MolDX: Biomarker Testing for Risk Stratification in Metabolic Dysfunction-Associated Steatotic Liver Disease and Metabolic Dysfunction-Associated Steatohepatitis

Title XVIII of the Social Security Act, §1862(a)(1)(A) allows coverage and payment for only those services that are considered to be reasonable and necessary.

42 CFR §410.32(a) Diagnostic x-ray tests, diagnostic laboratory tests, and other diagnostic tests: Conditions

CMS Internet-Only Manual, Pub. 100-02, Medicare Benefit Policy Manual, Chapter 15, §80 Requirements for Diagnostic X-Ray, Diagnostic Laboratory, and Other Diagnostic Tests, §80.1.1 Certification Changes

This policy describes coverage for molecular or proteomic biomarker tests for the diagnosis and management of liver fibrosis in the setting of metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH). In accordance with American Association for the Study of Liver Disease (AASLD) guidance,1 the term MASLD will be used as a replacement for non-alcoholic fatty liver disease (NAFLD), and MASH as a replacement for non-alcoholic steatohepatitis (NASH). As comparisons have found a near complete overlap between the recently-defined MASLD population and the historical NAFLD population,2 results from biomarker validation studies among patients with NAFLD/NASH will be considered applicable to patients with MASLD/MASH. Other types of chronic liver disease (CLD) [including but not limited to metabolic dysfunction- and alcohol-associated liver disease (MetALD), alcohol-associated liver disease (ALD), viral hepatitis and autoimmune hepatitis] are considered separate entities3 with distinct etiologies, natural histories and management, and are therefore not encompassed under this policy.

Criteria for Coverage

Molecular or proteomic biomarker testing for the assessment of risk of liver fibrosis in the setting of MASLD or MASH is considered reasonable and necessary when ALL the following criteria are met:

1. The patient is an adult with clinical suspicion or diagnosis of MASLD or MASH based on current professional society guidelines [e.g., AASLD, American Gastroenterological Association (AGA), American Association of Clinical Endocrinologists (AACE)].
2. A primary risk assessment based on non-molecular/ proteomic laboratory testing, as outlined by consensus guidelines, does not indicate low risk [e.g., fibrosis-4 index (FIB-4) ≥ 1.3].
3. Liver stiffness measurement (LSM) by imaging [e.g., vibration controlled transient elastography (VCTE), magnetic resonance elastography (MRE)] is indeterminate or not performed.
4. The results of the test will be used to directly aid in pending management decisions (e.g., referral to a specialist, performance of liver biopsy, eligibility for pharmacologic therapy) as documented in the patient’s medical record.
5. Testing is not performed more than once within a 12-month period nor within 12 months following a liver biopsy.
6. Clinical validity (CV) of any analytes or profiles must be established through a study published in the peer-reviewed literature for the intended use of the test in the intended population with demonstrated reproducibility across clinical study cohorts.
7. If the test relies on an algorithm, the algorithm must be validated in a cohort that is not a development cohort for the algorithm.
8. The test has satisfactorily completed a Technical Assessment (TA) by the Molecular Diagnostic Services Program (MolDX^®).
9. Molecular and proteomic tests utilizing a similar methodology or evaluating similar analytes as a test for which existing coverage has been established must demonstrate equivalent or superior test performance (i.e., sensitivity and/or specificity) when used for the same indication in the same intended use population. New tests that become available with significantly improved performance may render older tests no longer compliant with this policy.

Background

MASLD is a type of CLD defined by hepatic steatosis (>5 percent liver fat) in patients with at least one risk factor for cardiometabolic dysfunction (including obesity, hyperglycemia / type 2 diabetes mellitus (T2D), hypertension, and dyslipidemia). MASLD is commonly asymptomatic, and the natural history of the disease is usually fairly indolent with the majority of patients taking years or even decades to progress. The more severe form of disease, MASH, is diagnosed when histological evidence of inflammation and hepatocellular injury are present in addition to steatosis. As liver scarring accumulates, MASH may evolve to cirrhosis, which occurs more frequently in in those with T2D or prediabetes, morbid obesity, or more than one cardiometabolic risk factor.^4,5 Advancing stages of fibrosis are associated with poor liver-related outcomes (e.g., hepatocellular carcinoma (HCC), liver decompensation, need for transplantation) as well as increased all-cause mortality.⁶ A meta-analysis of 1,495 subjects with 17,452 patient years of follow-up showed exponential increases in the liver-related mortality rate with each histologic stage of ?brosis.⁶ Therefore, accurate stratification for risk of fibrosis is one of the primary objectives in patient evaluation.

