METHODS: Cost-effectiveness analysis used decision tree and Markov models to estimate lifetime costs and health benefits from societal perspective, based on a cohort of 509 metabolic syndrome patients in Thailand. Data were obtained from published literatures and Thai database. Results were reported as incremental cost-effectiveness ratios (ICERs) in 2014 US dollars (USD) per quality-adjusted life year (QALY) gained with discount rate of 3%. Sensitivity analyses were performed to assess the influence of parameter uncertainty on the results.
RESULTS: The ICER of ultrasonography screening of 50-year-old metabolic syndrome patients with intensive weight reduction program was 958 USD/QALY gained when compared with no screening. The probability of being cost-effective was 67% using willingness-to-pay threshold in Thailand (4848 USD/QALY gained). Screening before 45 years was cost saving while screening at 45 to 64 years was cost-effective.
CONCLUSIONS: For patients with metabolic syndromes, ultrasonography screening for NAFLD with intensive weight reduction program is a cost-effective program in Thailand. Study can be used as part of evidence-informed decision making.
TRANSLATIONAL IMPACTS: Findings could contribute to changes of NAFLD diagnosis practice in settings where economic evidence is used as part of decision-making process. Furthermore, study design, model structure, and input parameters could also be used for future research addressing similar questions.
METHODS: A total of 509 patients with MetS were recruited. All were diagnosed by clinicians with ultrasonography-confirmed whether they were patients with NAFLD. Patients were randomly divided into derivation (n=400) and validation (n=109) cohort. To develop the risk score, clinical risk indicators measured at the time of recruitment were built by logistic regression. Regression coefficients were transformed into item scores and added up to a total score. A risk scoring scheme was developed from clinical predictors: BMI ≥25, AST/ALT ≥1, ALT ≥40, type 2 diabetes mellitus and central obesity. The scoring scheme was applied in validation cohort to test the performance.
RESULTS: The scheme explained, by area under the receiver operating characteristic curve (AuROC), 76.8% of being NAFLD with good calibration (Hosmer-Lemeshow χ2 =4.35; P=.629). The positive likelihood ratio of NAFLD in patients with low risk (scores below 3) and high risk (scores 5 and over) were 2.32 (95% CI: 1.90-2.82) and 7.77 (95% CI: 2.47-24.47) respectively. When applied in validation cohort, the score showed good performance with AuROC 76.7%, and illustrated 84%, and 100% certainty in low- and high-risk groups respectively.
CONCLUSIONS: A simple and non-invasive scoring scheme of five predictors provides good prediction indices for NAFLD in MetS patients. This scheme may help clinicians in order to take further appropriate action.
METHODS: We performed a retrospective analysis of data from 759 patients with biopsy-proven NAFLD (24% with advanced fibrosis), seen at 10 centers in 9 countries in Asia, from 2006 through 2018. By using liver biopsies as the reference standard, we calculated percentages of misclassifications and indeterminate or discordant results from assessments made based on fibrosis scores (NAFLD fibrosis score [NFS] or Fibrosis-4 score) and liver stiffness measurements (LSMs), alone or in combination. The analysis was repeated using randomly selected subgroups with a different prevalence of advanced fibrosis (histologic fibrosis stage ≥F3).
RESULTS: In groups in which 3.7% and 10% of patients had advanced fibrosis, a 2-step approach (using the NFS followed by LSM only for patients with indeterminate or high NFS) and using a gray zone of 10 to 15 kPa for LSM, produced indeterminate or discordant results for 6.9% of patients and misclassified 2.7% of patients; only 25.6% of patients required LSM. In the group in which 10% of patients had advanced fibrosis, the same approach produced indeterminate or discordant results for 7.9% of patients and misclassified 6.6% of patients; only 27.4% of patients required LSM. In groups in which 24% and 50% of patients had advanced fibrosis, using LSM ≥10 kPa alone for the diagnosis of advanced fibrosis had the highest accuracy and misclassified 18.1% and 18.3% of patients, respectively. These results were similar when the Fibrosis-4 score was used in place of NFS.
CONCLUSIONS: In a retrospective analysis, we found that a 2-step approach using fibrosis scores followed by LSM most accurately detects advanced fibrosis in populations with a low prevalence of advanced fibrosis. However, LSM ≥10 kPa identifies patients with advanced fibrosis with the highest level of accuracy in populations with a high prevalence of advanced fibrosis.
