Metabolic Dysfunction-Associated Fibrosis 5 (MAF-5) Score Predicts Liver Fibrosis Risk and Outcome in the General Population With Metabolic Dysfunction

被引:22
作者
van Kleef, Laurens A. [1 ]
Francque, Sven M. [2 ,3 ]
Prieto-Ortiz, Jhon E. [4 ]
Sonneveld, Milan J. [1 ]
Sanchez-Luque, Carlos B. [4 ]
Prieto-Ortiz, Robin G. [4 ]
Kwanten, Wilhelmus J. [2 ,3 ]
Vonghia, Luisa [2 ,3 ]
Verrijken, An [3 ,5 ]
De Block, Christophe [3 ,5 ]
Gadi, Zouhir [2 ,3 ]
Janssen, Harry L. A. [1 ,6 ]
de Knegt, Robert J. [1 ]
Brouwer, Willem Pieter [1 ]
机构
[1] Univ Med Ctr, Erasmus Med Ctr, Dept Gastroenterol & Hepatol, Dr Molewaterpl 40, NL-3015 GD Rotterdam, Netherlands
[2] Antwerp Univ Hosp, Dept Gastroenterol & Hepatol, Antwerp, Belgium
[3] Univ Antwerp, Lab Expt Med & Paediat, Antwerp, Belgium
[4] Ctr Enfermedades Hepat & Digest, Bogota, Colombia
[5] Antwerp Univ Hosp, Dept Endocrinol Diabetol Metab, Antwerp, Belgium
[6] Univ Hlth Network, Toronto Ctr Liver Dis, Toronto Gen Hosp, Toronto, ON, Canada
关键词
Liver Fibrosis; General Population; Noninvasive Test; NIT; Metabolic Dysfunction-Associated - Associated Steatotic Liver Disease; DISEASE; NAFLD; STIFFNESS; DIAGNOSIS;
D O I
10.1053/j.gastro.2024.03.017
中图分类号
R57 [消化系及腹部疾病];
学科分类号
摘要
BACKGROUND & AIMS: There is an unmet need for noninvasive tests to improve case-finding fi nding and aid primary care professionals in referring patients at high risk of liver disease. METHODS: A metabolic dysfunction-associated fibrosis (MAF-5) score was developed and externally validated in a total of 21,797 individuals with metabolic dysfunction in population-based (National Health and Nutrition Examination Survey 2017-2020, National Health and Nutrition Examination Survey III, and Rotterdam Study) and hospital-based (from Antwerp and Bogota) cohorts. Fibrosis was defined as liver stiffness >= 8.0 kPa. Diagnostic accuracy was compared with FIB-4, nonalcoholic fatty liver disease fibrosis score (NFS), LiverRisk score and steatosis-associated fibrosis estimator (SAFE). MAF-5 was externally validated with liver stiffness measurement >= 8.0 kPa, with shear-wave elastography >= 7.5 kPa, and biopsy-proven steatotic liver disease according to Metavir and Nonalcoholic Steatohepatitis Clinical Research Network scores, and was tested for prognostic performance (all-cause mortality).RESULTS: The MAF-5 score comprised waist circumference, body mass index (calculated as kg / m(2)), diabetes, aspartate aminotransferase, and platelets. With this score, 60.9% was predicted at low, 14.1% at intermediate, and 24.9% at high risk of fibrosis. The observed prevalence was 3.3%, 7.9%, and 28.1%, respectively. The area under the receiver operator curve of MAF-5 (0.81) was significantly higher than FIB-4 (0.61), and outperformed the FIB-4 among young people (negative predictive value [NPV], 99%; area under the curve [AUC], 0.86 vs NPV, 94%; AUC, 0.51) and older adults (NPV, 94%; AUC, 0.75 vs NPV, 88%; AUC, 0.55). MAF-5 showed excellent performance to detect liver stiffness measurement >= 12 kPa (AUC, 0.86 training; AUC, 0.85 validation) and good performance in detecting liver stiffness and biopsy-proven liver fibrosis among the external validation cohorts. MAF-5 score >1 was associated with increased risk of all-cause mortality in (un)adjusted models (adjusted hazard ratio, 1.59; 95% CI, 1.47-1.73). CONCLUSIONS: The MAF-5 score is a validated, age- independent, inexpensive referral tool to identify individuals at high risk of liver fi brosis and all-cause mortality in primary care populations, using simple variables.
引用
收藏
页码:357 / 367.e9
页数:20
相关论文
共 36 条
[1]  
Akinbami L.J., 2022, National Center for Health Statistics Vital Health Statis, V2, P1, DOI DOI 10.15620/CDC:115434
[2]   The NAFLD fibrosis score: A noninvasive system that identifies liver fibrosis in patients with NAFLD [J].
