Low Accuracy of FIB-4 and NAFLD Fibrosis Scores for Screening for Liver Fibrosis in the Population

Diagnostic Accuracy of the LiverRisk Score to Detect Increased Liver Stiffness Among a United States General Population and Subgroups

Background

The LiverRisk score (LRS) has recently been proposed to predict liver fibrosis and future development of liver-related outcomes in the general population. Here, we performed an external validation of this score.

Methods

We used data from National Health and Nutrition Examination Survey 2017-2020, a United States population-based cohort to assess the diagnostic accuracy of the LRS to detect a liver stiffness measurement (LSM) ≥8 and ≥12 kPa. Performance was tested among the entire general population and clinically relevant subgroups.

Results

The cohort comprised 7,025 participants (aged 49 [33-63], 49% male), and 9.7% had an LSM ≥8 and 3.2% had an LSM ≥12 kPa. The area under the receiver characteristic operator curve (AUC) in the overall population was 0.73 (95% confidence interval [CI] :0.71-0.75) and 0.78 (95% CI: 0.74-0.81) to detect an LSM ≥8 and ≥ 12 kPa, respectively, significantly outperforming the fibrosis 4 index (FIB-4) but not the nonalcoholic fatty liver disease fibrosis score, steatosis-associated fibrosis estimator (SAFE), or metabolic dysfunction-associated fibrosis 5 (MAF-5). Performance was consistent among most subgroups, but AUC levels to detect an LSM ≥8 kPa decreased to <0.70 among participants aged 18-40 or 60-80 years, blacks, and individuals with diabetes or liver steatosis. The LRS categorized 80.5% as very low risk, 17.7% as low risk, and 1.8% as at risk, prevalence of an LSM ≥8 in these groups was 6.3%, 20.8%, and 50.5%, respectively. The sensitivity to detect an LSM ≥8 kPa was 47.3% in the overall population (but dropped to 21.3% for individuals aged 18-40 years) despite applying the lowest cut-off, which should yield the highest sensitivity.

Conclusion

The LRS score is a promising new tool to predict liver fibrosis; however, its diagnostic accuracy attenuates especially among patients aged 18-40 or 60-80 years. The overall sensitivity was only 47.3% at the lowest LRS cut-off. Further studies assessing cost-benefit ratios according to the LRS compared to FIB-4 and other risk scores such as MAF-5 and SAFE are required to determine its usefulness in referral strategies.

Efficacy of [68Ga]Ga-FAPI-PET as a non-invasive evaluation method of liver fibrosis

INTRODUCTION

Liver fibrosis is a chronic fibrosing hepatic disorder following recurrent injury, characterized by the excessive accumulation of extracellular matrix. Early detection has a great clinical impact because 80-90% of hepatocellular carcinomas are known to develop in fibrotic or cirrhotic (end-stage fibrotic) livers. PET imaging with FAP ligands exhibited highly promising results in recent years to visualize fibrosis in various organs due to the crucial role of activated fibroblasts in fibrosing processes. However, still little is known about the efficacy of FAP imaging in liver fibrosis. Thus, we sought to investigate the potential of FAPI-PET in a cohort of oncological and non-oncological patients.

METHODS

199 patients who underwent FAPI-PET/CT at the University Hospital of Heidelberg between July 2017 and July 2020 were retrospectively analyzed. The tracer uptake of the liver was analyzed and correlated with radiological and clinical parameters.

RESULTS

We observed a weak but significant negative correlation between the hepatic FAPI uptake and CT density (r = - 0.273, P < 0.001***). A positive correlation was observed between hepatic FAPI uptake and the aspartate aminotransferase (AST)-to-platelet ratio index (APRI) (r = 0.183, P = 0.009**), an established surrogate for liver fibrosis. The liver SUV (standardized uptake value) mean and SUVmax of FAPI showed significant differences between groups of patients with low (< 0.5), middle (0.5-1.0) and higher (> 1.0) levels of APRI (both P < 0.001***).

CONCLUSION

These preliminary observational results suggest that FAPI-PET may be a viable non-invasive method to asses liver fibrosis.

Detection of Undiagnosed Liver Cirrhosis via Artificial Intelligence-Enabled Electrocardiogram (DULCE): Rationale and design of a pragmatic cluster randomized clinical trial

Background

Cirrhosis is a leading cause of morbidity and mortality worldwide, yet preventable at early stages. Currently, effective approaches for early diagnosis are lacking. A novel electrocardiogram (ECG)-enabled deep learning model trained for detection of advanced chronic liver disease (CLD) has demonstrated promising results and it may be used for screening of advanced CLD in primary care.

Design

A pragmatic, cluster randomized trial (NCT05782283) in 45 Mayo Clinic primary care practices will be conducted over a period of 6 months with 6 months of follow up. Care teams will be randomized 1:1 to intervention or usual care, stratified by region and patient volume. Patients from providers enrolled in the trial who undergo an ECG during the study period will be included. In the intervention arm, consenting providers to patients identified as higher risk of advanced CLD based on their ECG will be notified with a recommendation for noninvasive fibrosis assessment. The primary endpoint will be detection of advanced CLD (defined as stage 3-4 on blood- or imaging-based noninvasive liver disease assessment or liver biopsy). Secondary outcomes will include completion of fibrosis assessment tests within 180 days of ECG, new diagnosis of liver disease stratified by etiology and risk factors for CLD, and detection of any liver fibrosis (stages 1-4). Post-study surveys to participating clinicians will be conducted.

Summary

Preliminary findings suggest outstanding potential for the use of an ECG-enabled machine learning algorithm for detection of advanced CLD in the primary care community.

Increased prevalence and risk of atherosclerotic cardiovascular disease in individuals with Type 1 diabetes and metabolic dysfunction-associated steatotic liver disease

OBJECTIVE

This study aimed to investigate the correlation between metabolic dysfunction-associated steatotic liver disease (MASLD) and atherosclerotic cardiovascular disease (ASCVD) in individuals with type 1 diabetes (T1D).

METHODS

Adults with T1D (n = 659) were consecutively screened for liver steatosis via abdominal ultrasound. The presence of macrovascular disease (including coronary artery disease [CAD], peripheral artery disease [PAD], or ischaemic stroke [CVA, cerebrovascular accident]) was identified via electronic medical records. The 5- and 10-year risks of fatal/nonfatal ASCVD were assessed via the Steno Type 1 Risk Engine. Insulin resistance was assessed via the estimated glucose disposal rate (eGDR).

RESULTS

The MASLD prevalence was 16.8%. The prevalence of composite ASCVD (18.9 vs. 6.8%, p < 0.001), CAD (9.9 vs. 4.7%, p = 0.031), PAD (9.0 vs. 2.2%, p < 0.001) and CVA (6.3 vs. 1.1%, p = 0.002) was greater in people with MASLD. The 5-year (7.8 [2.1-14.4] vs. 4.8 [1.6-12.0]%, p = 0.034) and 10-year (15.0 [4.1-26.8] vs. 9.4 [3.1-22.5]%, p = 0.035) risks of ASCVD were greater in those with MASLD. MASLD was associated with prevalent ASCVD (adjusted OR 4.26, 95% CI 1.79-10.11, p < 0.001), independent of age, sex, diabetes duration, smoking, statin use, LDL-cholesterol, the glomerular filtration rate, albuminuria, and metabolic syndrome.

CONCLUSION

MASLD is associated with both an increased prevalence of ASCVD and an increased calculated risk of fatal/nonfatal ASCVD in people with T1D.

Development and Validation of Machine Learning-Based Marker for Early Detection and Prognosis Stratification of Nonalcoholic Fatty Liver Disease

Nonalcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease and is considered the hepatic manifestation of metabolic syndrome, triggering out adverse outcomes. A stacked multimodal machine learning model is constructed and validated for early identification and prognosis stratification of NAFLD by integrating genetic and clinical data sourced from 36 490 UK Biobank and 9 007 Nanfang Hospital participants and extracted its probabilities as in-silico scores for NAFLD (ISNLD). The efficacy of ISNLD is evaluated for the early prediction of severe liver disease (SeLD) and analyzed its association with metabolism-related outcomes. The multimodal model performs satisfactorily in classifying individuals into low- and high-risk groups for NAFLD, achieving area under curves (AUCs) of 0.843, 0.840, and 0.872 within training, internal, and external test sets, respectively. Among high-risk group, ISNLD is significantly associated with intrahepatic and metabolism-related complications after lifestyle factors adjustment. Further, ISNLD demonstrates notable capability for early prediction of SeLD and further stratifies high-risk subjects into three risk subgroups of elevated risk for adverse outcomes. The findings emphasize the model's ability to integrate multimodal features to generate ISNLD, enabling early detection and prognostic prediction of NAFLD. This facilitates personalized stratification for NAFLD and metabolism-related outcomes based on digital non-invasive markers, enabling preventive interventions.

DiabetesLiver score: A non-invasive algorithm for advanced liver fibrosis and liver-related outcomes in type 2 diabetes mellitus population

BACKGROUND

This study aimed to develop and validate a non-invasive model for screening advanced liver fibrosis and predicting liver-related outcomes in patients with type 2 diabetes mellitus (T2DM).

METHODS

This study included patients with T2DM from five tertiary hospitals for the development and internal validation of a non-invasive model. Advanced liver fibrosis was defined as a liver stiffness measurement ≥12 kPa. An external validation cohort was obtained from the National Health and Nutrition Examination Survey (NHANES), and the model's predictive performance for hepatocellular carcinoma (HCC) and liver-related mortality was assessed in the UK Biobank.

FINDINGS

In total, 28,197 patients with T2DM were enrolled. In the derivation cohort (n = 1,129), waist circumference, alanine aminotransferase, aspartate aminotransferase, platelet count, and albumin were identified as independent risk factors for advanced fibrosis and were fit to develop the "DiabetesLiver score." The area under the curve (AUC) was 0.835 (95% confidence interval [CI]: 0.781-0.890), significantly higher than the AUCs of non-invasive tests (all p < 0.01). It maintained high AUCs of 0.870 and 0.823 in the internal validation (n = 1,000), and NHANES cross-sectional (n = 1,432) cohorts, respectively. A dual cutoff of 2.39 and 3.99 with sensitivity ≥90% and specificity ≥90%, respectively, was used to classify patients into low-, middle-, and high-risk groups. In the UK Biobank cohort (n = 24,636), the high-risk group had an elevated risk of liver-related outcomes.