Mirroring the obesity epidemic, the burden of MASLD has been increasing worldwide, with a rise of nearly 50% in the global prevalence over the past three decades.⁷ Estimates of the prevalence of MASLD in the United States vary from 35 - 48%, with the highest rates among those of Hispanic origin.⁸ A recent study of patients with T2D in the US outpatient setting showed that ~70% have MASLD and approximately 15% have stage ≥2 fibrosis.⁹ Among North American patients with MASLD, ~30% of those without an indication for liver biopsy were reported to have MASH; the proportion with MASH rose to 60% in the presence of an indication for biopsy.⁵ MASH recently overtook Hepatitis C virus (HCV) as the leading etiology among US liver transplant patients with HCC, and remained second only to ALD in those without HCC.¹⁰ In 2021-2022, MASH was the primary listing diagnosis for 6,299 liver transplant patients, compared to 10,011 with ALD and only 1,793 with HCV.¹⁰

Historically, lifestyle modifications with diet and exercise have been the mainstay of therapeutic recommendations, with limited pharmacologic interventions available outside of the setting of T2D.^11,12 However, in March of 2024, the Food and Drug Administration (FDA) approved resmetirom as the first pharmacotherapy for the treatment of adults with MASH with moderate to advanced (stages F2-F3) liver fibrosis on the basis of the randomized double-blind MAESTRO trial, which demonstrated significant improvement or resolution of liver scarring in patients receiving resmetirom compared to placebo.¹³ The FDA-approved drug label for resmetirom does not require liver biopsy to confirm advanced fibrosis.¹⁴ Additional agents are under active investigation.¹⁵

Evaluation of liver fibrosis

Liver biopsy has traditionally been considered the gold standard for evaluation of fibrosis, which is typically staged histologically on a scale ranging from F0 (no fibrosis) to F4 (cirrhosis). However, biopsy has several drawbacks. In addition to being an invasive procedure with the potential for associated complications such as pain and bleeding,¹⁶ the small size of the needle core relative to the liver can result in sampling error,^17,18 and studies have demonstrated high inter-observer variability in pathologist reads.¹⁸ It is acknowledged by the provider community that liver biopsies are in fact not consistently performed in clinical practice.^{19, 20}

The AASLD,¹⁹ AGA,²¹ AACE²² and American Diabetes Association (ADA)²³ currently recommend a sequential approach to MASLD evaluation and risk assessment, with a primary rule-out assessment using FIB-4 to filter out patients at low risk for advanced fibrosis, followed by secondary assessment of the remaining intermediate- to high-risk patients with VCTE (an imaging-based assessment of fibrosis) or the Enhanced Liver Fibrosis (ELF) blood test. [The ELF test is also endorsed by the United Kingdom’s National Institute for Health and Care Excellence (NICE) for assessment for advanced liver fibrosis in people with MASLD.²⁴] A repeat assessment cycle beginning with clinical evaluation and standard laboratory testing (e.g., FIB-4) may be considered every 1-2 years or 2-3 years depending on patient risk^19,21 due to the slowly-progressive nature of the disease.²⁵ The AASLD also issued a practice guidance update regarding selection of patients for prescription of resmetirom which favors the use of imaging but allows that blood-based testing may be utilized, and further notes that MAESTRO trial participants (all of whom had biopsy-proven F2-F3 fibrosis) had an ELF interquartile range of 9.2-10.4.²⁶ While there are currently no defined thresholds by which to measure drug response, the AASLD recommends reassessment at 12 months with the same imaging- or blood-based modality that was used to determine treatment eligibility.²⁶

The FIB-4 score, the first step in the guidelines’ evaluation cascade, is a calculation based on the patient’s age and readily available chemistry and hematology lab values according to the formula FIB-4 = (age × AST) / (platelet count × √ALT). In a comparison with seven other serum-based tests that utilize standard laboratory markers to predict F3-F4 fibrosis, the FIB-4’s area under the receiver-operating characteristic (AUROC) curve of 0.802 outperformed those of the NAFLD fibrosis score (NFS), Goteburg University Cirrhosis Index (GUCI), AST:ALT ratio, AST:platelet ratio index (APRI), AST:platelet ratio, body mass index (BMI) AST:ALT diabetes (BARD) score, and cirrhosis discriminant score (CDS), which ranged from 0.666 to 0.758.²⁷ In a population of 541 confirmed MASLD patients (59% with MASH and advanced fibrosis prevalence of 23%), this study also showed that using FIB-4 values of ≤1.30 and ≥2.67 for the absence and presence of advanced fibrosis, respectively, had sensitivity of 0.74 with negative predictive value (NPV) of 90% and specificity of 0.98 with positive predictive value (PPV) of 80%.²⁷ However, the proportion of FIB-4 scores falling in the indeterminate range has been reported to be as high as ~30%.²⁸ Furthermore, due to the influence of age on the score, the FIB-4 test has been shown to have lower specificity in patients over 65 years old.^29,30 

