NFI, a clinical scoring tool for predicting non-alcoholic fatty liver in the Chinese population

Zhao, Ming; Hu, Yanli; Shi, Changcheng; Wang, Kan; Li, J.; Song, Jiahui; Huo, Congde; Xi, Yingfei; Bu, Shizhong; Huang, Qinghai

doi:10.1016/j.puhe.2021.10.012

Cited by 4 publications

(6 citation statements)

References 41 publications

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“…By contrast, the predictive value of UHR was still present, no matter the gender or level of liver functioning, making it a more reliable indicator for patients with different clinical profiles. Currently, liver biopsy is considered as the gold standard for assessing the severity of NAFLD steatosis, but it is not suitable for large-scale screening, due to its invasive nature, as well as the possibility of sampling errors [11]. In this study, NAFLD was diagnosed by ultrasound, though this has the limitation of being unable to determine NAFLD severity.…”

Section: Discussionmentioning

confidence: 99%

“…Recently, Zhao et al [11] performed step-to-multiple logistic regression analysis on 1000 samples and obtained the NAFLD index (NFI), which includes ALT/ AST and TG, as a clinical scoring tool for predicting NAFLD. Accordingly, we compared the predictive value of UHR for NAFLD onset in non-obese adults to other indicators recently proposed in the literature [34][35][36][37][38].…”

Section: Discussionmentioning

confidence: 99%

“…As a result, developing methods to detect NAFLD in non-obese patients has become crucial. Currently, liver biopsy is the gold standard for diagnosing NAFLD, but it is associated with significant limitations, due to the invasive nature of the operation, along with the risk of sampling errors [11]. Therefore, multiplestudies have attempted to find a simpler, less invasive detection indicatorby investigating various serum markers.…”

Section: Introductionmentioning

confidence: 99%

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Higher serum uric acid to HDL-cholesterol ratio is associated with onset of non-alcoholic fatty liver disease in a non-obese Chinese population with normal blood lipid levels

et al. 2022

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Background Recent studies have demonstrated the presence of associations between metabolic syndrome and the onset of nonalcoholic fatty liver disease (NAFLD). Metabolic syndrome, in turn, has been found to be linked to high serum uric acid to HDL-cholesterol ratios (UHR). However, the relationship between UHR values and the occurrence of NAFLD in non-obese individuals remains unknown. The present study aimed to examine the possible correlation between UHR values and NAFLD onset among a non-obese Chinese population without dyslipidemia, as well as comparing the predictive value of UHR versus other NAFLD onset predictors. Methods A total of 9837 non-obese patients, with normal blood lipid levels, were included in a 5-year retrospective cohort study, and the onset of NAFLD in these patients was diagnosed by liver ultrasound. Results Out of the 9837 patients, 855 were diagnosed with NAFLD during the 5-year follow-up period, for an overall total prevalence of 8.7% at the end of the study period. Across quintiles 1, 2, 3, 4 and 5 of UHR (respectively, ratios of ≤ 120.88, 120.89–154.01, 154.02–189.91, 189.92–240.46, and ≥ 240.47), the prevalence of NAFLD among the patients increased from 2.4%, 5%, 7.9%, 10.3%, and 17.8%, respectively. After adjustments for age, gender, liver and kidney functional markers, as well as metabolic indicators, multivariate Cox proportional hazard regression analysis demonstrated that the hazard ratio (HR) was the highest in quintile 5, at 1.76 (1.12–2.75), and the lowest in quintile 1. The area under the curve (AUC) for UHR (0.690) was higher than that for serum uric acid (UA, 0.666) and HDL-C (0.636), suggesting the predictive ability of UHR for NAFLD onset was better than either alone. This finding was further supported by the presence of an independent association between UHR and NAFLD, even within the normal range of UA and HDL-C; the HR (95% confidence interval, CI) for NAFLD was 1.002 (1.000–1.004). Compared with other significant predictors, AUC for UHR (0.67) was similar to that of low-density lipoprotein cholesterol (LDL-C)/high-density lipoprotein cholesterol (HDL-C, 0.68), non-high-density lipoprotein cholesterol (NHDL-C)/HDL-C (0.68) and alanine aminotransferase (ALT)/aspartate aminotransferase (AST) ratios (0.7), and was higher than that of LDL-C (0.63), remnant cholesterol (RC,0.59), and albumin (ALB)/alkaline phosphatase (ALP) ratio (0.61). The sensitivity of UHR (71%) was the highest among all indicators. In the subgroup with ALT < 40U/L, the AUC for UHR was 0.70, which was the highest among all predictors; among ALT > 40U/L, UHR was able to predict the occurrence of NAFLD (AUC = 0.61, p = 0.007), which was not the case for RC (P = 0.441), ALB/ALP (P = 0.419), and ALT/AST (P = 0.159). Conclusions UHR serve as an inexpensive and reliable predictor of NAFLD onset in non-obese Chinese people with normal blood lipid levels, allowing for identification of individuals at high risk for NAFLD.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Higher serum uric acid to HDL-cholesterol ratio is associated with onset of non-alcoholic fatty liver disease in a non-obese Chinese population with normal blood lipid levels