CONCLUSIONS

The DiabetesLiver score demonstrated good performance in identifying advanced liver fibrosis and the development of liver-related events in the T2DM population.

FUNDING

National Natural Science Foundation.

Diagnostic Performance of Noninvasive Tests for Identifying Advanced Fibrosis in Metabolic Dysfunction-Associated Fatty Liver Disease With Mixed Etiologies

OBJECTIVES

To assess the performance of fibrosis-4 index (FIB-4), nonalcoholic fatty liver disease fibrosis score (NFS) and aspartate aminotransferase to platelet ratio index (APRI) for advanced fibrosis in metabolic dysfunction-associated fatty liver disease (MAFLD) subgroups categorized by concomitant liver conditions.

METHODS

We conducted a multicentered study comprising inpatients with type 2 diabetes mellitus and MAFLD. Participants were categorized into 2 groups: MAFLD with pure metabolic etiologies (MAFLD-P) and MAFLD with mixed etiologies (MAFLD-M). Diagnostic performance of FIB-4, NFS, and APRI was assessed by area under the curve (AUC), sensitivity, and specificity.

RESULTS

This study comprised a total of 1475 participants, with a mean (SD) age of 58.4 (13) years and 835 (56.6%) males. FIB-4 and APRI had higher AUCs for advanced fibrosis in the MAFLD-M group than in the MAFLD-P group (MAFLD-M vs MAFLD-P: FIB-4 0.680 vs 0.591, P = .0442; APRI 0.723 vs 0.631, P = .0363). No significant difference was observed in the AUC of NFS between the 2 subgroups (MAFLD-M 0.572 vs MAFLD-P 0.617; P = .3237). Besides, the sensitivity of FIB-4 (69.6% vs 54.0%; P = .019) and APRI (43.5% vs 26.1%; P = .005) was higher in the MAFLD-M group. However, no significant difference in sensitivity of NFS and specificity of FIB-4, NFS, and APRI was observed between subgroups.

CONCLUSIONS

In this diagnostic study of the type 2 diabetes mellitus population, FIB-4 and APRI showed better performance for identifying advanced fibrosis in MAFLD with mixed etiologies.

Global patterns of utilization of noninvasive tests for the clinical management of metabolic dysfunction-associated steatotic liver disease

BACKGROUND

Noninvasive tests (NITs) are used to risk-stratify metabolic dysfunction-associated steatotic liver disease. The aim was to survey global patterns of real-world use of NITs.

METHODS

A 38-item survey was designed by the Global NASH Council. Providers were asked about risks for advanced fibrosis, which NITs (cutoff values) they use to risk-stratify liver disease, monitor progression, and which professional guidelines they follow.

RESULTS

A total of 321 participants from 43 countries completed the survey (54% hepatologists, 28% gastroenterologists, and 18% other). Of the respondents, 85% would risk-stratify patients with type 2 diabetes, obesity (82%), or abnormal liver enzymes (73%). Among NITs to rule out significant or advanced fibrosis, transient elastography (TE) and fibrosis-4 (FIB-4) were most used, followed by NAFLD Fibrosis Score, Enhanced Liver Fibrosis, and magnetic resonance elastography. The cutoffs for ruling out significant fibrosis varied considerably between practices and from guidelines, with only 50% using TE <8 kPa, 65% using FIB-4 <1.30 for age <65, and 41% using FIB-4 <2.00 for age ≥65. Similar variability was found for ruling in advanced fibrosis, where thresholds of FIB-4 ≥2.67 and TE ≥10 kPa were used by 20% and 17%, respectively. To establish advanced fibrosis, 48% would use 2 NITs while 23% would consider 1 NIT, and 17% would confirm with liver biopsy. TE was used by >75% to monitor, and 66% would monitor (intermediate or high risk) annually. Finally, 65% follow professional guideline recommendations regarding NITs.

CONCLUSIONS

In clinical practice, there is variability in NIT use and their thresholds. Additionally, there is suboptimal adherence to professional societies' guidelines.

A new generation of non-invasive tests of liver fibrosis with improved accuracy in MASLD

BACKGROUND & AIMS

The accuracy of non-invasive tests (NITs) should be ≥80% (EASL recommendation). We aimed to compare the accuracies of the recommended NITs for advanced fibrosis in metabolic dysfunction-associated steatotic liver disease (MASLD) and to develop NITs with improved accuracy.

METHODS

A total of 1,051 patients with MASLD were allocated to derivation (n = 637) and validation (n = 414) sets. The main outcome (Kleiner F3+F4) was primarily evaluated by accuracy. Recommended NITs included: FIB-4, Fibrotest, FibroMeter, liver stiffness measurement (LSM by Fibroscan), Elasto-FibroMeter (FibroMeter-LSM combination), and ELF (enhanced liver fibrosis) in 396 patients. We used machine learning-optimized multitargeting to develop new NITs: FIB-9 (including nine common biomarkers), FIB-11 (adding two specialized blood markers) and FIB-12 (adding LSM).

RESULTS

In the whole population, the accuracies of recommended NITs were insufficient: Fibrotest, 68.0%; FIB-4, 71.2%; FibroMeter, 75.1%; LSM, 75.9%; Elasto-FibroMeter, 78.6%. Therefore, new NITs (FIB-9, FIB-11, FIB-12) were developed in the derivation set. In the validation set, AUROCs were: FIB-4, 0.757; Fibrotest, 0.766; FibroMeter, 0.850; LSM, 0.852; FIB-9, 0.863; FIB-11, 0.880; Elasto-FibroMeter, 0.894; FIB-12, 0.912 (p <0.001). The FIB-12 AUROC was superior to the ELF AUROC (0.906 vs. 0.865, p = 0.039). Accuracies were: FIB-4, 68.8%; Fibrotest, 68.6%; LSM, 75.4%; FibroMeter, 76.3%; FIB-9, 78.7%; Elasto-FibroMeter, 79.7%; FIB-11, 80.2%; FIB-12, 83.3% (p <0.001 between all NITs). Scores were segmented by ≥90% sensitivity and specificity cut-offs or NIT match, which individualized subgroups with NIT accuracies ≥80%, e.g. for FIB-9: 85.8% in 68.1% of patients using two cut-offs and 83.2% in 71.7% of patients where FIB-9 agreed with FIB-4.

CONCLUSIONS

Recommended NITs had accuracies <80% for advanced fibrosis in MASLD. Several NIT segmentations individualized subgroups with accuracies ≥80%. New NITs further improved accuracy. The simple FIB-9 (available via a free calculator) provided accuracy equaling or surpassing recommended NITs. FIB-12 outperformed other NITs.

IMPACT AND IMPLICATIONS

Currently recommended non-invasive tests (NITs) have insufficient accuracy (<80%) for the diagnosis of advanced fibrosis in metabolic dysfunction-associated steatotic liver disease (MASLD). Therefore, we developed three new NITs with new statistical techniques. Thus, FIB-9 (available via a free calculator), including nine common blood markers, equaled the performance of patented NITs. FIB-11, adding two specialized blood markers, and FIB-12, adding liver stiffness, had accuracy >80%. FIB-12 outperformed all other NITs. FIB-9 is suitable for screening and FIB-11 or FIB-12 for diagnosis.

A metabolome-derived score predicts metabolic dysfunction-associated steatohepatitis and mortality from liver disease

BACKGROUND & AIMS

Metabolic dysfunction-associated steatohepatitis (MASH) is associated with a >10-fold increase in liver-related mortality. However, biomarkers predicting both MASH and mortality in patients with metabolic dysfunction-associated steatotic liver disease (MASLD) are missing. We developed a metabolome-derived prediction score for MASH and examined whether it predicts mortality in Chinese and European cohorts.

METHODS

The MASH prediction score was developed using a multi-step machine learning strategy, based on 44 clinical parameters and 250 serum metabolites measured by proton nuclear magnetic resonance in 311 Chinese adults undergoing a liver biopsy. External validation was conducted in a Finnish liver biopsy cohort (n = 305). We investigated associations of the score with all-cause and cause-specific mortality in the population-based Shanghai Changfeng study (n = 5,893) and the UK biobank (n = 111,673).

RESULTS

A total of 24 clinical parameters and 194 serum metabolites were significantly associated with MASH in the Chinese liver biopsy cohort. The final MASH score included BMI, aspartate aminotransferase, tyrosine, and the phospholipid-to-total lipid ratio in VLDL. The score identified patients with MASH with AUROCs of 0.87 (95% CI 0.83-0.91) and 0.81 (95% CI 0.75-0.88) in the Chinese and Finnish cohorts, with high negative predictive values. Participants with a high or intermediate risk of MASH based on the score had a markedly higher risk of MASLD-related mortality than those with a low risk in Chinese (hazard ratio 23.19; 95% CI 4.80-111.97) and European (hazard ratio 20.15; 95% CI 10.95-37.11) individuals after 7.2 and 12.6 years of follow-up, respectively. The MASH prediction score was superior to the Fibrosis-4 index and the NAFLD fibrosis score in predicting MASLD-related mortality.

CONCLUSION

The metabolome-derived MASH prediction score accurately predicts risk of MASH and MASLD-related mortality in both Chinese and European individuals.

IMPACT AND IMPLICATIONS

Metabolic dysfunction-associated steatohepatitis (MASH) is associated with more than a 10-fold increase in liver-related death. However, biomarkers predicting not only MASH, but also death due to liver disease, are missing. We established a MASH prediction score based on 44 clinical parameters and 250 serum metabolites using a machine learning strategy. This metabolome-derived MASH prediction score could accurately identify patients with MASH among both Chinese and Finnish individuals, and it was superior to the Fibrosis-4 index and the NAFLD fibrosis score in predicting MASLD-related death in the general population. Thus, the new MASH prediction score is a useful tool for identifying individuals with a markedly increased risk of serious liver-related outcomes among at-risk and general populations.

