% CI 0.822–0.834), and the TyG index (AUROC 0.774, 95% CI 0.767–0.781) (all p < 0.001). DCA confirmed the clinical utility of the CLN.


This physical examination and laboratory test-based, nonimage-assisted novel nomogram has better performance in predicting NAFLD than the FLI, the VAI, the HSI and the TyG index alone. This model can be used as a quick screening tool to assess NAFLD in the general population.

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Fig. 1
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Fig. 3



Clinical and laboratory-based nomogram


Body mass index


Waist circumference


Systolic blood pressure


Diastolic blood pressure


Heart rate




Platelet count


White blood cell count


Neutrophil count


Lymphocyte count


Monocyte count






Uric acid


Fasting blood glucose




Total cholesterol


Low-density lipoprotein cholesterol


High-density lipoprotein cholesterol


Alpha fucosidase


Alanine aminotransferase


Aspartate aminotransferase


Gamma-glutamyl transpeptidase




Alkaline phosphatase


Carcinoembryonic antigen


Alpha fetoprotein


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This work was supported by research grants from Zhejiang Provincial Medical & Hygienic Science and Technology Project of China (2018KY385). Zhejiang Provincial Natural Science Foundation of China (LY20H160023). The supporting institutions had no involvement in the study design; the collection, analysis and interpretation of the data; the writing of the manuscript; or the decision to submit the manuscript for publication.

Author information




CC and ZSS conceived and designed the research. YSF, TXF and LYX collected samples. ZL and YJ conducted the experiments. WWP and LJM analyzed the data. CC and LJM wrote the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Shusen Zheng.

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The study protocol was approved by the Ethics Committee of the First Affiliated Hospital of Zhejiang University School of Medicine.

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Cen, C., Wang, W., Yu, S. et al. Development and validation of a clinical and laboratory-based nomogram to predict nonalcoholic fatty liver disease. Hepatol Int (2020).

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  • Nonimage assisted
  • Prediction model
  • Healthy population
  • Metabolic syndrome
  • Liver biopsy
  • Early diagnosis and prevention
  • Fatty liver index
  • Hepatic steatosis index
  • Triglycerides and glucose index
  • Visceral adiposity index