After FIB-4, LSM is one option for the second step in the guidelines’ flowchart. VCTE, the most common technique by which to derive LSM, may be performed at the point of care but requires specialized equipment not typically found in primary care offices as well as experienced trained personnel that may not be available in all practice settings; >500 exams are generally needed to obtain competency.²⁸ In addition, VCTE has a substantial failure rate (over 20%) in patients with severe (BMI ≥30) and morbid (BMI ≥40) obesity.³¹ Further confounding variables that affect VCTE accuracy include significant steatosis, inflammation, necrosis, cholestasis, venous congestion, and recent meal ingestion.^31,32 Other imaging modalities, such as sound wave elastography (SWE) or magnetic resonance elastography (MRE), are sometimes offered but are overall less well characterized, and can similarly be limited by availability (particularly of bariatric MRE facilities) and high resource utilization. 

The blood-based alternative to VCTE mentioned in guidelines as a follow-up to indeterminate/high FIB-4 is the ELF test, which is based on the combined quantitative measurements of hyaluronic acid, amino-terminal propeptide of type III procollagen, and tissue inhibitor of matrix metalloproteinase 1. The ELF test has FDA approval for use in MASH patients with advanced fibrosis (F3 or F4) to assess the likelihood of progression to cirrhosis and liver-related clinical events.³³ Although not FDA-authorized for other indications, the ELF test has been extensively investigated for detecting advanced fibrosis in MASLD. However, the literature is complicated by the use of different formulas and thresholds. In a meta-analysis of 11 studies of the ELF test, the scoring systems were standardized and a multiple thresholds model was applied to generate a summary receiver-operating characteristic (SROC) curve, which showed an area under the curve (AUC) of 0.83 (95% CI 0.71–0.90) for detecting advanced fibrosis compared to biopsy.³⁴ Using the guideline-recommended lower threshold of 7.7 and upper threshold of 9.8, the ELF test had a sensitivity of 0.93 for excluding fibrosis and specificity of 0.86 for advanced fibrosis; at a disease prevalence of 50%, NPV is 83% and PPV is 82%.³⁴ Therefore, the authors suggested that the ELF test is better suited for higher-prevalence settings,³⁴ such as would be seen in a pre-selected cohort with FIB-4 ≥1.3.

In a comparison of ELF to liver stiffness measurement (LSM) by FibroScan® (an FDA-approved VCTE system) for the prediction of liver fibrosis in patients with biopsy-confirmed MASLD, no significant difference was found in the AUROC curves (ELF=0.812 and LSM=0.839).³⁵ A retrospective, cross-sectional study of 829 patients (462 with transient elastography data and 463 with liver biopsy data), showed that a significant increase in ELF score was correlated with advanced fibrosis.³⁶ The AUROC for ELF for identifying fibrosis was 0.81 (95% CI, 0.77 to 0.85) with biopsy as the standard and 0.79 (95% CI, 0.75 to 0.82) with transient elastography as the reference. 

Other currently available tests related to MASLD include NASH Fibro-Test / NASH FibroSure and FibroSpect, which originated for use in the setting of Hepatitis C, and LiverFASt. NASH Fibro-Test / FibroSure has been better studied for its ability to predict steatosis³⁷ or steatohepatitis³⁸ than fibrosis.³⁹ In a single retrospective study, FibroSpect had a higher AUROC than FIB-4 and NFS, but the latter values were lower than expected based on other studies.⁴⁰ Similarly, while data on LiverFASt have been presented at conferences, peer-reviewed publications are scarce.⁴¹

“At risk” MASH

In addition to the identification of patients with advanced fibrosis, an area of active interest is the detection of “at-risk” MASH, defined as steatohepatitis with an NAFLD activity score (a semi-quantitative measurement of histology injury that takes into account steatosis, hepatocyte ballooning and inflammation) of 4 or greater and fibrosis stage of at least 2. Current AASLD guidelines note that “serum and plasma-based lipidomic, metabolomic, and proteomic biomarkers are in development for ‘at-risk’ [M]ASH” but “have not reached the level of clinical evidence needed for use in routine clinical practice.”¹⁹