Diagnosis and Monitoring of Metabolic Dysfunction Associated with Fatty Liver Disease in Primary Care Patients with Risk Factors-EsteatoGal Study

Objective: The objective of this study was to calculate the epidemiological impact of metabolic dysfunction associated with fatty liver disease (MAFLD) and hepatic fibrosis in primary care (PC). Secondarily, we assessed the correlation between serological markers (FIB-4, ELF test), abdominal ultrasound, and transient elastography in the early detection of MAFLD. Methods: An observational prospective study was designed to determine the prevalence of MAFLD and to assess the correlation between complementary tests. Patients were recruited from five health centres. Eligible participants were adults aged between 18 and 70 years with at least one metabolic risk factor, including being overweight (BMI 25-29.9 kg/m2) or obese (BMI > 30 kg/m2), or diagnosed with type 2 diabetes mellitus (T2DM), dyslipidemia, or metabolic syndrome. The prevalence of MAFLD was calculated. Correlations between diagnostic tests were evaluated using Pearson's correlation coefficient. Results: A total of 98 patients was included. Using CAP (controlled attenuation parameter) measurements, the prevalence of MAFLD was found to be 67.7%, and the prevalence of hepatic fibrosis was 6.5%. The correlation between conventional ultrasound and CAP from FibroScan® for the diagnosis of MAFLD was low and not statistically significant (0.160 [95% CI: -0.100; 0.400], p = 0.226). In contrast, the diagnosis of hepatic fibrosis using FibroScan® in PC showed a high correlation with diagnoses performed in gastroenterology department (0.942 [95% CI: 0.844; 0.979], p < 0.001). The correlation with biochemical markers was low and not statistically significant for both FIB-4 (0.125 [95% CI: -0.129; 0.363], p = 0.334) and the ELF test (0.159 [95% CI: -0.111; 0.407], p = 0.246). Conclusions: Two out of three patients with metabolic risk factors were diagnosed with MAFLD, while hepatic fibrosis diagnoses were uncommon. These results reinforce the validity of using FibroScan® in PC.

Development and Validation of a Machine Learning-based Model for Prediction of Liver Fibrosis and MASH

BACKGROUND AND AIM

The development of accurate noninvasive tests to identify individuals with metabolic dysfunction-associated steatohepatitis (MASH) and liver fibrosis is of great clinical importance. In this study, we aimed to develop 2 noninvasive diagnostic models on the basis of routine clinical and laboratory data, using machine learning, to identify patients with MASH and significant fibrosis (fibrosis stages 2 to 4), respectively.

METHODS

This analysis included the training (n=456) and the validation (n=105) sets of patients who underwent liver biopsy and laboratory testing for liver disease at 2 hospitals in China. Logistic regression, random forest, support vector machine, and the XGBoost algorithm were used to construct models, respectively. The best diagnostic models for MASH and significant fibrosis were compared with 7 existing noninvasive scoring systems including AAR, AST to platelet ratio index (APRI), BARD score, fibrosis-4 (FIB-4), fibrotic non-alcoholic steatohepatitis (NASH) index (FNI), homeostatic model assessment of insulin resistance (HOMA-IR), and non-alcoholic fatty liver disease fibrosis score (NFS). Performance was estimated by the area under the receiver operating characteristic curve (AUROC).

RESULTS

The final noninvasive diagnostic model integrated 19 indicators derived from routine clinical and laboratory tests. The XGBoost models exhibited superior performance in MASH and significant fibrosis with an improved AUROC value (MASH, 0.670, 95% CI 0.530-0.811; significant fibrosis, 0.713, 95% CI 0.611-0.815) compared with other noninvasive scoring systems in the validation set.

CONCLUSIONS

Utilizing machine learning can assist in diagnosing MASH and significant fibrosis based on clinical epidemiological information with good diagnostic performance.

Letter to the Editor in response to the article "Effect of luseogliflozin on liver fibrosis differs depending on alcohol consumption in patients with type 2 diabetes"

Letter to the Editor in response to the article “Effect of luseogliflozin on liver fibrosis differs depending on alcohol consumption in patients with type 2 diabetes” highlighted the favorable changes in FIB‐4, HbAlc, weight loss, and serum albumin concentrations in drinkers and non‐drinkers with type‐2 diabetes and liver fibrosis. This retrospective study not only covered the facts respective to a topic but the depth and diversity of the study beamed so many perspectives which enhanced our concepts. Still, there is always a margin of uncertainties and addressing those limitations will enhance the validity of further studies.

Association between glucose time-in-range and the severity of metabolic dysfunction-associated steatotic liver disease in Chinese adults with type 2 diabetes mellitus

BACKGROUND

This study investigated the correlation between glucose time-in-range (TIR) and hepatic steatosis severity or liver fibrosis risk in Chinese adults with type 2 diabetes mellitus (T2DM) comorbid with metabolic dysfunction-associated steatotic liver disease (MASLD).

METHODS

Participants with T2DM were evaluated for hepatic steatosis and fibrosis using vibration-controlled transient elastography. TIR was calculated based on data from a retrospective continuous glucose monitoring system.

RESULTS

A total of 184 T2DM patients with MASLD were enrolled. The controlled attenuation parameter (CAP) and liver stiffness measurement (LSM) decreased with increasing TIR (p < 0.05). Spearman correlation showed negative correlations between CAP, LSM, and TIR (r = -0.824 and - 0.842, p < 0.05) and positive correlations with basal insulin resistance (HOMA-IR) (r = 0.205 and 0.208, p < 0.01). Multiple linear regression revealed TIR and HOMA-IR independently correlated with CAP (std. regression coefficients = -0.695 and 0.103, p < 0.05) and LSM (std. regression coefficients = -0.735 and 0.083, p < 0.05), wit0.34 h TIR having a stronger impact. Binary logistic regression showed TIR Groups 3 (70% ≥ TIR < 85%) and 4 (TIR ≥ 85%) were protective for MASLD (OR = 0.26 and 0.11, 95% CI 0.10-0.66 and 0.04-0.29, P = 0.005 and < 0.001) and liver fibrosis (OR = 0.29 and 0.13, 95% CI 0.12-0.74 and 0.05-0.36, P = 0.010 and < 0.001) compared to TIR Group 1 (lowest quartile).

CONCLUSION

In T2DM patients with coexisting MASLD, a significant and independent association existed between TIR and the severity of hepatic steatosis.

CLINICAL TRIAL NUMBER

Not applicable.

Pharmaco-Economic Assessment of Screening Strategies for High-Risk MASLD in Primary Care

BACKGROUND AND AIMS

Several scientific associations recommend a sequential combination of non-invasive tests (NITs) to identify high-risk MASLD patients but their cost-effectiveness is unknown.

METHODS

A cost-utility model was developed to assess the incremental cost-effectiveness ratio (ICER) of recommended screening strategies for patients with clinically suspected MASLD, specifically those with type 2 diabetes (T2D) and obesity with multiple cardiometabolic risk factors which will be initiated in primary care. Six screening strategies were assessed, using either vibration-controlled transient elastography (VCTE) or the enhanced liver fibrosis (ELF) test as a second-line test following an initial Fibrosis-4 (FIB-4) assessment as the first line NIT. The model included treatment effects of resmetirom for metabolic dysfunction-associated steatohepatitis (MASH) patients with F2 or F3 fibrosis.

RESULTS

All screening strategies for high-risk MASLD in US incurred additional costs compared to no screening, ranging from $13 587 to $14 730 per patient with T2D and $14 274 to $15 661 per patient with obesity. However, screening reduced long-term costs, ranging from $22 150 to $22 279 per patient with T2D and $13 704 to $13 705 per patient with obesity, compared to $24 221 and $14 956 for no screening, respectively. ICERs ranged from $26 913 to $27 884 per QALY for T2D patients and $23 265 to $24  992 per QALY for patients with obesity. While ICERs were influenced by VCTE availability, they remained cost-effective when using ELF as the second-line test. Our findings remain robust across a range of key parameters.

CONCLUSIONS

Screening for high-risk MASLD is cost-effective according to recent guidelines. Implementing these screening strategies in primary care should be considered.

Evidence-based criteria for identifying at-risk individuals requiring liver disease screening

BACKGROUND

Liver fibrosis screening is recommended in at-risk groups, but a clear definition of "at risk" for entry criteria is lacking. We analyzed different combinations of established risk factors to define specific screening entry criteria with a prespecified sensitivity requirement.

METHODS

Data regarding individuals aged 40-70 years from Finnish health-examination surveys (FINRISK 2002-2012 and Health 2000, n=15,057) and the UK Biobank (n=454,990) were linked with healthcare registries for liver cirrhosis-related events (LREs; liver-related hospitalizations, cancer, or death). The predictive performance of 1919 combinations of risk factors, including alcohol consumption, metabolic disturbances, abnormal liver function tests, and Chronic Liver Disease risk score, was assessed for 10-year LRE risk requiring a minimum 90% sensitivity. Validations were performed using liver stiffness measurement (LSM) >12 kPa in the NHANES 2017-2020 sample (n=3367).

RESULTS

Optimal entry criteria for predicting 10-year LRE risk with >90% sensitivity included any one of: hazardous alcohol use, severe obesity, metabolic syndrome, an AST-to-ALT ratio >0.8 with elevated ALT, and an intermediate-to-high Chronic Liver Disease risk score. The sensitivity and specificity for this strategy were 91% and 51% for LREs, respectively, in the Finnish cohort, and 91% and 41% for LSM >12 kPa in the US sample. In the US sample, applying these entry criteria followed by fibrosis-4 ≥1.3 for predicting LSM >12 kPa reduced the sensitivity to 45% (specificity: 85%), which was attributed to the suboptimal sensitivity of fibrosis-4.

CONCLUSIONS

This study identifies an inexpensive risk factor-based strategy with >90% sensitivity for predicting LRE and LSM >12 kPa, which is practical and scalable for targeted liver fibrosis screening to improve population outcomes. However, a more sensitive first-line noninvasive fibrosis test is needed.