AIM: To identify the association of baseline GGT level and QRISK2 score among patients with biopsy-proven nonalcoholic fatty liver disease (NAFLD).
METHODS: This was a retrospective study involving 1535 biopsy-proven NAFLD patients from 10 Asian centers in 8 countries using data collected by the Gut and Obesity in Asia (referred to as "GO ASIA") workgroup. All patients with available baseline GGT levels and all 16 variables for the QRISK2 calculation (QRISK2-2017; developed by researchers at the United Kingdom National Health Service; https://qrisk.org/2017/; 10-year cardiovascular risk estimation) were included and compared to healthy controls with the same age, sex, and ethnicity. Relative risk was reported. QRISK2 score > 10% was defined as the high-CVD-risk group. Fibrosis stages 3 and 4 (F3 and F4) were considered advanced fibrosis.
RESULTS: A total of 1122 patients (73%) had complete data and were included in the final analysis; 314 (28%) had advanced fibrosis. The median age (interquartile range [IQR]) of the study population was 53 (44-60) years, 532 (47.4%) were females, and 492 (43.9%) were of Chinese ethnicity. The median 10-year CVD risk (IQR) was 5.9% (2.6-10.9), and the median relative risk of CVD over 10 years (IQR) was 1.65 (1.13-2.2) compared to healthy individuals with the same age, sex, and ethnicity. The high-CVD-risk group was significantly older than the low-risk group (median [IQR]: 63 [59-67] vs 49 [41-55] years; P < 0.001). Higher fibrosis stages in biopsy-proven NAFLD patients brought a significantly higher CVD risk (P < 0.001). Median GGT level was not different between the two groups (GGT [U/L]: Median [IQR], high risk 60 [37-113] vs low risk 66 [38-103], P = 0.56). There was no correlation between baseline GGT level and 10-year CVD risk based on the QRISK2 score (r = 0.02).
CONCLUSION: The CVD risk of NAFLD patients is higher than that of healthy individuals. Baseline GGT level cannot predict CVD risk in NAFLD patients. However, advanced fibrosis is a predictor of a high CVD risk.
METHODS: 1812 biopsy-proven NAFLD patients across nine countries in Asia assessed between 2006 and 2019 were pooled into a curated clinical registry. Demographic, metabolic and histological differences between non-obese and obese NAFLD patients were evaluated. The performance of Fibrosis-4 index for liver fibrosis (FIB-4) and NAFLD fibrosis score (NFS) to identify advanced liver disease across the varying obesity subgroups was compared. A random forest analysis was performed to identify novel predictors of fibrosis and steatohepatitis in non-obese patients.
FINDINGS: One-fifth (21.6%) of NAFLD patients were non-obese. Non-obese NAFLD patients had lower proportions of NASH (50.5% vs 56.5%, p = 0.033) and advanced fibrosis (14.0% vs 18.7%, p = 0.033). Metabolic syndrome in non-obese individuals was associated with NASH (OR 1.59, 95% CI 1.01-2.54, p = 0.047) and advanced fibrosis (OR 1.88, 95% CI 0.99-3.54, p = 0.051). FIB-4 performed better than the NFS score (AUROC 81.5% vs 73.7%, p
AIMS: We evaluated the performance of machine learning (ML) and non-patented scores for ruling out SF among NAFLD/MASLD patients.
METHODS: Twenty-one ML models were trained (N = 1153), tested (N = 283), and validated (N = 220) on clinical and biochemical parameters of histologically-proven NAFLD/MASLD patients (N = 1656) collected across 14 centres in 8 Asian countries. Their performance for detecting histological-SF (≥F2fibrosis) were evaluated with APRI, FIB4, NFS, BARD, and SAFE (NPV/F1-score as model-selection criteria).
RESULTS: Patients aged 47 years (median), 54.6% males, 73.7% with metabolic syndrome, and 32.9% with histological-SF were included in the study. Patients with SFvs.no-SF had higher age, aminotransferases, fasting plasma glucose, metabolic syndrome, uncontrolled diabetes, and NAFLD activity score (p 140) was next best in ruling out SF (NPV of 0.757, 0.724 and 0.827 in overall, test and validation set).
CONCLUSIONS: ML with clinical, anthropometric data and simple blood investigations perform better than FIB-4 for ruling out SF in biopsy-proven Asian NAFLD/MASLD patients.