Metabolic Dysfunction-Associated Steatotic Liver DiseaseMASLD-PREVENTNCT07791589
Fibrosis and Metabolic Markers in Relation to PREVENT Cardiovascular Risk in MASLD
An observational study of Metabolic Dysfunction-Associated Steatotic Liver Disease, run by Özgür Bahadır at 1 site in Turkey (Türkiye).
Trial summary
This retrospective observational study evaluates the relationship between non-invasive liver fibrosis and metabolic markers and estimated cardiovascular risk in adults with metabolic dysfunction-associated steatotic liver disease (MASLD). Read more about this study
- Who is it for?
- Ages 30 to 79 years
- Conditions the study is for
- Metabolic Dysfunction-Associated Steatotic Liver Disease
- How many people
- 271 participants
- Where
- 1 siteTurkey (Türkiye)
- Study dates
- 1 Jun 2026to 1 Jul 2026
- Phase
- Observational
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 30 to 79 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Adults with MASLD who were evaluated at the study center between January 1, 2024 and April 30, 2026 and met the eligibility criteria for the primary PREVENT cardiovascular risk analysis.
Who may be able to join
- Adults aged 30 to 79 years. Metabolic dysfunction-associated steatotic liver disease (MASLD), defined by hepatic steatosis on ultrasonography together with at least one cardiometabolic risk factor.
- Clinical data available for calculation of the PREVENT cardiovascular risk estimates within the supported input ranges.
Who cannot join
- Alternative causes of chronic liver disease. One or more required PREVENT input variables outside the supported ranges: systolic blood pressure 90-200 mmHg, total cholesterol 130-320 mg/dL, HDL cholesterol 20-100 mg/dL, eGFR 15-140 mL/min/1.73 m², or BMI 18.5-39.9 kg/m².
- Prior cardiovascular disease, defined as a history of stroke, coronary artery disease, heart failure, atrial fibrillation, or peripheral arterial disease.
Trial locations and contacts
1 site in 1 country.
Turkey (Türkiye)1 site
Göztepe Prof. Dr. Süleyman Yalçın City Hospital
Istanbul, 34722
About this study
Official title: Fibrosis Versus Metabolic Risk in MASLD: Age-Adjusted Associations With PREVENT Cardiovascular Risk
This retrospective observational study evaluates the relationship between non-invasive liver fibrosis and metabolic markers and estimated cardiovascular risk in adults with metabolic dysfunction-associated steatotic liver disease (MASLD). The primary objective is to assess the association between the Fibrosis-4 index (FIB-4) and 10-year cardiovascular disease risk estimated using the American Heart Association PREVENT equations, with particular attention to the effect of age on this association. Secondary analyses evaluate the Fibrosis-3 index (FIB-3), triglyceride-glucose index (TyG), and liver stiffness measurement (LSM) in relation to PREVENT-estimated risks of cardiovascular disease, atherosclerotic cardiovascular disease, and heart failure.
Read the detailed description
This is a retrospective, single-center, observational study of adults with metabolic dysfunction-associated steatotic liver disease (MASLD) evaluated between January 1, 2024 and April 30, 2026. MASLD was defined by hepatic steatosis on ultrasonography together with at least one cardiometabolic risk factor, after exclusion of alternative causes of chronic liver disease.
Clinical and laboratory data were obtained from electronic medical records. Non-invasive indices included the Fibrosis-4 index (FIB-4), Fibrosis-3 index (FIB-3), triglyceride-glucose index (TyG), and liver stiffness measurement (LSM) by transient elastography when available.
Cardiovascular risk was estimated using the American Heart Association Predicting Risk of Cardiovascular Disease EVENTs (PREVENT) base equations. Ten-year estimates were calculated for total cardiovascular disease (PREVENT-CVD), atherosclerotic cardiovascular disease (PREVENT-ASCVD), and heart failure (PREVENT-HF).