Training and Performance of an Electrocardiogram-Enabled Machine Learning Model for Detection of Advanced Chronic Liver Disease

INTRODUCTION

Building on prior results, we hypothesized that an electrocardiogram (ECG)-enabled machine learning (ML) model could be used to detect advanced chronic liver disease (CLD).

METHODS

A cohort with CLD and 12-lead ECGs was matched with controls from electronic health records. A ML model was trained as a binary classifier.

RESULTS

There are 12,930 patients with CLD and 64,577 controls in the cohort. The model's discriminative ability to classify CLD showed an area under the receiver-operating characteristic curve 0.858 (95% confidence interval: 0.850-0.866), and at the chosen threshold, CLD ECGs had 12 times higher odds of being classified as CLD (diagnostic odds ratio 12.33, 95% confidence interval: 11.16-13.63).

DISCUSSION

An ECG-enabled ML model affords great promise in identifying advanced CLD in low resource areas.

Diagnosis and Management of Early Stages of ALD

Early forms of alcohol-associated liver disease (ALD) include different stages in the progression of compensated liver disease ranging from steatosis to steatohepatitis and fibrosis. ALD has been classically diagnosed at advanced stages more frequently than other liver diseases. This fact probably contributed to the scarcity of studies on early forms of ALD. Recent studies have investigated the prevalence of early ALD in the general population and have described the natural history of alcohol-induced steatosis and fibrosis, which have been linked to worse prognosis compared with early stages of other chronic liver diseases. In addition, studies on screening and early diagnosis of ALD in at-risk populations have shown that these strategies allow early detection and intervention. Of note, up to 28% of the United States population has concurrent alcohol use and metabolic syndrome, and estimated prevalence of advanced fibrosis among heavy drinkers with metabolic syndrome has increased from 3% in the 1990s to more than 10% in the 2010s. Therefore, new challenges and treatment opportunities will emerge for patients with ALD. In this review, we provide an overview of the state of the art in early ALD, focusing on natural history, diagnosis, and management, and provide insights into future perspectives.

The role of the advanced lung cancer inflammation index (ALI) in the risk of liver fibrosis and mortality among US adult MAFLD patients: a cross-sectional study of NHANES 1999-2018

BACKGROUND

Metabolic dysfunction-associated fatty liver disease (MAFLD) is a prevalent chronic liver disease globally, with inflammation and nutrition playing key roles in its progression. The Advanced Lung Cancer Inflammation Index (ALI) is a novel biomarker reflecting nutritional and inflammatory status. This study aims to explore the association between ALI and the risk of liver fibrosis and prognosis in MAFLD patients.

METHODS

This cross-sectional study analyzed NHANES data from the 1999-2018 on adult participants in the US. Weighted logistic regression assessed the association between ALI and liver fibrosis risk. Mortality outcomes, including all-cause, cardiovascular disease (CVD), and cancer mortality, analyzed using weighted Kaplan-Meier and Cox proportional hazards models. Restricted cubic splines (RCS) and threshold effect analyses were uesd to explore non-linear relationships. Receiver operating characteristic (ROC) curve evaluated the prognostic value of ALI, and stratified analyses examined subgroup differences.

RESULTS

A total of 6,858 MAFLD patients (mean age 51.38 ± 17.22 years, 54% male) were included. A non-linear relationship was found between ALI and liver fibrosis risk, with a threshold at 5.68, beyond which the risk increased significantly (OR = 2.35, 95% CI: 1.89-2.95). Stronger associations were observed in subgroups with central obesity and prediabetes (P for interaction < 0.05). ALI was inversely associated with all-cause mortality (HR = 0.64, 95% CI: 0.56-0.72) and CVD mortality (HR = 0.57, 95% CI: 0.46-0.65), but not cancer mortality. RCS analysis showed an L-shaped non-linear relationship with all-cause mortality (threshold at 5.36) and a linear relationship with CVD mortality. Low HDL cholesterol and excessive alcohol consumption influenced the association between ALI and all-cause mortality (P for interaction < 0.05). ALI demonstrated the highest predictive accuracy for CVD mortality.

CONCLUSION

ALI is associated with an increased risk of liver fibrosis and reduced all-cause and CVD mortality, highlighting its potential value in assessing MAFLD prognosis, particularly CVD-related mortality.

Prediction of major liver-related events in the population using prognostic models

Liver disease poses a significant global health burden, with steatotic liver disease related to metabolic dysfunction and/or alcohol use being the most prevalent type. Current risk stratification strategies emphasize detecting advanced fibrosis as a surrogate marker for liver-related events (LREs), such as hospitalization, liver cancer, or death. However, fibrosis alone does not adequately predict imminent outcomes, particularly in fast-progressing individuals without advanced fibrosis at evaluation. This underscores the need for models designed specifically to predict LREs, enabling timely interventions. The Chronic Liver Disease (CLivD) risk score, the dynamic aspartate aminotransferase-to-alanine aminotransferase ratio (dAAR), and the Cirrhosis Outcome Risk Estimator (CORE) were explicitly developed to predict LRE risk rather than detect fibrosis. Derived from general population cohorts, these models incorporate either standard liver enzymes (dAAR and CORE) or risk factors (CLivD), enabling broad application in primary care and population-based settings. They directly estimate the risk of future LREs, improving on traditional fibrosis-focused approaches. Conversely, widely used models like the Fibrosis-4 index and newer ones, such as the LiverRisk and LiverPRO scores, were initially developed to detect significant/advanced fibrosis or liver stiffness. While not designed for LRE prediction, they have later been analyzed for this purpose. Integrating fibrosis screening with LRE-focused models like CLivD, dAAR, and CORE can help healthcare systems adopt proactive, preventive care. This approach emphasizes identifying individuals at imminent risk of severe outcomes, potentially ensuring better resource allocation and personalized interventions.

Metabolic dysfunction-associated steatotic liver disease in adults

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the umbrella term that comprises metabolic dysfunction-associated steatotic liver, or isolated hepatic steatosis, through to metabolic dysfunction-associated steatohepatitis, the progressive necroinflammatory disease form that can progress to fibrosis, cirrhosis and hepatocellular carcinoma. MASLD is estimated to affect more than one-third of adults worldwide. MASLD is closely associated with insulin resistance, obesity, gut microbial dysbiosis and genetic risk factors. The obesity epidemic and the growing prevalence of type 2 diabetes mellitus greatly contribute to the increasing burden of MASLD. The treatment and prevention of major metabolic comorbidities such as type 2 diabetes mellitus and obesity will probably slow the growth of MASLD. In 2023, the field decided on a new nomenclature and agreed on a set of research and action priorities, and in 2024, the US FDA approved the first drug, resmetirom, for the treatment of non-cirrhotic metabolic dysfunction-associated steatohepatitis with moderate to advanced fibrosis. Reliable, validated biomarkers that can replace histology for patient selection and primary end points in MASH trials will greatly accelerate the drug development process. Additionally, noninvasive tests that can reliably determine treatment response or predict response to therapy are warranted. Sustained efforts are required to combat the burden of MASLD by tackling metabolic risk factors, improving risk stratification and linkage to care, and increasing access to therapeutic agents and non-pharmaceutical interventions.

Waist circumference as a predictor for severity of liver fibrosis in non-alcoholic fatty liver disease patients

Introduction

Non-alcoholic fatty liver disease (NAFLD) may in some cases progress to increasing grades of liver fibrosis and eventually cirrhosis. NAFLD patients often succumb to cardiovascular causes. Previous studies have linked visceral fat, a known cardiovascular risk factor, to NAFLD. Visceral fat is best quantified by measuring the waist circumference (WC). This study is aimed to determine the association of waist circumference with severity of liver fibrosis in NAFLD patients.

Methods

In this cross-sectional study we recruited 82 NAFLD patients diagnosed via ultrasonography. They underwent anthropometric examination followed by transient elastography with Fibro Scan to assess of liver stiffness measure (LSM). A cutoff LSM value of 7kPa was used to indicate significant fibrosis. Among the participants, 40 patients had an LSM value of <7 kPa (insignificant/no fibrosis), while 42 were found to have >7 kPa (significant fibrosis). Biochemical parameters of Lipid profile and Liver enzymes were also analyzed.

Statistical Analysis Used

SPSS software with Student t-test, Chi-square t-test, ANOVA, and Spearman correlation with 95% CI is used. P <0.05 is considered significant.

Results

Patients with significant fibrosis had higher mean weight (P < 0.001), BMI (P = 0.009), WC (P = 0.002), and waist-hip ratio (WHR, P = 0.032) compared to those with no fibrosis. However, hip circumference (HC) was not significantly associated between the two groups. In correlation studies, BMI (P = 0.001), weight (P < 0.001), WC (P = 0.001), and HC (P = 0.008) positively correlated with severity of liver fibrosis in NAFLD patients. However, no significant correlation was found with WHR.

Conclusion

Weight, BMI, and visceral fat indicators like WC and WHR are strongly associated with liver fibrosis severity in NAFLD patients. Notably, weight, BMI, WC, and HC positively correlate with fibrosis severity, while WHR does not. Early diagnosis of fatty liver is crucial to prevent progression to life-threatening conditions like NASH or NASH cirrhosis. Waist circumference could serve as a practical screening tool in primary health care centres for identifying NAFLD patients at risk of fibrosis progression.

The fibrosis investigating navigator in diabetes (FIND): A tool to predict liver fibrosis risk in subjects with diabetes

BACKGROUND

Type 2 diabetes increases the risk of cirrhosis and liver cancer. Noninvasive and early assessment of liver fibrosis is essential. We aimed to develop a score to aid in the initial assessment of liver fibrosis in the diabetic population.

METHODS

A fibrosis investigating navigator in diabetes (FIND) score was developed and validated in the NHANES dataset (2017-2020). Fibrosis was defined as a liver stiffness measurement (LSM) ≥8.0 kPa. The diagnostic accuracies of FIB-4, NFS, LiverRisk, steatosis-associated fibrosis estimator (SAFE) and metabolic dysfunction-associated fibrosis (MAF-5) were compared. FIND was also externally validated in various liver diseases via biopsy as a reference in an Asian centre between 2016 and 2020. Finally, we examined the prognostic implications of the FIND index utilizing data from the UK Biobank cohort (2006-2010).

