Noninvasive tests for liver fibrosis in 2024: are there different scales for different diseases?

Liver fibrosis is the common pathway from various chronic liver diseases and its progression leads to cirrhosis which carries a significant risk for the development of portal hypertension-related complications and hepatocellular carcinoma. It is crucial to identify and halt the worsening of liver fibrosis given its important prognostic implication. Liver biopsy is the gold standard for assessing the degree of liver fibrosis but is limited due to its invasiveness and impracticality for serial monitoring. Many noninvasive tests have been developed over the years trying to assess liver fibrosis in a practical and accurate way. The tests are mainly laboratory- or imaging-based, or in combination. Laboratory-based tests can be derived from simply routine blood tests to patented laboratory parameters. Imaging modalities include ultrasound and magnetic resonance elastography, in which vibration-controlled transient elastography is the most widely validated and adopted whereas magnetic resonance elastography has been proven the most accurate liver fibrosis assessment tool. Nonetheless, noninvasive tests do not always apply to all liver diseases, nor does a common cut-off value of a test mean the same degree of liver fibrosis in different scenarios. In this review, we discuss the diagnostic and prognostic performance, as well as the confounders and limitations, of different noninvasive tests on liver fibrosis assessment in various liver diseases.

CAMP-B score predicts the risk of hepatocellular carcinoma in patients with chronic hepatitis B after HBsAg seroclearance.

BACKGROUND: Risk of hepatocellular carcinoma (HCC) persists after hepatitis B surface antigen (HBsAg) seroclearance in patients with chronic hepatitis B (CHB). AIMS: To identify risk factors and construct a predictive model for HCC development. METHODS: We retrospectively analysed patients with CHB with HBsAg seroclearance. Primary outcome was HCC development. Factors identified from a multivariate Cox model in the training cohort, consisting of 3476 patients from two Korean hospitals, were used to construct the prediction model. External validation was performed using data from 5255 patients in Hong Kong. RESULTS: In the training cohort, HCC occurred in 102 patients during 24,019 person-years of observation (0.43%/year). Risk scores were assigned to cirrhosis (C:3), age ≥50 years (A:2), male sex (M:3) and platelet count <150,000/mm3 (P:1); all were independently associated with an increased risk of HCC in multivariate analysis The time-dependent area under receiver operating characteristic curves for 5, 10 and 15 years in the training and validation cohorts were 0.782, 0.817 and 0.825 and 0.785, 0.771 and 0.796, respectively. In the validation cohort, 85 patients developed HCC (0.24%/year). The corresponding incidence of HCC in the low-, intermediate- and high-risk groups were 0.07%, 0.37% and 0.90%, respectively. CONCLUSIONS: The CAMP-B score (cirrhosis, age ≥50 years, male sex and platelet count <150,000/mm3/L) was significantly associated with HCC development after HBsAg seroclearance. CAMP-B score can be easily implemented in real-world clinical practice and helps stratify HCC risk in patients with CHB following HBsAg seroclearance.

Serum PRO-C3 is useful for risk prediction and fibrosis assessment in MAFLD with chronic kidney disease in an Asian cohort.

BACKGROUND: Metabolic dysfunction-associated fatty liver disease (MAFLD) is an emerging risk factor for chronic kidney disease (CKD). N-terminal propeptide of collagen type 3 (PRO-C3) is a biomarker of advanced fibrosis in MAFLD and PRO-C3 may be involved in renal fibrosis. We aimed to use PRO-C3 measurements to generate a new algorithmic score to test the prediction of MAFLD with chronic kidney disease (MAFLD-CKD). METHODS: A derivation and independent validation cohort of 750 and 129 Asian patients with biopsy-confirmed MAFLD were included. Serum PRO-C3 concentration was measured and regression analyses were performed to examine associations with MAFLD-CKD. A derivative algorithm for MAFLD-CKD risk prediction was evaluated with receiver operator characteristic (ROC) curve analysis. RESULTS: The study included two Asian cohorts (n = 180 with MAFLD-CKD; mean-eGFR: 94.93 mL/min/1.73 m2; median-urinary albumin-to-creatinine ratio: 6.58 mg/mmol). PRO-C3 was associated with the severity of MAFLD-CKD and independently associated with MAFLD-CKD (adjusted odds ratio = 1.16, 95% confidence interval [CI]: 1.08-1.23, p < .001). A new non-invasive score (termed PERIOD) including PRO-C3 efficiently predicted MAFLD-CKD (AUROC = .842, 95% CI: .805-.875). Accuracy, specificity and negative predictive values were 80.2%, 85.1% and 88.4%, respectively. In the validation cohort, the PERIOD score had good diagnostic performance (AUROC = .807, 95% CI: .691-.893) with similar results in all patient subgroups. In the MAFLD-CKD subgroup, the accuracy for identifying advanced fibrosis was further improved by combining the PRO-C3-based ADAPT with the Agile 3+ scores (AUROC = .90, 95% CI: .836-.964). CONCLUSIONS: The PERIOD score is helpful for accurately predicting the risk of MAFLD-CKD. PRO-C3 can also be used to assess liver fibrosis in people with MAFLD-CKD.