The primary analysis examines the association between FIB-4 and PREVENT-CVD risk. FIB-3 and TyG are evaluated as secondary markers, while analyses involving PREVENT-ASCVD, PREVENT-HF, and LSM are supportive. Because age is incorporated into FIB-4 and is also a major determinant of cardiovascular risk, crude associations are compared with age-adjusted partial Spearman correlations. A sensitivity analysis is also performed in participants without diabetes.
Participants with prior cardiovascular disease were excluded from the primary prevention cohort. Analyses are based on complete cases, without imputation of missing data.
- Keywords
- PREVENT, FIB-4, FIB-3, Triglyceride-Glucose Index, Cardiovascular Risk
What is being measured
The primary outcome is the main question the study is designed to answer.
Correlation between FIB-4 score and 10-year PREVENT-CVD risk
FIB-4 score (unitless) was calculated as (age × AST)/(platelet count × √ALT). Ten-year PREVENT-CVD risk was expressed as a percentage (%) and calculated using the published sex-specific American Heart Association PREVENT base equation. Correlation was quantified using Spearman's rank correlation coefficient (rho; unitless, range -1 to +1). An age-adjusted partial Spearman correlation was also calculated.
Measured: At the index clinical evaluation during the retrospective study period (January 1, 2024 to April 30, 2026)
Secondary outcomes (11)
Correlation between FIB-3 score and 10-year PREVENT-CVD risk
FIB-3 score (unitless) was calculated as 5 × ln(AST) - 2 × ln(ALT) - 0.18 × (platelet count/10) - 5. Ten-year PREVENT-CVD risk was expressed as a percentage (%) and calculated using the published sex-specific American Heart Association PREVENT base equation. Correlation was quantified using Spearman's rank correlation coefficient (rho; unitless, range -1 to +1). An age-adjusted partial Spearman correlation was also calculated.
Measured: At the index clinical evaluation during the retrospective study period (January 1, 2024 to April 30, 2026)
Correlation between TyG index and 10-year PREVENT-CVD risk
The triglyceride-glucose (TyG) index (unitless) was calculated as ln[(fasting triglycerides × fasting glucose)/2], with triglycerides and glucose expressed in mg/dL. Ten-year PREVENT-CVD risk was expressed as a percentage (%) and calculated using the published sex-specific American Heart Association PREVENT base equation. Correlation was quantified using Spearman's rank correlation coefficient (rho; unitless, range -1 to +1). An age-adjusted partial Spearman correlation was also calculated.
Measured: At the index clinical evaluation during the retrospective study period (January 1, 2024 to April 30, 2026)
Correlation between liver stiffness measurement and 10-year PREVENT-CVD risk
Liver stiffness measurement (LSM) was expressed in kilopascals (kPa) and measured by transient elastography using a FibroScan 502 Touch system (Echosens, Paris, France). Ten-year PREVENT-CVD risk was expressed as a percentage (%) and calculated using the published sex-specific American Heart Association PREVENT base equation. Correlation was quantified using Spearman's rank correlation coefficient (rho; unitless, range -1 to +1). An age-adjusted partial Spearman correlation was also calculated.
Measured: At the index clinical evaluation during the retrospective study period (January 1, 2024 to April 30, 2026)
Correlation between FIB-4 score and 10-year PREVENT-ASCVD risk
FIB-4 score (unitless) was calculated as (age × AST)/(platelet count × √ALT). Ten-year PREVENT-ASCVD risk was expressed as a percentage (%) and calculated using the published sex-specific American Heart Association PREVENT base equation. Correlation was quantified using Spearman's rank correlation coefficient (rho; unitless, range -1 to +1). An age-adjusted partial Spearman correlation was also calculated.