RESULTS

The FIND score model yielded an AUROC of 0.781 for the prediction of an LSM ≥8 kPa in the validation set, which was consistently greater than that of other available models (all p < 0.05). In the whole NHANES dataset, the 85% sensitivity cut-off of 0.16 corresponded to a NPV of 91.9%, whereas the 85% specificity cut-off of 0.31 corresponded to a PPV of 50.6%. FIND displayed overall accuracies similar to those of the other models in staging fibrosis stages, with biopsy used as a reference. In the UK Biobank cohort, FIND >0.31 was associated with an increased risk of all-cause and liver-related mortality in the diabetic population in adjusted models (HR, 1.75; 95% CI, 1.62-1.89; HR, 23.59; 95% CI, 13.67-40.69).

CONCLUSIONS

In diabetes patients, the novel FIND score performs well in identifying subjects at risk of liver fibrosis and predicting all-cause and liver-related mortality.

The use of ELF in predicting liver fibrosis prevalence and fibrosis progression in the general population

BACKGROUND AND AIMS

The enhanced liver fibrosis (ELF) test has good discrimination performance in detecting advanced liver fibrosis. The chronic liver disease (CLivD) risk score based on clinical data accurately predicts risk for future severe liver disease. Considering the ELF test as a surrogate marker for liver fibrosis, we analyzed predictors of elevated ELF (eELF) and its change.

METHODS

The study cohort consisted of Finnish general population-based health surveys Health2000 and a follow-up study 10 years later Health2011 with 6084 and 2937 individuals, respectively with phenotype and ELF data. eELF was defined as ELF ≥ 9.8, and clinically relevant fibrosis progression as an ELF change ≥0.6. CLivD risk score was calculated at baseline. Analyses were age-adjusted.

RESULTS

Obesity measures and diabetes predicted eELF at baseline. Only waist-hip ratio (WHR) could predict clinically relevant fibrosis progression over the follow-up consistently among men and women (OR 1.35 and 1.41, respectively). High-risk alcohol use was a significant risk factor for eELF only among men (OR 1.72, p = 0.049), and it did not predict fibrosis progression in either sex. Although elevated transaminases were associated with eELF, in most individuals with eELF they were within reference limits. Increased CLivD scores correlated with baseline and the change of ELF values over the 10-year follow-up independent of baseline ELF (p < 0.001).

CONCLUSIONS

Liver fibrosis progression is difficult to predict based on single risk factors or liver enzymes. ELF had limited value to predict fibrosis progression. The CLivD score, based on multiple risk factors, predicted both occurrence of baseline eELF and its progression over a 10-year follow-up.

Noninvasive assessment of hepatic decompensation

Noninvasive tests (NITs) are used in all aspects of liver disease management. Their most prominent break-through since the millennium has been in advancing early detection of liver fibrosis, but their use is not limited to this. In contrast to the symptom-driven assessment of decompensation in patients with cirrhosis, NITs provide not only opportunities for earlier diagnoses but also accurate prognostication, targeted treatment decisions, and a means of monitoring disease. NITs can inform disease management and decision-making based on validated cutoffs and standardized interpretations as a valuable supplement to clinical acumen. The Baveno VI and VII consensus meetings resulted in tangible improvements to pathways of care for patients with compensated and decompensated advanced chronic liver disease, including the combination of platelet count and transient elastography to diagnose clinically significant portal hypertension. Furthermore, circulating NITs will play increasingly important roles in assessing the response to interventions against ascites, variceal bleeding, HE, acute kidney injury, and infections. However, due to NITs' wide availability, there is a risk of inaccurate use, leading to a waste of resources and flawed decisions. In this review, we describe the uses and pitfalls of NITs for hepatic decompensation, from risk stratification in primary care to treatment decisions in outpatient clinics, as well as for the in-hospital management of patients with acute-on-chronic liver failure. We summarize which NITs to use when, for what indications, and how to maximize the potential of NITs for improved patient management.

Serum ECM1 is a promising biomarker for staging and monitoring fibrosis in patients with chronic hepatitis B

It is critical to assess the extent and progression of liver fibrosis for patients to receive suitable treatments, but its diagnostic methods remain unmet. Extracellular matrix protein 1 (ECM1) has previously been reported to be a key factor in the induction and progression of liver fibrosis. However, little is known about the use of ECM1 as a biomarker to evaluate fibrosis. In a CCl4-induced mouse model of liver fibrosis, the present study demonstrated that ECM1 decreased with gradually increasing fibrosis. Using biopsy as a reference, the serum ECM1 levels decreased with increasing fibrosis stage in 247 patients with liver fibrosis, but there were no significant changes between fibrosis stage 2 and stage 0-1. To improve the performance of ECM1, age, platelet count, and ECM1 concentration were combined to calculate an EPA (ECM1-platelet-age) score (ranging from 0 to 10). The areas under the receiver operating characteristic curve of the EPA scores for the detection of F⩾2, F⩾3, and F4 were 0.6801, 0.7377, and 0.8083, respectively, which showed a comparable or significantly greater diagnostic performance for assessing fibrosis than that of the AST/ALT ratio, APRI score, or FIB-4 score. In HBV patients following antiviral treatment, the dynamics of the EPA score depended on the status of liver fibrosis development. The accuracy of the EPA score in predicting fibrosis regression and progression was 66.00% and 71.43%, respectively, while that of the LSM, another useful method for monitoring hepatic fibrosis changes during treatment, was only 52.00% and 7.14%, respectively. Compared with healthy controls, there were lower levels of serum ECM1 in HBV patients and individuals with HCV infection, MAFLD, ALD, PBC, and DILI. These findings suggested that individuals with reduced ECM1 levels may have a risk of developing liver injury, and further examinations or medical care are needed. In conclusion, the ECM1-containing EPA score is a valuable noninvasive test for staging fibrosis and predicting the progression of liver fibrosis. Additionally, ECM1 alone is an indicator for distinguishing patients with liver injury from healthy controls.

Moving diagnosis of liver fibrosis into the community

Chronic liver disease (CLD) is a leading cause of death worldwide, with alcohol consumption and metabolic risk factors accounting for the majority of cases of CLD in many developed countries. Currently, specific strategies for the early diagnosis of CLD are lacking and consequently most cases are diagnosed at an advanced stage, which is associated with negative consequences for disease management and prognosis. Screening for CLD is based on either detection of chronic viral hepatitis B and C, or detection of liver fibrosis in patients with steatotic liver disease related to alcohol or metabolic dysfunction. Non-invasive tools, including serological and imaging-based tests, can be used to detect liver fibrosis. Clinical practice guidelines recommend screening for liver fibrosis using algorithms that combine different non-invasive tests, with widely available but low accuracy tests, such as FIB-4, recommended as a first screening step in the primary care setting, and other tests with lower availability but higher accuracy, such as transient elastography or the enhanced liver fibrosis test, recommended as a second step. There are different pathways for early detection of patients with CLD from primary to specialised care, with primary care providers being key for early detection, management and referral of patients. In addition, interventions targeting metabolic risk factors and alcohol consumption should be carried out in collaboration between specialists and primary care. In this review, we describe liver fibrosis from the community perspective, highlighting gaps in knowledge on how to define the optimal combination of tests, target population, the ideal pathway of care for CLD, and how to increase implementation of programmes for early diagnosis of liver diseases in clinical practice.

Estimating the prevalence of adults at risk for advanced hepatic fibrosis using FIB-4 in a Swiss tertiary care hospital

BACKGROUND & AIMS

Chronic liver diseases pose a serious public health issue. Identifying patients at risk for advanced liver fibrosis is crucial for early intervention. The Fibrosis-4 score (FIB-4), a simple non-invasive test, classifies patients into three risk groups for advanced fibrosis. This study aimed to estimate the prevalence of patients at risk for advanced hepatic fibrosis at a Swiss tertiary care hospital by calculating the FIB-4 score in routine blood analysis.

METHODS

A retrospective study was conducted using data from 36,360 patients who visited outpatient clinics at eight main clinics of the University Hospital Bern in Switzerland. The data collection period ran from January 1st to December 31st, 2022. Patients attending the hepatology outpatient clinic were excluded. We then calculated the overall and clinic-specific prevalence of patients falling into the high risk category for advanced fibrosis according to FIB-4.

RESULTS

Among the 36,360 patients, 26,245 (72.2%) had a low risk of advanced fibrosis (FIB-4 <1.3), whereas 3913 (10.8%) and 2597 (7.1%) patients were flagged to have a high risk of advanced fibrosis (FIB-4 >2.67 and FIB-4 >3.25 respectively). Geriatrics and Cardiology had the highest proportions of patients at risk for advanced fibrosis over all clinics.

CONCLUSIONS

This study demonstrates a high prevalence of high FIB-4 score in a Swiss tertiary care hospital. The implementation of the automatically generated FIB-4 score in daily practice, not only in primary care, but also within tertiary care hospitals, could be crucial for early identification of outpatients at high risk of advanced liver fibrosis requiring further hepatological investigations.

Golgi protein 73: charting new territories in diagnosing significant fibrosis in MASLD: a prospective cross-sectional study

Objectives

To explore the correlation between serum Golgi protein 73 (GP73) levels and the degree of fibrosis in Metabolic dysfunction associated steatotic liver disease (MASLD); to establish a non-invasive diagnostic algorithm based on serum GP73 and liver elasticity.

Methods

This is a prospective cross-sectional study, including 228 patients diagnosed with MASLD from May 2018 to January 2024 at two tertiary hospitals. Clinical data and hepatic pathological features and the correlation between serum GP73 and liver fibrosis were assessed. A new algorithm was conducted after logistic regression. Receiver Operating Characteristic (ROC) curve was used to compare its diagnostic performance with traditional models.

Results

Significant fibrosis was diagnosed in 37.2% (85/228) patients. Serum GP73 levels were markedly higher in patients with significant fibrosis than in those without (128 ng/mL v.s 46 ng/mL, p< 0.001). Serum GP73 levels independently predicted significant liver fibrosis (adjusted odds ratio, aOR 1.028, p< 0.001). A new algorithm based on GP73 was developed with a higher area under ROC (AUC) of 0.840 than that of Fibrosis index-4 (p< 0.001).