Vibration-Controlled Transient Elastography Scores to Predict Liver-Related Events in Steatotic Liver Disease.

Importance: Metabolic dysfunction-associated steatotic liver disease (MASLD) is currently the most common chronic liver disease worldwide. It is important to develop noninvasive tests to assess the disease severity and prognosis. Objective: To study the prognostic implications of baseline levels and dynamic changes of the vibration-controlled transient elastography (VCTE)-based scores developed for the diagnosis of advanced fibrosis (Agile 3+) and cirrhosis (Agile 4) in patients with MASLD. Design, Setting, and Participants: This cohort study included data from a natural history cohort of patients with MASLD who underwent VCTE examination at 16 tertiary referral centers in the US, Europe, and Asia from February 2004 to January 2023, of which the data were collected prospectively at 14 centers. Eligible patients were adults aged at least 18 years with hepatic steatosis diagnosed by histologic methods (steatosis in ≥5% of hepatocytes) or imaging studies (ultrasonography, computed tomography or magnetic resonance imaging, or controlled attenuation parameter ≥248 dB/m by VCTE). Main Outcomes and Measures: The primary outcome was liver-related events (LREs), defined as hepatocellular carcinoma or hepatic decompensation (ascites, variceal hemorrhage, hepatic encephalopathy, or hepatorenal syndrome), liver transplant, and liver-related deaths. The Agile scores were compared with histologic and 8 other noninvasive tests. Results: A total of 16 603 patients underwent VCTE examination at baseline (mean [SD] age, 52.5 [13.7] years; 9600 [57.8%] were male). At a median follow-up of 51.7 (IQR, 25.2-85.2) months, 316 patients (1.9%) developed LREs. Both Agile 3+ and Agile 4 scores classified fewer patients between the low and high cutoffs than most fibrosis scores and achieved the highest discriminatory power in predicting LREs (integrated area under the time-dependent receiver-operating characteristic curve, 0.89). A total of 10 920 patients (65.8%) had repeated VCTE examination at a median interval of 15 (IQR, 11.3-27.7) months and were included in the serial analysis. A total of 81.9% of patients (7208 of 8810) had stable Agile 3+ scores and 92.6% of patients (8163 of 8810) had stable Agile 4 scores (same risk categories at both assessments). The incidence of LREs was 0.6 per 1000 person-years in patients with persistently low Agile 3+ scores and 30.1 per 1000 person-years in patients with persistently high Agile 3+ scores. In patients with high Agile 3+ score at baseline, a decrease in the score by more than 20% was associated with substantial reduction in the risk of LREs. A similar trend was observed for the Agile 4 score, although it missed more LREs in the low-risk group. Conclusions and Relevance: Findings of this study suggest that single or serial Agile scores are highly accurate in predicting LREs in patients with MASLD, making them suitable alternatives to liver biopsy in routine clinical practice and in phase 2b and 3 clinical trials for steatohepatitis.

Chronic hepatitis B baseline viral load and on-treatment liver cancer risk: A multinational cohort study of HBeAg-positive patients.