Measured: At the index clinical evaluation during the retrospective study period (January 1, 2024 to April 30, 2026)
Correlation between FIB-3 score and 10-year PREVENT-ASCVD risk
FIB-3 score (unitless) was calculated as 5 × ln(AST) - 2 × ln(ALT) - 0.18 × (platelet count/10) - 5. Ten-year PREVENT-ASCVD risk was expressed as a percentage (%) and calculated using the published sex-specific American Heart Association PREVENT base equation. Correlation was quantified using Spearman's rank correlation coefficient (rho; unitless, range -1 to +1). An age-adjusted partial Spearman correlation was also calculated.
Measured: At the index clinical evaluation during the retrospective study period (January 1, 2024 to April 30, 2026)
Correlation between TyG index and 10-year PREVENT-ASCVD risk
The triglyceride-glucose (TyG) index (unitless) was calculated as ln[(fasting triglycerides × fasting glucose)/2], with triglycerides and glucose expressed in mg/dL. Ten-year PREVENT-ASCVD risk was expressed as a percentage (%) and calculated using the published sex-specific American Heart Association PREVENT base equation. Correlation was quantified using Spearman's rank correlation coefficient (rho; unitless, range -1 to +1). An age-adjusted partial Spearman correlation was also calculated.
Measured: At the index clinical evaluation during the retrospective study period (January 1, 2024 to April 30, 2026)
Correlation between liver stiffness measurement and 10-year PREVENT-ASCVD risk
Liver stiffness measurement (LSM) was expressed in kilopascals (kPa) and measured by transient elastography using a FibroScan 502 Touch system (Echosens, Paris, France). Ten-year PREVENT-ASCVD risk was expressed as a percentage (%) and calculated using the published sex-specific American Heart Association PREVENT base equation. Correlation was quantified using Spearman's rank correlation coefficient (rho; unitless, range -1 to +1). An age-adjusted partial Spearman correlation was also calculated.
Measured: At the index clinical evaluation during the retrospective study period (January 1, 2024 to April 30, 2026)
Correlation between FIB-4 score and 10-year PREVENT-HF risk
FIB-4 score (unitless) was calculated as (age × AST)/(platelet count × √ALT). Ten-year PREVENT-HF risk was expressed as a percentage (%) and calculated using the published sex-specific American Heart Association PREVENT base equation. Correlation was quantified using Spearman's rank correlation coefficient (rho; unitless, range -1 to +1). An age-adjusted partial Spearman correlation was also calculated.
Measured: At the index clinical evaluation during the retrospective study period (January 1, 2024 to April 30, 2026)
Correlation between FIB-3 score and 10-year PREVENT-HF risk
FIB-3 score (unitless) was calculated as 5 × ln(AST) - 2 × ln(ALT) - 0.18 × (platelet count/10) - 5. Ten-year PREVENT-HF risk was expressed as a percentage (%) and calculated using the published sex-specific American Heart Association PREVENT base equation. Correlation was quantified using Spearman's rank correlation coefficient (rho; unitless, range -1 to +1). An age-adjusted partial Spearman correlation was also calculated.
Measured: At the index clinical evaluation during the retrospective study period (January 1, 2024 to April 30, 2026)
Correlation between TyG index and 10-year PREVENT-HF risk
The triglyceride-glucose (TyG) index (unitless) was calculated as ln[(fasting triglycerides × fasting glucose)/2], with triglycerides and glucose expressed in mg/dL. Ten-year PREVENT-HF risk was expressed as a percentage (%) and calculated using the published sex-specific American Heart Association PREVENT base equation. Correlation was quantified using Spearman's rank correlation coefficient (rho; unitless, range -1 to +1). An age-adjusted partial Spearman correlation was also calculated.
Measured: At the index clinical evaluation during the retrospective study period (January 1, 2024 to April 30, 2026)
Correlation between liver stiffness measurement and 10-year PREVENT-HF risk
Liver stiffness measurement (LSM) was expressed in kilopascals (kPa) and measured by transient elastography using a FibroScan 502 Touch system (Echosens, Paris, France). Ten-year PREVENT-HF risk was expressed as a percentage (%) and calculated using the published sex-specific American Heart Association PREVENT base equation. Correlation was quantified using Spearman's rank correlation coefficient (rho; unitless, range -1 to +1). An age-adjusted partial Spearman correlation was also calculated.