Conclusions

Serum GP73 is an independent risk factor for significant liver fibrosis in MASLD, and the GFA (GP73-Fibroscan-Age) model has good diagnostic efficacy for significant liver fibrosis.

Prevalence of Low FIB-4 in MASLD-Related Hepatocellular Carcinoma: A Multicentre Study

BACKGROUND

Major society guidelines recommend the fibrosis-4 index (FIB-4) as the initial step to risk stratifying people with metabolic dysfunction-associated steatotic liver disease (MASLD). We aimed to evaluate the proportion of people with MASLD-related hepatocellular carcinoma (HCC) and a low FIB-4.

METHODS

This cohort study included 613 consecutive adults (33% female) diagnosed with MASLD-related HCC from January 2008 to August 2023 at seven international centres in Australia, India, Japan, South Korea, Singapore and the United States. The primary objective was to determine the proportion of participants with a low FIB-4, defined as FIB-4 < 1.3, or < 2 if age > 65 years, in people without cirrhosis.

RESULTS

The mean (±SD) age and body mass index were 71 (±11) years and 27 (±7) kg/m2, respectively. Overall, 235 participants (38%) did not have known cirrhosis. The median FIB-4 was 3.90 (IQR 2.42-6.42). A total of 78 participants (13%) had a low FIB-4. Among participants without known cirrhosis (n = 235), 62 participants (26%) had a low FIB-4. Participants with a low FIB-4 had larger median total tumour diameter (p < 0.001) and lower median serum alpha-fetoprotein (p = 0.005), compared to participants without a low FIB-4. Cirrhosis was associated with lower odds of low FIB-4, but not other factors such as male sex, type 2 diabetes, or obesity.

CONCLUSION

More than a quarter of those with MASLD-related HCC without cirrhosis have a low FIB-4. The proposed clinical care pathways may not identify these people for further evaluation.

Development, validation, and prognostic evaluation of LiverPRO for the prediction of significant liver fibrosis in primary care: a prospective cohort study

BACKGROUND

Clinically significant liver fibrosis is associated with future adverse events in patients with steatotic liver disease. We designed a software tool for detection of clinically significant liver fibrosis in primary care.

METHODS

In this prospective cohort study, we developed and validated LiverPRO using six independent cohorts from Denmark, Germany, and England that included patients from primary and secondary care with steatotic liver disease related to alcohol or metabolic dysfunction. We used clinically significant fibrosis (histology stage ≥F2) and advanced fibrosis (≥F3) as outcomes for variable selection in the development cohort and built the model with fractional polynomial regression. In all cohorts, we independently validated the tool for prediction of elevated liver stiffness by transient elastography (≥8 kPa and ≥12 kPa) and for the 2-year and 5-year risk of liver-related events. Diagnostic performance was assessed using the area under the receiver operating curve (AUC), with clinical performance evaluated through sensitivity, specificity, and Harrell's C-statistic for prognostic purposes.

FINDINGS

In the development cohort (n=462), we derived 466 multivariable models consisting of age in combination with three to nine variables from a list of nine blood tests (aspartate aminotransferase, alkaline phosphatase, gamma-glutamyl transferase, international normalised ratio, albumin, sodium, bilirubin, platelet count, and cholesterol). In the development cohort, LiverPRO diagnosed clinically significant fibrosis with good accuracy (transient elastography ≥8 kPa area under the receiver operating characteristic curve [AUC] 0·86 [95% CI 0·83-0·90]). In the DECIDE validation cohort (n=6468), LiverPRO detected participants with a transient elastography of 8 kPa or higher with good accuracy (AUC 0·80 [95% CI 0·78-0·82]), comparable to enhanced liver fibrosis testing (0·78 [0·75-0·80]) and the LiverRisk score (0·81 [0·79-0·84]), but superior to the Fibrosis-4 index (0·69 [0·66-0·72]) and NAFLD Fibrosis Score (0·74 [0·72-0·77]). Findings were consistent in three other validation cohorts (n=2554), albeit accuracy was slightly lower. Using a rule-out cutoff of less than 25% (indicating no further examinations required), LiverPRO had a rule-out sensitivity of 80·6% (95% CI 76·4-84·3) and a rule-out negative predictive value of 98·0% (95% CI 97·5-98·4) in the DECIDE cohort. Similarly, with a rule-out cutoff of less than 1·3, FIB-4 had a rule-out sensitivity of 53·8% (48·5-58·9) and a rule-out negative predictive value of 95·8% (95·1-96·4). For rule-in thresholds, using a cutoff of more than 65% (indicating referral to a hepatologist required) LiverPRO had a rule-in specificity of 95·5% (95% CI 94·9-96·0) and a rule-in positive predictive value of 33·0% (95% CI 28·5-37·8) in the DECIDE cohort whereas FIB-4, with a rule-in threshold of 2·67, had a rule-in specificity of 98·7% (94·9-96·0) and a rule-in positive predictive value 35·6% (27·0-44·9). Using UK Biobank data, LiverPRO predicted liver-related events with a C-statistic of 0·80 (0·77-0·84) at 2 years.

INTERPRETATION

LiverPRO reliably identifies clinically significant liver fibrosis and elevated liver stiffness, predicts the risk of liver-related events in primary care, and is adaptable to the availability of different liver blood test analytes. On the basis of these results LiverPRO was certified according to IVDR class b, obtaining European CE approval in 2024.

FUNDING

EU Horizon 2020 research and innovation programme and Novo Nordisk Foundation.

Machine-learning-based plasma metabolomic profiles for predicting long-term complications of cirrhosis

BACKGROUND AND AIMS

The complications of liver cirrhosis occur after long asymptomatic stages of progressive fibrosis and are generally diagnosed late. We aimed to develop a plasma metabolomic-based score tool to predict these events.

APPROACH AND RESULTS

We enrolled 64,005 UK biobank participants with metabolomic profiles. Participants were randomly divided into the training (n=43,734) and validation cohorts (n=20,271). Liver cirrhosis complications were defined as hospitalization for liver cirrhosis or presentation with HCC. An interpretable machine-learning framework was applied to learn the metabolomic states extracted from 168 circulating metabolites in the training cohort. An integrated nomogram was developed and compared to conventional and genetic risk scores. We created 3 groups: low-risk, middle-risk, and high-risk through selected cutoffs of the nomogram. The predictive performance was validated through the area under a time-dependent receiver operating characteristic curve (time-dependent AUC), calibration curves, and decision curve analysis. The metabolomic state model could accurately predict the 10-year risk of liver cirrhosis complications in the training cohort (time-dependent AUC: 0.84 [95% CI: 0.82-0.86]), and outperform the fibrosis-4 index (time-dependent AUC difference: 0.06 [0.03-0.10]) and polygenic risk score (0.25 [0.21-0.29]). The nomogram, integrating metabolomic state, aspartate aminotransferase, platelet count, waist/hip ratio, and smoking status showed a time-dependent AUC of 0.930 at 3 years, 0.889 at 5 years, and 0.861 at 10 years in the validation cohort, respectively. The HR in the high-risk group was 43.58 (95% CI: 27.08-70.12) compared with the low-risk group.

CONCLUSIONS

We developed a metabolomic state-integrated nomogram, which enables risk stratification and personalized administration of liver-related events.

Metabolic Dysfunction-Associated Steatotic Liver Disease

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common chronic liver disease in the United States. It is characterized by steatosis in the liver and is potentially reversible. Risk factors include obesity, type 2 mellitus, and other metabolic disorders. Metabolic dysfunction-associated steatohepatitis (MASH), a more severe form of MASLD, puts patients at risk for cirrhosis, liver decompensation, and liver cancer. Diet, exercise, and weight loss are the cornerstones of management. Although only 1 medication has been approved for treatment of MASH, other pharmacotherapies and surgeries that aid weight loss and optimize metabolic risk factors can be used. Early diagnosis and intervention are important to prevent progression to cirrhosis and its complications, including cancer.

Elevated thyroid autoantibodies as risk factors for metabolic dysfunction-associated fatty liver disease in type 2 diabetes mellitus

Objective

This study aims to explore the relationship between thyroid peroxidase antibody (TPOAb) and thyroglobulin antibody (TgAb) levels and metabolic dysfunction-associated fatty liver disease (MAFLD) in patients with type 2 diabetes mellitus (T2DM), providing a theoretical basis for MAFLD prevention and treatment.

Methods

From June 2020 to May 2023, 534 T2DM patients were selected from the Endocrinology Department of Xiangyang Hospital affiliated with Wuhan University of Science and Technology. After applying exclusion criteria, 432 subjects were included. Based on abdominal ultrasound and MAFLD diagnostic criteria, subjects were divided into non-MAFLD (n=163) and MAFLD (n=260) groups. Differences in various indicators between the two groups were compared. Correlation analysis assessed the relationship between TPOAb, TgAb, and other indicators, and the prevalence of MAFLD was analyzed under different thyroid function and antibody levels. Multivariate logistic regression identified risk factors for MAFLD in T2DM patients. According to the FIB-4 index, the group with MAFLD was divided into low-risk (FIB-4< 1.30, n=150), medium-risk (1.30≤FIB-4 ≤ 2.67, n=100), and high-risk liver fibrosis groups (FIB-4 > 2.67, n=10). Differences in thyroid function and autoantibody levels among the three groups were compared.

