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| ID | Type | Description | Link |
|---|---|---|---|
| PDP1/NT2311/13.05.2020 | Other Identifier | EEA Grants/Norway Grants under the Financial Mechanism 2014-2021, |
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| Name | Class |
|---|---|
| Transilvania University of Brasov | OTHER |
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This study aims to evaluate the presence of Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) risk factors and estimate the probability of advanced liver disease in a Romanian cohort from the European Health Examination Survey (EHES). Using standardized clinical, anthropometric, and laboratory data, the study will assess metabolic and alcohol-related contributors to liver disease. The primary focus is to identify an at-risk MASLD population, characterize associated metabolic risk factors, and evaluate disease awareness through the presence of ICD-10 diagnostic codes for liver disease.
The study applies the Forns Score as a validated non-invasive tool for assessing liver fibrosis risk and incorporates the latest EASL-AASLD 2024 guidelines to define MASLD, MASH, Alcohol-Related Liver Disease (ALD), and MetALD (combined metabolic and alcohol-related liver disease). Additionally, it will explore potential underdiagnosis rates of liver disease by comparing clinical risk markers with documented diagnoses.
The study is a post hoc, cross-sectional, retrospective analysis and does not involve new data collection or patient contact. Data analysis will be performed using descriptive statistics, subgroup comparisons, and multivariate models to assess relationships between metabolic risk factors, MASLD probability, and liver disease awareness. This research will contribute to the understanding of MASLD epidemiology in Romania and inform public health strategies for early detection and prevention.
Detailed Description
This study is designed as a post hoc analysis of data from the European Health Examination Survey (EHES) - Romania, focusing on MASLD risk factors and advanced liver disease probability. The EHES is a large-scale population survey conducted in European countries, with standardized methodologies for data collection, ensuring comparability across different nations.
Study Objectives Primary Objective: Define an at-risk MASLD population in Romania.
Secondary Objectives:
Identify additional liver disease risk factors (viral hepatitis, iron overload, alcohol consumption).
Identify a population of confirmed advanced liver disease patients. Assess hepatitis prevalence vs. disease awareness (ICD-10 coding). Identify potential risk factors associated with hepatitis.
Study Design and Methodology Study Type: Observational, cross-sectional, retrospective. Data Source: EHES Romania dataset. Population: Adults (≥18 years) included in the EHES survey. Exclusion Criteria: Missing Forns Score variables (platelet count, total cholesterol, gamma-glutamyl transferase, age).
Sample Size Estimation: Based on MASLD prevalence (25-30%), minimum n=1000-1500 for subgroup analyses. (5300 available) Definition of Liver Disease Subtypes (EASL-AASLD 2024 Guidelines) MASLD: Hepatic steatosis with at least one metabolic risk factor. MASH: Progressive MASLD with hepatocellular injury and fibrosis. ALD: Liver disease in individuals exceeding alcohol thresholds (≥30g/day men, ≥20g/day women).
MetALD: Overlap of MASLD and ALD.
Statistical Analysis Plan Descriptive statistics for population characteristics and MASLD prevalence. Subgroup comparisons (MASLD vs. non-MASLD, ALD vs. non-ALD, etc.). Multivariate logistic regression for risk factor associations. Sensitivity analysis for missing data handling. Quality Assurance and Data Management EHES follows standardized data validation, quality control, and external audits.
Data checks and verification against medical records ensure accuracy. No new data collection or patient interaction in this study.
Ethical Considerations The EHES obtained informed consent from all participants [PMID: 39491016]. This study uses anonymized, pre-existing data. No ethical approval needed beyond EHES compliance. Data Sharing Statement Individual participant data will not be publicly available. Aggregated results will be shared upon request. Funding Statement No external funding. Study Timeline Data analysis starts: 20/02/2025 Expected completion:1/04/2025
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| MASLD-At-Risk Cohort | Individuals meeting MASLD criteria based on metabolic dysfunction risk factors and hepatic steatosis. | ||
| MASH Cohort | Subgroup with MASLD who meet additional criteria for hepatic inflammation and fibrosis risk. | ||
| Alcohol-Related Liver Disease (ALD) Cohort: | Participants exceeding alcohol consumption thresholds who exhibit liver dysfunction and no other risk factors for liver diseas | ||
| MetALD Cohort: | Individuals exhibiting both MASLD and ALD characteristics, requiring combined metabolic and alcohol-related assessment and no other risk factors for liver disease | ||
| Non-MASLD Control Group | Participants with no significant metabolic dysfunction and normal liver function and no other risk factors for liver disease serving as a reference population. |
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| Measure | Description | Time Frame |
|---|---|---|
| Definition of an at-risk for MASLD population in Romania based on metabolic and hepatic risk factors. | Classification for the composite outcome requires the presence of at least one of the following five cardiometabolic risk factors: Overweight or Obesity: Defined by a Body Mass Index (BMI) ≥25 kg/m² for non-Asians and ≥23 kg/m² for Asians. Type 2 Diabetes Mellitus: A confirmed diagnosis of type 2 diabetes. Insulin Resistance: Indicators include fasting glucose levels ≥100 mg/dL or HbA1c ≥5.7%. Dyslipidemia: Characterized by triglycerides ≥150 mg/dL or reduced HDL cholesterol levels (<40 mg/dL for men and <50 mg/dL for women). Hypertension: Blood pressure readings ≥130/85 mmHg or the use of antihypertensive medications. Unit of Measure: Percentage of total study population. | Baseline |
| Measure | Description | Time Frame |
|---|---|---|
| Identification of Patients with Known Liver Disease | Description: The proportion of individuals with known liver disease Other known liver diseases will be accepted according to ICD-10: B18.0, B18.1, B18.8, B18.9, K75.4, E83.0, K74.3, K83.01, D86.8, D86.9, M35.00, M35.09 , K74.60, K74.69, K70.30, K70.31, K74.0, K74.1, K74.2, K76.0, K75.81 Unit of Measure: Percentage of participants with known liver disease from the sample |
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Inclusion Criteria:
Exclusion Criteria:
Missing essential data preventing reliable MASLD and liver disease risk assessment:
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The EHES study aimed to enroll a representative sample of the adult population aged 25-64. Considering the structure of the Romanian population in this age group, a minimum sample size of 4235 enrollees was considered. Also, knowing from other European EHES studies that the enrollment rate was 50%, the pre study sample population selected from the lists of family doctors was 9600. Out of the total 9600, after excluding non-eligibles (893), refusals (2846) and incomplete evaluations (481), 5380 participants were included in the study.