BACKGROUND AND AIMS: A single-nation study reported that pretreatment HBV viral load is associated with on-treatment risk of HCC in patients who are HBeAg-positive without cirrhosis and with chronic hepatitis B initiating antiviral treatment. We aimed to validate the association between baseline HBV viral load and on-treatment HCC risk in a larger, multinational cohort. APPROACH AND RESULTS: Using a multinational cohort from Korea, Hong Kong, and Taiwan involving 7545 adult patients with HBeAg-positive, without cirrhosis and with chronic hepatitis B who started entecavir or tenofovir treatment with baseline HBV viral load ≥5.00 log 10 IU/mL, HCC risk was estimated by baseline viral load. HBV viral load was analyzed as a categorical variable. During continuous antiviral treatment (median, 4.28 y), HCC developed in 200 patients (incidence rate, 0.61 per 100 person-years). Baseline HBV DNA level was independently associated with on-treatment HCC risk in a nonlinear pattern. HCC risk was lowest with the highest baseline viral load (≥8.00 log 10 IU/mL; incidence rate, 0.10 per 100 person-years), but increased sharply as baseline viral load decreased. The adjusted HCC risk was 8.05 times higher (95% CI, 3.34-19.35) with baseline viral load ≥6.00 and <7.00 log 10 IU/mL (incidence rate, 1.38 per 100 person-years) compared with high (≥8.00 log 10 IU/mL) baseline viral load ( p <0.001). CONCLUSIONS: In a multinational cohort of adult patients with HBeAg-positive without cirrhosis and with chronic hepatitis B, baseline HBV viral load was significantly associated with HCC risk despite antiviral treatment. Patients with the highest viral load who initiated treatment had the lowest long-term risk of HCC development.

Machine learning improves the prediction of significant fibrosis in Asian patients with metabolic dysfunction-associated steatotic liver disease - The Gut and Obesity in Asia (GO-ASIA) Study.

BACKGROUND: The precise estimation of cases with significant fibrosis (SF) is an unmet goal in non-alcoholic fatty liver disease (NAFLD/MASLD). 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 < 0.001, each). ML models showed 7%-12% better discrimination than FIB-4 to detect SF. Optimised random forest (RF) yielded best NPV/F1 in overall set (0.947/0.754), test set (0.798/0.588) and validation set (0.852/0.559), as compared to FIB4 in overall set (0.744/0.499), test set (0.722/0.456), and validation set (0.806/0.507). Compared to FIB-4, RF could pick 10 times more patients with SF, reduce unnecessary referrals by 28%, and prevent missed referrals by 78%. Age, AST, ALT fasting plasma glucose, and platelet count were top features determining the SF. Sequential use of SAFE < 140 and FIB4 < 1.2 (when SAFE > 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.

Reply to Allaire, M.; Thabut, D. Comment on "Wu et al. Baveno VII Criteria Is an Accurate Risk Stratification Tool to Predict High-Risk Varices Requiring Intervention and Hepatic Events in Patients with Advanced Hepatocellular Carcinoma. Cancers 2023, 15, 2480".

We thank Allaire et al [...].

A Liver Stiffness-Based Etiology-Independent Machine Learning Algorithm to Predict Hepatocellular Carcinoma.

BACKGROUND & AIMS: The existing hepatocellular carcinoma (HCC) risk scores have modest accuracy, and most are specific to chronic hepatitis B infection. In this study, we developed and validated a liver stiffness-based machine learning algorithm (ML) for prediction and risk stratification of HCC in various chronic liver diseases (CLDs). METHODS: MLs were trained for prediction of HCC in 5155 adult patients with various CLDs in Korea and further tested in 2 prospective cohorts from Hong Kong (HK) (N = 2732) and Europe (N = 2384). Model performance was assessed according to Harrell's C-index and time-dependent receiver operating characteristic (ROC) curve. RESULTS: We developed the SMART-HCC score, a liver stiffness-based ML HCC risk score, with liver stiffness measurement ranked as the most important among 9 clinical features. The Harrell's C-index of the SMART-HCC score in HK and Europe validation cohorts were 0.89 (95% confidence interval, 0.85-0.92) and 0.91 (95% confidence interval, 0.87-0.95), respectively. The area under ROC curves of the SMART-HCC score for HCC in 5 years was ≥0.89 in both validation cohorts. The performance of SMART-HCC score was significantly better than existing HCC risk scores including aMAP score, Toronto HCC risk index, and 7 hepatitis B-related risk scores. Using dual cutoffs of 0.043 and 0.080, the annual HCC incidence was 0.09%-0.11% for low-risk group and 2.54%-4.64% for high-risk group in the HK and Europe validation cohorts. CONCLUSIONS: The SMART-HCC score is a useful machine learning-based tool for clinicians to stratify HCC risk in patients with CLDs.

