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. 2022 Aug 31:13:986841.
doi: 10.3389/fendo.2022.986841. eCollection 2022.

Clinical spectrum transition and prediction model of nonalcoholic fatty liver disease in children with obesity

Xuelian Zhou  1 , Xiufu Lin  1 , Jingnan Chen  1 , Jiaqi Pu  1 , Wei Wu  1 , Zhaoyuan Wu  1 , Hu Lin  1 , Ke Huang  1 , Li Zhang  1 , Yangli Dai  1 , Yan Ni  1 , Guanping Dong  1 , Junfen Fu  1
Affiliations

Clinical spectrum transition and prediction model of nonalcoholic fatty liver disease in children with obesity

Xuelian Zhou et al. Front Endocrinol (Lausanne). .

Abstract

Objective: This study aims to outline the clinical characteristics of pediatric NAFLD, as well as establish and validate a prediction model for the disease.

Materials and methods: The retrospective study enrolled 3216 children with obesity from January 2003 to May 2021. They were divided into obese without NAFLD, nonalcoholic fatty liver (NAFL), and nonalcoholic steatohepatitis (NASH) groups. Clinical data were retrieved, and gender and chronologic characteristics were compared between groups. Data from the training set (3036) were assessed using univariate analyses and stepwise multivariate logistic regression, by which a nomogram was developed to estimate the probability of NAFLD. Another 180 cases received additional liver hydrogen proton magnetic resonance spectroscopy (1H-MRS) as a validation set.

Results: The prevalence of NAFLD was higher in males than in females and has increased over the last 19 years. In total, 1915 cases were NAFLD, and the peak onset age was 10-12 years old. Hyperuricemia ranked first in childhood NAFLD comorbidities, followed by dyslipidemia, hypertension, metabolic syndrome (MetS), and dysglycemia. The AUROC of the eight-parameter nomogram, including waist-to-height ratio (WHtR), hip circumference (HC), triglyceride glucose-waist circumference (TyG-WC), alanine aminotransferase (ALT), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A1(ApoA1), insulin sensitivity index [ISI (composite)], and gender, for predicting NAFLD was 0.913 (sensitivity 80.70%, specificity 90.10%). Calibration curves demonstrated a great calibration ability of the model.

Conclusion and relevance: NAFLD is the most common complication in children with obesity. The nomogram based on anthropometric and laboratory indicators performed well in predicting NAFLD. This can be used as a quick screening tool to assess pediatric NAFLD in children with obesity.

Keywords: children; clinical spectrum; nonalcoholic fatty liver disease; obesity; prediction model.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flow chart. We identified a total of 4276 children with obesity from Jan 2003 to May 2021 who came to our hospital for metabolic assessment. 3216 children were enrolled in this study according to the above exclusion criteria. They were divided into three groups according to liver ultrasound and serum ALT concentration, and their clinical characteristics were detailed and analyzed. We established and validated a nomogram model for predicting childhood NAFLD. Among which, 3036 cases were used as the training set and 180 cases were used as the validation set.
Figure 2
Figure 2
Metabolic spectrum of childhood obesity and comorbidities of pediatric NAFLD. (A) Gender composition of metabolic disorders in children with obesity: NAFLD is the most common complication of childhood obesity, more males suffered from obesity and metabolic disorder than females. (B) Chronologic composition of metabolic disorders in children with obesity: The prevalence of obesity and metabolic disorders in children has been increasing in recent 19 years. (C) Prevalence of metabolic disorders in children with obesity adjusted by gender: the prevalence of NAFLD and hypertension was much higher in males than females, while hyperuricemia was much more prevalent in females than males. (D) Gender composition of comorbidities in pediatric NAFLD: hyperuricemia ranked top one comorbidities of childhood NAFLD. (E) Chronologic composition of comorbidities in pediatric NAFLD: The prevalence of comorbidities of pediatric NAFLD has been increasing in the last 19 years. (F) Age distribution of children with NAFLD: the peak onset age of childhood NAFLD is 10-12 years old. Note: the number on the top of the figure indicates the count of patients, red represents females, and blue represents males.
Figure 3
Figure 3
The establishment and validation of a clinical predicting model for childhood NAFLD. (A) Nomogram model for predicting childhood NAFLD. (B) Receiver operating characteristics (ROC) curves for predicting NAFLD in the training set, the AUROC of the model is 0.821 (95% CI 0.806–0.835, p < 0.001) with the sensitivity and specificity of 70.70% and 79.10%, respectively. (C) ROC curves for predicting NAFLD in the validation set, the AUROC of the model is 0.913 (95% CI 0.879–0.960, p < 0.001) with the sensitivity and specificity of 80.70% and 90.10%, respectively. (D, E): calibration curves for assessment of the performance of the nomogram in the training set (D) and the validation set (E). (1000 bootstrap resamples). Nomogram predicted probability of NAFLD is plotted on the x-axis; actual probability is plotted on the y-axis.
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