Angulo, Paul ;
Hui, Jason M. ;
Marchesini, Giulio ;
Bugianesi, Ellisabetta ;
George, Jacob ;
Farrell, Geoffrey C. ;
Enders, Felicity ;
Saksena, Sushma ;
Burt, Alastair D. ;
Bida, John P. ;
Lindor, Keith ;
Sanderson, Schuyler O. ;
Lenzi, Marco ;
Adams, Leon A. ;
Kench, James ;
Therneau, Terry M. ;
Day, Christopher P. .
HEPATOLOGY, 2007, 45 (04) :846-854
[3]   EASL Clinical Practice Guidelines on non-invasive tests for evaluation of liver disease severity and prognosis-2021 update [J].
Berzigotti, Annalisa ;
Tsochatzis, Emmanouil ;
Boursier, Jerome ;
Castera, Laurent ;
Cazzagon, Nora ;
Friedrich-Rust, Mireen ;
Petta, Salvatore ;
Thiele, Maja .
JOURNAL OF HEPATOLOGY, 2021, 75 (03) :659-689
[4]   Screening for therapeutic trials and treatment indication in clinical practice: MACK-3, a new blood test for the diagnosis of fibrotic NASH [J].
Boursier, J. ;
Anty, R. ;
Vonghia, L. ;
Moal, V. ;
Vanwolleghem, T. ;
Canivet, C. M. ;
Michalak, S. ;
Bonnafous, S. ;
Michielsen, P. ;
Oberti, F. ;
Iannelli, A. ;
Van Gaal, L. ;
Patouraux, S. ;
Blanchet, O. ;
Verrijken, A. ;
Gual, P. ;
Rousselet, M. -C. ;
Driessen, A. ;
Hunault, G. ;
Bertrais, S. ;
Tran, A. ;
Cales, P. ;
Francque, S. .
ALIMENTARY PHARMACOLOGY & THERAPEUTICS, 2018, 47 (10) :1387-1396
[5]   Determination of reliability criteria for liver stiffness evaluation by transient elastography [J].
Boursier, Jerome ;
Zarski, Jean-Pierre ;
de Ledinghen, Victor ;
Rousselet, Marie-Christine ;
Sturm, Nathalie ;
Lebail, Brigitte ;
Fouchard-Hubert, Isabelle ;
Gallois, Yves ;
Oberti, Frederic ;
Bertrais, Sandrine ;
Cales, Paul .
HEPATOLOGY, 2013, 57 (03) :1182-1191
[6]   Current therapies and new developments in NASH [J].
Dufour, Jean-Francois ;
Anstee, Quentin M. ;
Bugianesi, Elisabetta ;
Harrison, Stephen ;
Loomba, Rohit ;
Paradis, Valerie ;
Tilg, Herbert ;
Wong, Vincent Wai-Sun ;
Zelber-sagi, Shira .
GUT, 2022, 71 (10) :2123-2134
[7]   Noninvasive Assessment of Nonalcoholic Fatty Liver Disease in Obese or Overweight Patients [J].
Francque, Sven M. A. ;
Verrijken, An ;
Mertens, Ilse ;
Hubens, Guy ;
Van Marck, Eric ;
Pelckmans, Paul ;
Michielsen, Peter ;
Van Gaal, Luc .
CLINICAL GASTROENTEROLOGY AND HEPATOLOGY, 2012, 10 (10) :1162-1168
[8]   Low Accuracy of FIB-4 and NAFLD Fibrosis Scores for Screening for Liver Fibrosis in the Population [J].
Graupera, Isabel ;
Thiele, Maja ;
Serra-Burriel, Miquel ;
Caballeria, Llorenc ;
Roulot, Dominique ;
Wong, Grace Lai-Hung ;
Fabrellas, Nuria ;
Guha, Indra Neil ;
Arslanow, Anita ;
Exposito, Carmen ;
Hernandez, Rosario ;
Aithal, Guruprasad Padur ;
Galle, Peter R. ;
Pera, Guillem ;
Wong, Vincent Wai-Sun ;
Lammert, Frank ;
Gines, Pere ;
Castera, Laurent ;
Krag, Aleksander .
CLINICAL GASTROENTEROLOGY AND HEPATOLOGY, 2022, 20 (11) :2567-+
[9]  
Hashemi SA, 2016, CASP J INTERN MED, V7, P242
[10]   Setting up of a machine learning algorithm for the identification of severe liver fibrosis profile in the general US population cohort [J].
Hassoun, Samir ;
Bruckmann, Chiara ;
Ciardullo, Stefano ;
Perseghin, Gianluca ;
Di Gaudio, Francesca ;
Broccolo, Francesco .
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 2023, 170