Prevalence and risk factors for impaired renal function among Asian patients with nonalcoholic fatty liver disease.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is associated with impaired renal function, and both diseases often occur alongside other metabolic disorders. However, the prevalence and risk factors for impaired renal function in patients with NAFLD remain unclear. The objective of this study was to identify the prevalence and risk factors for renal impairment in NAFLD patients. METHODS: All adults aged 18-70 years with ultrasound-diagnosed NAFLD and transient elastography examination from eight Asian centers were enrolled in this prospective study. Liver fibrosis and cirrhosis were assessed by FibroScan-aspartate aminotransferase (FAST), Agile 3+ and Agile 4 scores. Impaired renal function and chronic kidney disease (CKD) were defined by an estimated glomerular filtration rate (eGFR) with value of < 90 mL/min/1.73 m2 and < 60 mL/min/1.73 m2, respectively, as estimated by the CKD-Epidemiology Collaboration (CKD-EPI) equation. RESULTS: Among 529 included NAFLD patients, the prevalence rates of impaired renal function and CKD were 37.4% and 4.9%, respectively. In multivariate analysis, a moderate-high risk of advanced liver fibrosis and cirrhosis according to Agile 3+ and Agile 4 scores were independent risk factors for CKD (P< 0.05). Furthermore, increased fasting plasma glucose (FPG) and blood pressure were significantly associated with impaired renal function after controlling for the other components of metabolic syndrome (P< 0.05). Compared with patients with normoglycemia, those with prediabetes [FPG ≥ 5.6 mmol/L or hemoglobin A1c (HbA1c) ≥ 5.7%] were more likely to have impaired renal function (P< 0.05). CONCLUSIONS: Agile 3+ and Agile 4 are reliable for identifying NAFLD patients with high risk of CKD. Early glycemic control in the prediabetic stage might have a potential renoprotective role in these patients.

Atherosclerotic cardiovascular disease risk profile of patients with chronic hepatitis B treated with tenofovir alafenamide or tenofovir disoproxil fumarate for 96 weeks.

BACKGROUND: Patients with chronic hepatitis B (CHB) who switch from tenofovir disoproxil fumarate (TDF) to tenofovir alafenamide (TAF) show changes in lipid profiles. AIM: To evaluate how these changes affect cardiovascular risk. METHODS: This pooled analysis, based on two large prospective studies, evaluated fasting lipid profiles of patients with CHB who were treated with TAF 25 mg/day or TDF 300 mg/day for 96 weeks. Patients who fulfilled the American College of Cardiology criteria (age 40-79 years, high-density lipoprotein [HDL] 20-100 mg/dL, total cholesterol [TC] 130-320 mg/dL and systolic blood pressure 90-200 mmHg) required to assess 10-year atherosclerotic cardiovascular disease (ASCVD) risk with baseline lipid data and at least one post-baseline measurement were included in the ASCVD-risk population. The 10-year ASCVD risk was calculated for patients in this population, and changes from baseline to Week 96 were assessed using intermediate- (≥7.5%) and high-risk (≥20%) cut-offs. RESULTS: Among 1632 patients, 620 (38%) met the criteria for the ASCVD-risk population. At Week 96, fasting levels of all lipids, except TC:HDL ratio, were lower with TDF than TAF. No significant increase was observed in overall ASCVD risk or in any ASCVD-risk categories during the 96-week treatment period compared with baseline. A similar proportion of patients in the TAF and TDF treatment groups (1.3% and 2.3%, respectively; p = 0.34) reported cardiovascular events. CONCLUSION: Despite on-treatment differences in lipid profiles with TAF and TDF, predicted cardiovascular risk and clinical events were similar for both groups after 96 weeks.

