Liver biopsy-based validation, confirmation and comparison of the diagnostic performance of established and novel non-invasive non-alcoholic fatty liver disease indexes:Results from a large multi-center study

Background: Non-invasive tools (NIT) for non-alcoholic fatty liver disease (NAFLD) screening or diagnosis need to be thoroughly validated using liver biopsies.Purpose: To externally validate NITs designed to differentiate the presence or absence of liver steatosis as well as more advanced disease stages, to confirm fully validated indexes (n = 7 NITs), to fully validate partially validated indexes (n = 5 NITs), and to validate for the first time one new index (n = 1 NIT).Methods: This is a multi-center study from two Gastroenterology-Hepatology Departments (Greece and Australia) and one Bariatric-Metabolic Surgery Department (Italy). Overall, n = 455 serum samples of patients with biopsy-proven NAFLD (n = 374, including 237 patients with non-alcoholic steatohepatitis (NASH)) and Controls (n = 81) were recruited. A complete validation analysis was performed to differentiate the presence of NAFLD vs. Controls, NASH vs. NAFL, histological features of NASH, and fibrosis stages.Results: The index of NASH (ION) demonstrated the highest differentiation ability for the presence of NAFLD vs. Controls, with the area under the curve (AUC) being 0.894. For specific histological characterization of NASH, no NIT demonstrated adequate performance, while in the case of specific features of NASH, such as hepatocellular ballooning and lobular inflammation, ION demonstrated the best performance with AUC being close to or above 0.850. For fibrosis (F) classification, the highest AUC was reached by the aspartate aminotransferase to platelet ratio index (APRI) being ~0.850 yet only with the potential to differentiate the severe fibrosis stages (F3, F4) vs. mild or moderate fibrosis (F0–2) with an AUC > 0.900 in patients without T2DM. When we excluded patients with morbid obesity, the differentiation ability of APRI was improved, reaching AUC = 0.802 for differentiating the presence of fibrosis F2–4 vs. F0–1. The recommended by current guidelines index FIB-4 seemed to differentiate adequately between severe (i.e., F3–4) and mild or moderate fibrosis (F0–2) with an AUC = 0.820, yet this was not the case when FIB-4 was used to classify patients with fibrosis F2–4 vs. F0–1. Trying to improve the predictive value of all NITs, using Youden's methodology, to optimize the suggested cut-off points did not materially improve the results.Conclusions: The validation of currently available NITs using biopsy-proven samples provides new evidence for their ability to differentiate between specific disease stages, histological features, and, most importantly, fibrosis grading. The overall performance of the examined NITs needs to be further improved for applications in the clinic

The HIV patient profile in 2013 and 2003: Results from the Greek AMACS cohort.

Combined Antiretroviral therapy (cART) has improved life-expectancy of people living with HIV (PLHIV) but as they age, prevalence of chronic non-AIDS related comorbidities may increase. We study the evolution of HIV-disease markers and comorbidities' prevalence in PLHIV in Greece. Two cross-sectional analyses (2003 and 2013) on data from the AMACS cohort were performed. Comparisons were based on population average models and were repeated for subjects under follow-up at both 2003 and 2013. 2,403 PLHIV were identified in 2003 and 4,910 in 2013 (1,730 contributing for both cross-sections). Individuals in 2013 were on average older, diagnosed/treated for HIV for longer, more likely to be on cART, virologically suppressed, and with higher CD4 counts. Chronic kidney disease, dyslipidemia and hypertension prevalence increased over time. There was an increase in prescription of lipid-lowering treatment (3.5% in 2003 vs. 7.7% 2013, p20%) increased from 18.2% to 22.2% (p = 0.002). Increase in the prevalence of comorbidities was more pronounced in the subset of patients who were followed in both 2003 and 2013. The increased availability and uptake of cART led to significant improvements in the immuno-virological status of PLHIV in Greece, but they aged alongside an increase in prevalence of non-AIDS related comorbidities. These results highlight the need for appropriate monitoring, optimal cART selection and long-term management and prevention strategies for such comorbidities

The First External Validation of the Dallas Steatosis Index in Biopsy-proven Non-alcoholic Fatty Liver Disease:a Multicenter study