et al. 2022

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“…Yet, because of NAFLD often being associated with obesity, NAFLD in lean patients, especially pre-diabetics with normal blood lipid levels, are often overlooked until liver damage has progressed to the point of developing symptoms. Currently, liver biopsy is the gold standard for NAFLD diagnosis, but it has significant limitations due to high expenses, invasiveness, as well as risks for sampling errors and complications [ 19 ]. Therefore, a non-invasive approach for diagnosing and/or predicting NAFLD onset has been of great interest; numerous researchers have developed various predictive models, using a variety of biomarkers, such as from Zhang et al, whose model incorporated gender, age, BMI, triglycerides (TG) and other indicators to evaluate NAFLD risk in T2DM [ 20 ].…”

Section: Introductionmentioning

confidence: 99%

Development and application of a novel model to predict the risk of non-alcoholic fatty liver disease among lean pre-diabetics with normal blood lipid levels

Zhu

Shi

et al. 2022

Lipids Health Dis

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Background Non-alcoholic fatty liver disease (NAFLD) has been associated with type 2 diabetes, but its relationship with pre-diabetes is still unknown. This study aims to determine whether pre-diabetes is associated with NAFLD, followed by establishing a NAFLD predictive nomogram for lean Chinese pre-diabetics with normal blood lipids. Methods Datasets from 3 previous studies, 1 (2774 pre-diabetics with normal blood lipids for training, 925 for validation), 2 (546 for longitudinal internal validation, post-5-year follow-up), and 3 (501 from another institution for external validation), were used. Kaplan-Meier determined cumulative NAFLD hazard, and least absolute shrinkage and selection operator regression analysis uncovered its risk factors. Multivariate logistic regression analysis constructed the nomogram, followed by validation with receiver operating characteristic curve, calibration plot, and decision curve analyses. Results NAFLD incidence increased with diabetes progression, and pre-diabetics had higher cumulative risk versus non-diabetics, even for lean individuals with normal blood lipids. Six risk factors were identified: body mass index, total cholesterol, alanine aminotransferase:aspartate aminotransferase, triglyceride:high density lipoprotein cholesterol, fasting blood glucose and γ-glutamyl-transferase. The nomogram yielded areas under the curve of 0.808, 0.785, 0.796 and 0.832, for respectively, training, validation, longitudinal internal validation, and external validation, which, along with calibration curve values of p = 0.794, 0.875, 0.854 and 0.810 for those 4 datasets and decision curve analyses, validated its clinical utility. Conclusions Lean pre-diabetic Chinese with normal blood lipids have higher NAFLD risk versus non-diabetics. The nomogram is able to predict NAFLD among such individuals, with high discrimination, enabling its use for early detection and intervention.