Long-term use of tenofovir disoproxil fumarate increases fracture risk in elderly patients with chronic hepatitis B.

BACKGROUND & AIMS: The use of tenofovir disoproxil fumarate (TDF) is associated with a reduction in bone mineral density and an increase in bone metabolism biomarkers. However, data on clinical bone fractures remain limited. We evaluated the impact of TDF compared to entecavir on the risk of fracture in elderly patients with chronic hepatitis B (CHB). METHODS: Patients with CHB aged ≥60 years receiving entecavir or TDF between January 2008 and December 2022 were identified using a territory-wide database in Hong Kong. The risk of incident fracture in entecavir- and TDF-treated patients before and after month 24 were compared after propensity score matching. RESULTS: A total of 41,531 patients with CHB (mean age 69.8±7.8 years, 61.6% male) receiving entecavir (n = 39,897 [96.1%]) and TDF (n = 1,634 [3.9%]) were analysed. At a median follow-up of 25.3 (9.1-58.5) months, 1,733 (4.2%) patients developed incident fracture. Patients with incident fracture were more likely to have diabetes, hypertension, congestive heart failure, rheumatoid arthritis, osteoporosis, and a history of fracture. Compared with propensity score-matched entecavir-treated patients, the risk of incident fracture in TDF-treated patients was comparable in the first 24 months (weighted subdistribution hazard ratio [sHR] 0.99, 95% CI 0.56-1.73, p = 0.960) but increased after month 24 (weighted sHR 1.80, 95% CI 1.11-2.93, p = 0.019). The 24-, 60-, and 96-month cumulative incidences (95% CI) of fracture in TDF-treated and entecavir-treated patients were 2.3% (1.6%-3.4%) vs. 2.6% (1.9%-3.5%), 6.4% (5.0%-8.2%) vs. 4.7% (3.8%-6.0%), and 10.2% (8.3%-12.6%) vs. 6.8% (5.4%-8.5%), respectively. CONCLUSIONS: The risk of fracture increased with TDF treatment for ≥24 months in elderly patients with CHB. Selection of nucleos(t)ide analogues should be individualised based on age and comorbidities. IMPACT AND IMPLICATIONS: Previous literature suggested that the use of tenofovir disoproxil fumarate (TDF) is associated with a decrease in bone mineral density. However, data on the impact of TDF on long-term incident clinical fracture remains scarce. In this real-world territory-wide study of 41,531 treated patients with chronic hepatitis B in Hong Kong, patients who received TDF were at a higher risk of fracture after 2 years of treatment than those who received entecavir. Given the ageing population of patients with chronic hepatitis B and the rising prevalence of comorbidities, our findings support the current treatment guidelines that recommend selecting antiviral treatment based on age and comorbidities.

Machine-learning model comprising five clinical indices and liver stiffness measurement can accurately identify MASLD-related liver fibrosis.

BACKGROUND & AIMS: aMAP score, as a hepatocellular carcinoma risk score, is proven to be associated with the degree of chronic hepatitis B-related liver fibrosis. We aimed to evaluate the ability of aMAP score for metabolic dysfunction-associated steatotic liver disease (MASLD; formerly NAFLD)-related fibrosis diagnosis and establish a machine-learning (ML) model to improve the diagnostic performance. METHODS: A total of 946 biopsy-proved MASLD patients from China and the United States were included in the analysis. The aMAP score, demographic/clinical indices and liver stiffness measurement (LSM) were included in seven ML algorithms to build fibrosis diagnostic models in the training set (N = 703). The performance of ML models was evaluated in the external validation set (N = 125). RESULTS: The AUROCs of aMAP versus fibrosis-4 index (FIB-4) and aspartate aminotransferase-platelet ratio (APRI) in cirrhosis and advanced fibrosis were (0.850 vs. 0.857 [P = 0.734], 0.735 [P = 0.001]) and (0.759 vs. 0.795 [P = 0.027], 0.709 [P = 0.049]). When using dual cut-off values, aMAP had a smaller uncertainty area and higher accuracy (26.9%, 86.6%) than FIB-4 (37.3%, 85.0%) and APRI (59.0%, 77.3%) in cirrhosis diagnosis. The seven ML models performed satisfactorily in most cases. In the validation set, the ML model comprising LSM and 5 indices (including age, sex, platelets, albumin and total bilirubin used in aMAP calculator), built by logistic regression algorithm (called LSM-plus model), exhibited excellent performance. In cirrhosis and advanced fibrosis detection, the LSM-plus model had higher accuracy (96.8%, 91.2%) than LSM alone (86.4%, 67.2%) and Agile score (76.0%, 83.2%), respectively. Additionally, the LSM-plus model also displayed high specificity (cirrhosis: 98.3%; advanced fibrosis: 92.6%) with satisfactory AUROC (0.932, 0.875, respectively) and sensitivity (88.9%, 82.4%, respectively). CONCLUSIONS: The aMAP score is capable of diagnosing MASLD-related fibrosis. The LSM-plus model could accurately identify MASLD-related cirrhosis and advanced fibrosis.