Results

Compared to non-MAFLD patients, 73.46% of MAFLD patients were overweight or obese, were younger, and had a shorter duration of diabetes. Under normal thyroid function, MAFLD patients had higher levels of TSH, TgAb, and TPOAb (P<0.05). The prevalence of TgAb+, TPOAb+, and TgAb/TPOAb+ was significantly higher at 21.9%, 22.1%, and 29.6%, respectively, with higher prevalence in females. Spearman's correlation showed a positive correlation between TgAb, TPOAb, and AST, and between TPOAb and FINS. MAFLD prevalence varied among quartiles of TSH, TPOAb, and TgAb levels, with significant differences in TPOAb and TgAb components (P<0.05). MAFLD prevalence was positively correlated with TgAb and TPOAb levels. Thyroid autoantibody-positive patients had a significantly higher MAFLD prevalence (P=0.010) at 71.96%. Multivariate logistic analysis found elevated TSH and TPOAb levels as risk factors for MAFLD in T2DM patients [(OR 1.441, 95% CI: 1.213-1.712, P<0.001), (OR 1.005, 95% CI: 1.000-1.010, P=0.040)]. Medium-risk liver fibrosis patients had higher TgAb and TPOAb levels than low-risk and high-risk groups [TgAb: 1.04(0.59,2.83) vs 1.54(0.76,7.35) vs 0.55(0.27,1.32), P=0.035; TPOAb: 1.0(0.29,3.83) vs 2.42(0.5,23.08) vs 0.17(0.09,2.71), P=0.002]. Further comparisons revealed a significant difference in TgAb levels between the medium-risk and high-risk groups (P = 0.048). Additionally, significant differences in TPOAb levels were observed between the low-risk and medium-risk groups and between the medium-risk and high-risk groups (P = 0.016,P = 0.014).

Conclusion

In T2DM patients with MAFLD, elevated TSH, TgAb, and TPOAb levels are observed under normal thyroid function. Elevated TSH and TPOAb levels are risk factors for MAFLD in T2DM patients. TgAb and TPOAb levels vary among liver fibrosis risk groups, showing an inverted "V" pattern, suggesting a role in MAFLD progression to liver fibrosis.

Utility of Quantitative Assessment of Tc-99m-diethylenetriamine-penta-acetic acid-galactosyl Human Serum Albumin SPECT/CT in the Identification of Severe Liver Fibrosis: Its Complementary Diagnostic Value with Other Liver Function Indices

PURPOSE

To evaluate the value of Tc-99m-diethylenetriamine-penta-acetic acid-galactosyl human serum albumin (99mTc-GSA) single photon emission computed tomography (SPECT) for assessing liver fibrosis, and to assess its complementary value to other liver function indices such as fibrosis-4 (FIB-4) index and indocyanine green (ICG) clearance test parameters (ICG-R15 and ICG-K).

PROCEDURES

Seventy-eight patients with chronic liver disease and hepatocellular carcinoma who underwent 99mTc-GSA scintigraphy and other liver function tests including ICG test and FIB-4 index prior to hepatectomy were studied. 99mTc-GSA imaging was performed with SPECT/CT scanner (Discovery NM/CT 670). Immediately after injection of 99mTc-GSA, dynamic imaging was performed for 20 min, followed by SPECT data acquisition for 6 min. LHL15 which is a conventional index by 99mTc-GSA planar images, and liver uptake ration (LUR) was measured from 99mTc-GSA SPECT images. From the liver resection specimens, the degree of liver fibrosis was graded according to the Ludwig scale (F0-4).

RESULTS

Significant differences in LUR, LHL15, ICG-R15, ICG-K, platelet count and FIB-4 index were found between the F0-3 and F4 liver fibrosis patient groups (P < 0.05). Multivariate logistic regression analysis revealed that LUR and ICG-K were independent factors for identifying severe liver fibrosis (F4). Area under the curve of receiver operating curve analysis for the logistic regression model using LUR and ICG-K was 0.83. In the patient group with higher FIB-4 (≥ 3.16), the diagnostic performance of LUR for detecting severe liver fibrosis was significantly better than LHL15 (AUC: 0.83 vs. 0.75, P = 0.048). In the high FIB-4 index group, the sensitivity and specificity for identifying F4 was 88% and 85%, respectively, with LUR cutoff value of 41.2%.

CONCLUSIONS

LUR, measured by 99mTc-GSA SPECT, is a useful indicator for identifying sever liver fibrosis. Particularly in patients with high FIB-4 index (≥ 3.16), LUR can be a valuable indicator to identify severe liver fibrosis with high diagnostic accuracy.

Non-invasive tests for alcohol-associated liver disease

Alcohol consumption is a global phenomenon and a major contributor to alcohol-associated liver disease (ALD). Detecting individuals at risk of ALD has been challenging, with only a small fraction of patients being identified at early stages compared to other chronic liver diseases. In response to this challenge, non-invasive tests (NITs) have become essential tools for the detection of ALD, offering opportunities for early identification and intervention to mitigate the disease burden. Noninvasive alcohol consumption biomarkers are crucial in estimating individuals' recent alcohol intake, providing valuable insights into their drinking patterns. Various NITs have been investigated for the initial screening of asymptomatic individuals at risk of ALD, as well as for identifying specific stages of the disease. These NITs are applied in 2 main clinical scenarios: population-based stratification for identifying and predicting liver-related symptoms and diagnosing and prognosticating compensated cirrhosis or advanced chronic liver disease in secondary or tertiary care settings. Moreover, NITs play a significant role in the prognostic assessment of patients with various manifestations of ALD, including alcohol-associated hepatitis (AH), decompensated cirrhosis, and metabolic-associated and ALD. These tests guide appropriate treatment decisions and predict outcomes. In this review, various NITs for the early detection and monitoring of alcohol consumption were discussed. Additionally, the evaluation of NITs for screening and predicting ALD and liver complications was addressed comprehensively. Future perspectives of NITs for ALD were explored, alongside a thorough discussion of the opportunities and challenges associated with NITs for ALD screening.

GLCV-NET: An automatic diagnosis system for advanced liver fibrosis using global-local cross view in B-mode ultrasound images

BACKGROUND AND OBJECTIVE

Advanced liver fibrosis is a critical stage in the evaluation of chronic liver disease (CLD), holding clinical significance in the development of treatment strategies and estimating the disease progression.

METHODS

This paper proposes an innovative Global-Local Cross-View Network (GLCV-Net) for the automatic diagnosis of advanced liver fibrosis from ultrasound (US) B-mode images. The proposed method consists of three main components: 1. A Segmentation-enhanced Global Hybrid Feature Extractor for segmenting the liver parenchyma and extracting global features; 2. A Heatmap-weighted Local Feature Extractor for selecting candidate regions and automatically identifying suspicious areas to construct local features; 3. A Scale-adaptive Fusion Module to balance the contributions of global and local scales in evaluating advanced liver fibrosis.

RESULTS

The predictive performance of the model was validated on an internal dataset of 1003 chronic liver disease (CLD) patients and an external dataset of 46 CLD patients, both subjected to liver fibrosis staging through pathological assessment. On the internal dataset, GLCV-Net achieved 86.9% accuracy, 85.0% recall, 85.4% precision, and 85.2% F1-score. Further validation on the external dataset confirmed its robustness, with scores of 86.1% in accuracy, 83.1% in recall, 80.8% in precision, and 81.9% in F1-score.

CONCLUSION

These results underscore the GLCV-Net's potential as a promising approach for non-invasively and accurately diagnosing advanced liver fibrosis in CLD patients, breaking through the limitations of traditional methods by integrating global and local information of liver fibrosis, significantly enhancing diagnostic accuracy.

Forns index and fatty liver index, but not FIB-4, are associated with indices of glycaemia, pre-diabetes and type 2 diabetes: analysis of The Maastricht Study

OBJECTIVE

Glucose metabolism status (GMS) is linked to non-alcoholic fatty liver disease (NAFLD). Higher levels of advanced glycation end products (AGEs) are observed in people with type 2 diabetes mellitus (T2DM) and NAFLD. We examined the association between GMS, non-invasive tests and AGEs, with liver steatosis and fibrosis.

METHODS

Data from The Maastricht Study, a population-based cohort, were analysed. Participants with alcohol overconsumption or missing data were excluded. GMS was determined via an oral glucose tolerance test. AGEs, measured by skin autofluorescence (SAF), were assessed using an AGE Reader. Associations of GMS and SAF with the fibrosis-4 score (FIB-4), Forns index (FI) and fatty liver index (FLI) were investigated using multivariable linear regression, adjusted for sociodemographic, lifestyle and clinical variables.

RESULTS

1955 participants (56.6%) were analysed: 598 (30.6%) had T2DM, 264 (13.5%) had pre-diabetes and 1069 (54.7%) had normal glucose metabolism. Pre-diabetes was significantly associated with FLI (standardised regression coefficient (Stβ) 0.396, 95% CI 0.323 to 0.471) and FI (Stβ 0.145, 95% CI 0.059 to 0.232) but not FIB-4. T2DM was significantly associated with FLI (Stβ 0.623, 95% CI 0.552 to 0.694) and FI (Stβ 0.307, 95% CI 0.226 to 0.388) but not FIB-4. SAF was significantly associated with FLI (Stβ 0.083, 95% CI 0.036 to 0.129), FI (Stβ 0.106, 95% CI 0.069 to 0.143) and FIB-4 (Stβ 0.087, 95% CI 0.037 to 0.137).

CONCLUSION

The study showed that adverse GMS and higher glycaemia are positively associated with steatosis. FI, but not FIB-4, was related to adverse GMS concerning fibrosis. This study is the first to demonstrate that SAF is positively associated with steatosis and fibrosis.

Development and pilot evaluation of an evidence-based algorithm for MASLD (formerly NAFLD) management in primary care in Europe

Background

Metabolic dysfunction-associated steatotic liver disease (MASLD, formerly NAFLD), emerges as major cause of morbidity and mortality globally, with chronic patients facing increased risk. Guidelines on MASLD management in primary care (PC) are limited. This study aimed to develop and evaluate a clinical care pathway for use in PC to improve MASLD screening and management, including early detection, communication and treatment, in three European countries (Greece, Spain, the Netherlands).

Methods

An international multidisciplinary panel of experts oversaw pathway development, which was designed as a two-step algorithm with defined and sequenced tasks. To evaluate algorithm implementation, a controlled pilot study was conducted. Patients at risk of MASLD were assigned to general practitioners (GPs) trained in algorithm implementation (active group) or usual care (control group) and followed for 4-8 weeks. Primary outcomes were the number of patients screened for MASLD, managed in PC and referred to specialists.