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“…Owing to the lack of obvious symptoms at the early stages, most patients end up diagnosed with HCC after it has progressed to its advanced stages, contributing to its extremely low overall five-year survival rates of < 16% [1][2][3][4]. Currently, HCC is diagnosed based on a combination of serological, radiological, and pathological features, with liver biopsy being considered the gold standard; however, the procedure is limited by its invasiveness and risks for sampling errors [5]. As a result, alternative approaches for diagnosing HCC has been developed, such as imaging technologies, though this has its own shortcomings.…”

Section: Introductionmentioning

confidence: 99%

The combination of serum oligosaccharide chain (G-test), alpha-fetoprotein, and aspartate aminotransferase to alanine aminotransferase ratio provides the optimal diagnostic value for early detection of hepatocellular carcinoma

et al. 2022

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Background The purpose of this study was to compare the diagnostic value of serum oligosaccharide chain (G-test), alpha-fetoprotein (AFP) and aspartic aminotransferase to alanine aminotransferase ratios (AAR), both alone and in combination, for predicting hepatocellular carcinoma (HCC) onset. Methods Between Januarys 2020–2022, 152 subjects admitted to the First Affiliated Hospital of Nanchang University was enrolled in this study, of which 77 had HCC, 18 chronic hepatitis (CH), 37 liver cirrhosis (LC) and 20 were healthy. Data for patient characteristics were collected, and differences between groups were analyzed by either Mann-Whitney U or χ2 tests. Receiver operating characteristic (ROC) curve analysis was used to determine the diagnostic value of AFP, G-test, and AAR for HCC. Results G-test, AFP, and AAR were all found to have close correlations with HCC among the different patient groups, with G-test being the most predictive for HCC among healthy and CL patients, as represented by respective areas under the curve (AUC) of 0.953 and 0.792 (P < 0.001). By contrast, AAR had the greatest diagnostic ability for HCC among CH patients (AUC = 0.850; P < 0.001). However, the combination of all 3 biomarkers obtained the most optimal results for predicting HCC onset, in terms of predictive capability for all 3 non-HCC patient groups, yielding AUCs of 0.958, 0.898, and 0.808 (P < 0.001) for, respectively, healthy, CH, and LC patients. Additionally, AFP had higher specificity, but lower sensitivity, with increased threshold values, as the recommended threshold of AFP ≥ 400 ng/mL yielded a missed diagnosis rate of 72.7%. For AFP-negative HCC (AFP-NHCC) patients, G-test alone had the greatest diagnostic capability (AUC = 0.855; P < 0.001), sensitivity (83.8%), and specificity (87.5%). Conclusion G-test has the greatest diagnostic capability for HCC and AFP-NHCC, with high sensitivity and specificity, among healthy and LC patients. However, AAR had the highest diagnostic capability and sensitivity for HCC in CH. Overall, though, the combination of G-test, AFP and AAR provided the most optimal outcomes for predicting HCC onset, no matter the patient pre-conditions.

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NFI, a clinical scoring tool for predicting non-alcoholic fatty liver in the Chinese population

Cited by 4 publications

References 41 publications

Higher serum uric acid to HDL-cholesterol ratio is associated with onset of non-alcoholic fatty liver disease in a non-obese Chinese population with normal blood lipid levels

Higher serum uric acid to HDL-cholesterol ratio is associated with onset of non-alcoholic fatty liver disease in a non-obese Chinese population with normal blood lipid levels

Development and application of a novel model to predict the risk of non-alcoholic fatty liver disease among lean pre-diabetics with normal blood lipid levels

The combination of serum oligosaccharide chain (G-test), alpha-fetoprotein, and aspartate aminotransferase to alanine aminotransferase ratio provides the optimal diagnostic value for early detection of hepatocellular carcinoma

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