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Transylvania University School of Medicine | Brasov | Brașov County | 500019 | Romania | ||
| National Institute for Public Health |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 39491016 | Result | Brinduse LA, Eclemea I, Neculau AE, Paunescu BA, Bratu EC, Cucu MA. Rural versus urban healthcare through the lens of health behaviors and access to primary care: a post-hoc analysis of the Romanian health evaluation survey. BMC Health Serv Res. 2024 Nov 4;24(1):1341. doi: 10.1186/s12913-024-11861-9. | |
| 12297848 | Result |
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| Baseline |
| Identification of a Population with Probable Advanced Liver Disease: | Description: This outcome will estimate the prevalence of advanced liver disease using the Forns Score. Assessment Methods: The Forns Score will be applied to identify individuals at high risk of fibrosis. FORNS calculation utilizes the following formula : [7.811 - 3.131 × ln [number of platelets] × 0.781 ln [GGTP (U/L)] + 3.467 × ln [age (years)] - 0.014 [cholesterol (mg/dL)]\]. Risk Classification: Low Risk: Forns Score <4.2 (rules out significant fibrosis, ≥F2) High Risk: Forns Score >6.9 (indicates significant fibrosis, ≥F2) Unit of Measure: Percentage of participants Time Frame: Baseline | Baseline |
| Identification of Potential Factors Associated with advanced liver disease. | This outcome will analyze demographic, metabolic, and lifestyle variables associated with the presence of viral hepatitis. Assessment Methods: Multivariable logistic regression will be used to assess associations between hepatitis status and: Demographics: Age, sex, socioeconomic status Metabolic risk factors: Obesity (BMI, WHR), diabetes (HbA1c, fasting glucose) Lifestyle: Smoking status, alcohol consumption, physical activity Outcome Measurement: Identification of significant predictors of hepatitis using adjusted odds ratios and confidence intervals. | Baseline |
| Bucharest |
| Bucharest |
| 050463 |
| Romania |
| Forns X, Ampurdanes S, Llovet JM, Aponte J, Quinto L, Martinez-Bauer E, Bruguera M, Sanchez-Tapias JM, Rodes J. Identification of chronic hepatitis C patients without hepatic fibrosis by a simple predictive model. Hepatology. 2002 Oct;36(4 Pt 1):986-92. doi: 10.1053/jhep.2002.36128. |
| 29777749 | Result | Pimpin L, Cortez-Pinto H, Negro F, Corbould E, Lazarus JV, Webber L, Sheron N; EASL HEPAHEALTH Steering Committee. Burden of liver disease in Europe: Epidemiology and analysis of risk factors to identify prevention policies. J Hepatol. 2018 Sep;69(3):718-735. doi: 10.1016/j.jhep.2018.05.011. Epub 2018 May 17. |
| 29749059 | Result | Peacock A, Leung J, Larney S, Colledge S, Hickman M, Rehm J, Giovino GA, West R, Hall W, Griffiths P, Ali R, Gowing L, Marsden J, Ferrari AJ, Grebely J, Farrell M, Degenhardt L. Global statistics on alcohol, tobacco and illicit drug use: 2017 status report. Addiction. 2018 Oct;113(10):1905-1926. doi: 10.1111/add.14234. Epub 2018 Jun 4. |
| 35917801 | Result | Stival C, Lugo A, Odone A, van den Brandt PA, Fernandez E, Tigova O, Soriano JB, Jose Lopez M, Scaglioni S, Gallus S; TackSHS Project Investigators. Prevalence and Correlates of Overweight and Obesity in 12 European Countries in 2017-2018. Obes Facts. 2022;15(5):655-665. doi: 10.1159/000525792. Epub 2022 Aug 2. |
| 30414863 | Result | Younossi ZM. Non-alcoholic fatty liver disease - A global public health perspective. J Hepatol. 2019 Mar;70(3):531-544. doi: 10.1016/j.jhep.2018.10.033. Epub 2018 Nov 9. |
| 28930295 | Result | Younossi Z, Anstee QM, Marietti M, Hardy T, Henry L, Eslam M, George J, Bugianesi E. Global burden of NAFLD and NASH: trends, predictions, risk factors and prevention. Nat Rev Gastroenterol Hepatol. 2018 Jan;15(1):11-20. doi: 10.1038/nrgastro.2017.109. Epub 2017 Sep 20. |