Results

In this algorithm, patients with metabolic or liver dysfunction, confirmed MASLD or cardiovascular disease are screened with FIB-4 and classified as having risk of low-level (FIB-4 < 1.3), intermediate-level (1.3 ≤ FIB-4 < 2.67) or high-level MASLD (FIB-4 ≥ 2.67). The algorithm provides evidence-based tools to support GPs manage patients with risk of low-level MASLD in PC, coordinate linkage of patients with risk of high-level MASLD to specialists and refer patients with risk of intermediate-level MASLD for elastography (low-risk if <7.9 kPa or intermediate/high-risk if ≥7.9 kPa). During pilot evaluation, N = 37 participants were recruited in Spain (54.1% women, median age: 63 years). Significantly higher rates of patients in the active group (n = 17) than the control group (n = 20) were screened with FIB-4 (94.1% vs. 5.5%, p = 0.004). Patients in the active group received significantly more frequently a PC intervention for weight loss (70.6% vs. 10.0%, p < 0.001), alcohol regulation (52.9% vs. 0%, p < 0.001) and smoking cessation (29.4% vs. 0%, p = 0.005). In Greece no algorithm implementation was observed in either the active or control group, while the evaluation was not conducted in the Netherlands for logistic reasons.

Conclusion

This study provides evidence on the development and implementation of a new PC algorithm for MASLD screening and management. Variations among participating settings in algorithm implementation are indicative of context-specific particularities. Further research is necessary for integrating such pathways in tailored interventions to tackle this emerging public health issue.

Modified FIB-4 Index in Type 2 Diabetes Mellitus with Steatosis: A Non-Linear Predictive Model for Advanced Hepatic Fibrosis

Background: The Fibrosis-4 (FIB-4) index is widely recommended as a first-tier method for screening advanced hepatic fibrosis; however, its diagnostic performance is known to be suboptimal in patients with Type 2 diabetes mellitus (T2DM). We aim to propose a modified FIB-4, using the parameters of the existing FIB-4, tailored specifically for diabetic patients with metabolic dysfunction-associated steatotic liver disease (MASLD). Methods: A total of 1503 patients who underwent liver biopsy were divided into T2DM (n = 517) and non-T2DM (n = 986) groups. The model was developed using multiple regression analysis in the derivation cohort and validated in the validation cohort. Diagnostic accuracy was evaluated using the area under the receiver operating characteristic (AUC) curves. Results: Among the 1503 individuals, those with T2DM were older, more likely to be male, and had a higher prevalence of advanced hepatic fibrosis (≥F3) compared to non-T2DM individuals. Independent risk factors for advanced fibrosis in T2DM included age, AST, AST/ALT ratio, albumin, triglycerides, and platelet count. The optimized FIB-4 model for T2DM with MASLD (Diabetes Fibrosis Index) demonstrated superior diagnostic accuracy (AUC 0.771) compared to the FIB-4 (AUC 0.735, p = 0.012). The model showed a higher negative predictive value than the original FIB-4 across all age groups in the diabetic group. Conclusions: The newly optimized FIB-4 model for T2DM with MASLD (Diabetes Fibrosis Index), incorporating a non-linear predictive model, improves diagnostic performance (AUC) and the negative predictive value in MASLD with T2DM.

Risk Score for Hepatocellular Cancer in Adults Without Viral Hepatitis or Cirrhosis

IMPORTANCE

Hepatocellular carcinoma (HCC) is typically detected only at advanced stages when treatment options are limited. Most of the current HCC risk models focus on patients with viral hepatitis or diagnosed cirrhosis or require variables not routinely available in clinical care.

OBJECTIVE

To identify modifiable HCC risk factors in the general population and to develop a risk score to inform HCC screening and risk-factor modification interventions for high-risk individuals without viral hepatitis or decompensated cirrhosis.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study analyzed demographic, clinical, laboratory, and diagnostic data from the US Department of Veterans Affairs (VA) electronic health records. Data were divided into development and validation samples. Veterans aged 30 to 95 years were included, and those with hepatitis B or C virus infection, hepatic decompensation, or prevalent HCC were excluded. Patients were followed up until the occurrence of HCC diagnosis, death, or December 31, 2021. A Cox proportional hazards regression model for 10-year risk of HCC was developed and used to create an HCC risk score, and performance in development and validation samples and in patient subgroups was evaluated. One outpatient visit date per person at least 18 months after VA entry, between October 1, 2007, and March 31, 2020, was randomly selected and used as the index date for the start of follow-up. Analyses were performed from March 2023 to May 2024.

EXPOSURES

Age, sex, race and ethnicity, body mass index, liver fibrosis (detected with Fibrosis-4 Index [FIB-4]), diabetes status, smoking status, and alcohol use.

MAIN OUTCOMES AND MEASURES

First HCC diagnosis during follow-up. This information was ascertained from VA national cancer registry topography and histology codes and from International Classification of Diseases, Ninth Revision and International Statistical Classification of Diseases, Tenth Revision, Clinical Modification diagnosis codes for the inpatient or outpatient visits.

RESULTS

This study of 6 509 288 veterans included 6 048 917 males (92.9%), with a median (IQR) age of 65 (54-74) years, who identified as being of Hispanic (5.3%), non-Hispanic Black (15.0%), non-Hispanic White (68.9%), or other (4.6%) race and ethnicity. Overall, 15 142 patients (0.2%) developed HCC, 69.5% of whom had FIB-4 of 3.25 or lower at baseline. While FIB-4 was the most important variable, age, sex, race and ethnicity, body mass index, diabetes, smoking, and alcohol use were also informative. Discrimination in the development sample was better than FIB-4 alone (C statistic, 0.83 [95% CI, 0.82-0.85] vs 0.79 [95% CI, 0.77-0.80]). The HCC risk score performed consistently well in the validation sample and in all subgroups. A FIB-4 threshold of 3.25 would screen 5.0% of the cohort at a cost of 28 false-positives for every true-positive; a model risk score of 58 would screen 4.7% of the cohort at a cost of 23 false-positives for every true-positive.

CONCLUSIONS AND RELEVANCE

Results of this study suggest that a multivariable risk score that uses routinely available clinical data outperforms FIB-4 alone in identifying patients at risk of HCC who do not have viral hepatitis or hepatic decompensation at baseline.

Steatotic liver disease

Steatotic liver disease is the overarching term for conditions characterised by abnormal lipid accumulation in the liver (liver or hepatic steatosis). Steatotic liver disease encompasses what was previously termed non-alcoholic fatty liver disease (NAFLD), which is now called metabolic dysfunction-associated steatotic liver disease (MASLD). Additionally, steatotic liver disease includes alcohol-related liver disease (ALD) and MetALD, the new classification for the overlap between MASLD and ALD, and rare causes of liver steatosis. Cirrhosis is globally the 11th leading cause of death, and steatotic liver disease has become the leading cause of cirrhosis in the EU and USA. Steatotic liver disease affects around 30% of the global population and is mainly driven by obesity, type 2 diabetes, and alcohol intake, but only a minor proportion with steatotic liver disease progress to cirrhosis. The presence and progression of liver fibrosis led by hepatic inflammation is the main predictor of liver-related death across the entire spectrum of steatotic liver diseases. A combination of recent advancements of widely available biomarkers for early detection of liver fibrosis together with considerable advancements in therapeutic interventions offer the possibility to reduce morbidity and mortality in patients with steatotic liver disease. This Seminar covers the recent reclassification of steatotic liver disease and how it reflects clinical practice and prognosis. For early detection of liver fibrosis, we propose a collaborative diagnostic framework between primary care and liver specialists. Lastly, we discuss current best practices for managing steatotic liver disease, we explore therapeutic targets across the spectrum of steatotic liver diseases, and we review the pipeline of drugs in development for MASLD.

Noninvasive Tests in Assessment of Patients with Alcohol-Associated Liver Disease

Alcohol-associated liver disease (ALD) remains a significant public health concern, accounting for at least half of cirrhosis cases in Europe. Historically, liver biopsy has been considered the gold standard method for both diagnosing and staging ALD. However, in the past 3 decades, there has been a growing interest in developing noninvasive biomarkers for identifying high-risk patients prone to develop liver-related complications, including elastography methods or blood-based biomarkers. This review aims to summarize currently available noninvasive testing methods that are clinically available for assessing patients with ALD, including notably steatosis and fibrosis.

Association between liver fibrosis and the in-hospital mortality in patients with sepsis-induced coagulopathy

BACKGROUND

The impact of liver fibrosis on the clinical outcomes of patients with sepsis-induced coagulopathy (SIC) is not well understood. This study aimed to evaluate the association between liver fibrosis scores and in-hospital mortality in SIC patients.

METHODS

In this retrospective observational cohort study, data were collected from patients diagnosed with sepsis and admitted to the ICU at the First Affiliated Hospital of Wenzhou Medical University between January 2017 and December 2023. Liver fibrosis was evaluated using three scores: Fibrosis-4 (Fib-4), Aspartate Aminotransferase-to-Platelet Ratio Index (APRI), and Nonalcoholic Fatty Liver Disease Fibrosis Score (NFS). Patients were divided into tertiles according to their liver fibrosis scores, and the primary outcome was in-hospital mortality. Multivariable logistic regression and restricted cubic spline regression analyses were used to assess associations, complemented by sensitivity analyses through subgroup evaluations.

RESULTS

The cohort included 948 patients diagnosed with SIC with an in-hospital mortality of 26.16%. Multivariate logistic regression analysis revealed a significant association between higher liver fibrosis scores and increased in-hospital mortality. Specifically, patients in the highest tertile of Fib-4, APRI, and NFS scores had significantly higher odds of mortality (FIB-4: OR 3.62, 95% CI 1.03-12.69; APRI: OR 2.16, 95% CI 0.88-5.30; NFS: OR 6.80, 95% CI 2.11-21.93) compared to those in the lowest tertile. The restricted cubic spline regression model showed a linear increase in the risk of in-hospital mortality with increasing liver fibrosis score. Sensitivity analysis confirmed the consistency and stability of the results across the different subgroups.

CONCLUSION

Our study suggests that elevated liver fibrosis scores, particularly Fib-4 and NFS, are associated with higher in-hospital mortality in SIC patients. Further research, especially larger prospective studies, are needed to validate these findings.