Local Style Transfer via Latent Space Manipulation for Cross-Disease Lesion Segmentation.

Automatic lesion segmentation is important for assisting doctors in the diagnostic process. Recent deep learning approaches heavily rely on large-scale datasets, which are difficult to obtain in many clinical applications. Leveraging external labelled datasets is an effective solution to tackle the problem of insufficient training data. In this paper, we propose a new framework, namely LatenTrans, to utilize existing datasets for boosting the performance of lesion segmentation in extremely low data regimes. LatenTrans translates non-target lesions into target-like lesions and expands the training dataset with target-like data for better performance. Images are first projected to the latent space via aligned style-based generative models, and rich lesion semantics are encoded using the latent codes. A novel consistency-aware latent code manipulation module is proposed to enable high-quality local style transfer from non-target lesions to target-like lesions while preserving other parts. Moreover, we propose a new metric, Normalized Latent Distance, to solve the question of how to select an adequate one from various existing datasets for knowledge transfer. Extensive experiments are conducted on segmenting lung and brain lesions, and the experimental results demonstrate that our proposed LatenTrans is superior to existing methods for cross-disease lesion segmentation.

MAFLD fibrosis score: Using routine measures to identify advanced fibrosis in metabolic-associated fatty liver disease.

BACKGROUND: Early screening may prevent fibrosis progression in metabolic-associated fatty liver disease (MAFLD). AIMS: We developed and validated MAFLD fibrosis score (MFS) for identifying advanced fibrosis (≥F3) among MAFLD patients. METHODS: This cross-sectional, multicentre study consecutively recruited MAFLD patients receiving tertiary care (Malaysia as training cohort [n = 276] and Hong Kong and Wenzhou as validation cohort [n = 431]). Patients completed liver biopsy, vibration-controlled transient elastography (VCTE), and clinical and laboratory assessment within 1 week. We used machine learning to select 'highly important' predictors of advanced fibrosis, followed by backward stepwise regression to construct MFS formula. RESULTS: MFS was composed of seven variables: age, body mass index, international normalised ratio, aspartate aminotransferase, gamma-glutamyl transpeptidase, platelet count, and history of type 2 diabetes. MFS demonstrated an area under the receiver-operating characteristic curve of 0.848 [95% CI 0.800-898] and 0.823 [0.760-0.886] in training and validation cohorts, significantly higher than aminotransferase-to-platelet ratio index (0.684 [0.603-0.765], 0.663 [0.588-0.738]), Fibrosis-4 index (0.793 [0.735-0.854], 0.737 [0.660-0.814]), and non-alcoholic fatty liver disease fibrosis score (0.785 [0.731-0.844], 0.750 [0.674-0.827]) (DeLong's test p < 0.05). MFS could include 92.3% of patients using dual cut-offs of 14 and 15, with a correct prediction rate of 90.4%, resulting in a larger number of patients with correct diagnosis compared to other scores. A two-step MFS-VCTE screening algorithm demonstrated positive and negative predictive values and overall diagnostic accuracy of 93.4%, 89.5%, and 93.2%, respectively, with only 4.0% of patients classified into grey zone. CONCLUSION: MFS outperforms conventional non-invasive scores in predicting advanced fibrosis, contributing to screening in MAFLD patients.