Measured: At the index clinical evaluation during the retrospective study period (January 1, 2024 to April 30, 2026)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted28 Aug 2026
- Study start1 Jun 2026
- Primary completion1 Jul 2026
- Study completion1 Jul 2026
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (3)Papers the sponsor has linked to this study.
- Other trials for Metabolic Dysfunction-Associated Steatotic Liver DiseaseStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Retrospective
- Enrolment
- 271 participants (actual)
Sponsor and investigators
- Lead sponsor
- Özgür Bahadır
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Özgür Bahadır, Istanbul Medeniyet University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07791589
- Sponsor's protocol ID
- IMU-MASLD-PREVENT-01
- Acronym
- MASLD-PREVENT
- Status last verified
- Aug 2026
- First submitted
- 25 Aug 2026
- Last updated
- 28 Aug 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: De-identified individual participant data underlying the reported results may be shared with qualified researchers upon reasonable request to the corresponding author, subject to institutional and ethical approval.
Publications
Rinella ME, Lazarus JV, Ratziu V, Francque SM, Sanyal AJ, Kanwal F, Romero D, Abdelmalek MF, Anstee QM, Arab JP, Arrese M, Bataller R, Beuers U, Boursier J, Bugianesi E, Byrne CD, Castro Narro GE, Chowdhury A, Cortez-Pinto H, Cryer DR, Cusi K, El-Kassas M, Klein S, Eskridge W, Fan J, Gawrieh S, Guy CD, Harrison SA, Kim SU, Koot BG, Korenjak M, Kowdley KV, Lacaille F, Loomba R, Mitchell-Thain R, Morgan TR, Powell EE, Roden M, Romero-Gomez M, Silva M, Singh SP, Sookoian SC, Spearman CW, Tiniakos D, Valenti L, Vos MB, Wong VW, Xanthakos S, Yilmaz Y, Younossi Z, Hobbs A, Villota-Rivas M, Newsome PN; NAFLD Nomenclature consensus group. A multisociety Delphi consensus statement on new fatty liver disease nomenclature. J Hepatol. 2023 Dec;79(6):1542-1556. doi: 10.1016/j.jhep.2023.06.003. Epub 2023 Jun 24.
PubMed 37364790Kariyama K, Kawanaka M, Nouso K, Hiraoka A, Toyoda H, Tada T, Ishikawa T, Wakuta A, Miyake N, Murakami S, Shiota S, Kumada T; Real-Life Practice Experts for HCC (RELPEC) Study Group. Fibrosis-3 Index: A New Score to Predict Liver Fibrosis in Patients With Nonalcoholic Fatty Liver Disease Without Age as a Factor. Gastro Hep Adv. 2022 Aug 2;1(6):1108-1113. doi: 10.1016/j.gastha.2022.07.012. eCollection 2022.
PubMed 39131263Khan SS, Matsushita K, Sang Y, Ballew SH, Grams ME, Surapaneni A, Blaha MJ, Carson AP, Chang AR, Ciemins E, Go AS, Gutierrez OM, Hwang SJ, Jassal SK, Kovesdy CP, Lloyd-Jones DM, Shlipak MG, Palaniappan LP, Sperling L, Virani SS, Tuttle K, Neeland IJ, Chow SL, Rangaswami J, Pencina MJ, Ndumele CE, Coresh J; Chronic Kidney Disease Prognosis Consortium and the American Heart Association Cardiovascular-Kidney-Metabolic Science Advisory Group. Development and Validation of the American Heart Association's PREVENT Equations. Circulation. 2024 Feb 6;149(6):430-449. doi: 10.1161/CIRCULATIONAHA.123.067626. Epub 2023 Nov 10.
PubMed 37947085