AIMS: A new non-invasive tool (NIT) for non-alcoholic fatty liver disease (NAFLD) proposed in 2022 by the multi-ethnic Dallas Heart Study, i.e. the Dallas Steatosis Index (DSI), was validated herein using for the first time the gold standard i.e. liver biopsy-proven NAFLD.METHODS: This is a multicenter study based on samples and data from two Gastroenterology-Hepatology Clinics (Greece and Australia) and one Bariatric-Metabolic Surgery Clinic (Italy). Overall, n=455 patients with biopsy-proven NAFLD (n=374) and biopsy-proven controls (n=81) were recruited.RESULTS: The ability of DSI to correctly classify participants as NAFLD or controls was very good, reaching an Area Under the Curve (AUC)=0.887. The cut-off point that could best differentiate the presence vs. absence of NAFLD corresponded to DSI=0.0 (risk threshold: 50% | Sensitivity: 0.88; Positive Predictive Value (PPV): 93.0%; F1-score=0.91). DSI demonstrated significantly better performance characteristics than other liver steatosis indexes. Decision curve analysis revealed that the benefit of DSI as a marker to indicate the need for invasive liver assessment was confirmed only when higher DSI values, i.e.≥1.4, were used as risk thresholds. DSI performance to differentiate disease progression was inadequate (all AUCs&lt;0.700).CONCLUSIONS: DSI is more useful for disease screening (NAFLD vs. controls) than to differentiate diseases stages or progression. The value of any inclusion of DSI to guidelines needs to be further studied.</p

Liver biopsy-based validation, confirmation and comparison of the diagnostic performance of established and novel non-invasive non-alcoholic fatty liver disease indexes:Results from a large multi-center study

Background: Non-invasive tools (NIT) for non-alcoholic fatty liver disease (NAFLD) screening or diagnosis need to be thoroughly validated using liver biopsies.Purpose: To externally validate NITs designed to differentiate the presence or absence of liver steatosis as well as more advanced disease stages, to confirm fully validated indexes (n = 7 NITs), to fully validate partially validated indexes (n = 5 NITs), and to validate for the first time one new index (n = 1 NIT).Methods: This is a multi-center study from two Gastroenterology-Hepatology Departments (Greece and Australia) and one Bariatric-Metabolic Surgery Department (Italy). Overall, n = 455 serum samples of patients with biopsy-proven NAFLD (n = 374, including 237 patients with non-alcoholic steatohepatitis (NASH)) and Controls (n = 81) were recruited. A complete validation analysis was performed to differentiate the presence of NAFLD vs. Controls, NASH vs. NAFL, histological features of NASH, and fibrosis stages.Results: The index of NASH (ION) demonstrated the highest differentiation ability for the presence of NAFLD vs. Controls, with the area under the curve (AUC) being 0.894. For specific histological characterization of NASH, no NIT demonstrated adequate performance, while in the case of specific features of NASH, such as hepatocellular ballooning and lobular inflammation, ION demonstrated the best performance with AUC being close to or above 0.850. For fibrosis (F) classification, the highest AUC was reached by the aspartate aminotransferase to platelet ratio index (APRI) being ~0.850 yet only with the potential to differentiate the severe fibrosis stages (F3, F4) vs. mild or moderate fibrosis (F0–2) with an AUC &gt; 0.900 in patients without T2DM. When we excluded patients with morbid obesity, the differentiation ability of APRI was improved, reaching AUC = 0.802 for differentiating the presence of fibrosis F2–4 vs. F0–1. The recommended by current guidelines index FIB-4 seemed to differentiate adequately between severe (i.e., F3–4) and mild or moderate fibrosis (F0–2) with an AUC = 0.820, yet this was not the case when FIB-4 was used to classify patients with fibrosis F2–4 vs. F0–1. Trying to improve the predictive value of all NITs, using Youden's methodology, to optimize the suggested cut-off points did not materially improve the results.Conclusions: The validation of currently available NITs using biopsy-proven samples provides new evidence for their ability to differentiate between specific disease stages, histological features, and, most importantly, fibrosis grading. The overall performance of the examined NITs needs to be further improved for applications in the clinic