Another patented test with algorithm is the NIS4, which combines measurements of alpha-2 macroglobulin, miR-34a-5p, YKL-40 and hemoglobin A1c (HbA1c). In one study reporting results from two independent cohorts, the NIS4 was similar to VCTE (AUROCs 0.76 and 0.75, respectively) and better than ELF (AUROCs 0.83 and 0.77, respectively) and FIB-4 (AUROCs 0.80 and 0.74, respectively) at identifying at-risk MASH.⁴² The NIS2+, an optimization of the NIS4, removes alpha-2 macroglobulin and HbA1c from the NIS4 equation and adds sex-corrections (both independent and for miR-34a-5p), resulting in altered threshold values. The NIS2+ was statistically better than the NIS4 (AUROC 0.813 vs. 0.792, respectively) at categorizing at-risk MASH in patients being vetted for the RESOLVE-IT trial for the safety and efficacy of elafibranor treatment.⁴³ In a study dedicated to demonstrating performance in the Medicare-aged population, NIS4 and NIS2+ had similar results for the detection of at-risk MASH in subjects <65 years (.084 sensitivity for both at the low cutoffs, and specificities of 0.844 and 0.855 respectively at the high cutoffs) while NIS2+ had better specificity in those >65 years (0.677 vs. 0.811 at high thresholds, respectively); both tests outperformed FIB-4, NFS and ELF for this indication.⁴⁴ The AGA states that the NIS2+ is validated for the detection of at-risk MASH.²¹  

Another test developed for flagging at-risk MASH is the metabolomics advanced steatohepatitis fibrosis score (MASEF), which is based on 12 lipids, BMI, AST, and ALT. In a validation cohort of over 500 patients, the MASEF score had an AUROC of 0.79 (95% CI 0.75–0.83) for predicting at-risk MASH, with a sensitivity of 78%, specificity of 65%, PPV of 48%, and NPV of 88%. In addition, there was a non-significant difference between FIB-4 + MASEF and FIB-4 + LSM by VCTE.⁴⁵

The Foundation for the National Institutes of Health (FNIH) - Non-invasive Biomarkers of Metabolic Liver Disease (NIMBLE) consortium is a public-private partnership collaboration which aims to support regulatory approval of MASH-related biomarkers. In stage one of their efforts, FNIH NIMBLE prespecified successful performance metrics as an AUROC ≥0.7, superiority over ALT for disease activity, and superiority over the FIB-4 test for fibrosis severity. The fully blood-based panels prioritized for initial study were NIS4, OWLiver (which includes MASEF), ELF and PROC3. In an observational cohort of over 1000 patients representing the full spectrum of MASLD, the ELF and NIS4 tests met AUROC requirements; NIS4 outperformed ALT for activity score and ELF outperformed FIB-4 for all fibrosis endpoints when using the Youden cutpoint as well as when constraining to 90% sensitivity and 90% specificity.⁴⁶ OWLiver could not be fully evaluated due to the categorical nature of the results. In the next stage of the project, these tests will be advanced for further testing in patients with clinical risk factors in more specific intended use populations. The authors also note that this overarching framework can be applied to other promising tests in development, including combinatorial approaches that integrate imaging and blood measurements.⁴⁶

Given the population abundance of MASLD and the shortcomings of biopsy, it would be impractical and infeasible to rely on liver biopsy as a first-line means of risk stratification. Having such a flawed gold standard also makes interpretation of competing assays challenging. Simple blood-based tests that are widely accessible serve as an efficient, economical rule-out to exclude a need for further workup. In particular, the FIB-4 has demonstrated superior performance to other scoring systems, as well as an acceptable NPV of 90% for ruling out advanced fibrosis at a known prevalence of 23%,²⁷ which is higher than would be expected in an unselected population of unconfirmed MASLD, noting also that NPV would increase at lower prevalences. However, the large indeterminate zone and age bias preclude the application of FIB-4 as a standalone. The lower specificity in ages ≥65 is particularly relevant to the Medicare population as common comorbidities may make these patients poor candidates for invasive procedures. Therefore, this contractor will consider reasonable and necessary the further stratification of residual patients not eliminated by low FIB-4 to determine who would derive the greatest benefit from more labor- and resource-intensive measures. This approach also improves the PPV of the second-line test by enriching the outcome of interest (i.e., fibrosis) compared to the baseline population. While LSM by imaging (including VCTE as well as SWE and MRE) can be appropriate based on test performance metrics under ideal conditions, the lack of uniform availability makes this an inequitable solution. Furthermore, the unreliability in the setting of severe/morbid obesity (as well as factors such as congestion and cholestasis) prevents suitability of LSM by imaging for much of the MASLD population. In contrast, newer, more complex blood tests may not be bound by such demographic constraints and may be more widely obtainable through standard phlebotomy services. Evidentiary review reveals that some blood-based tests have already shown at least non-inferiority, if not superiority, to current standards of care. For the detection of fibrosis, the ELF test has demonstrated the capability to improve upon FIB-4 (AUROCs of 0.828 vs. 0.798 for F≥2, 0.835 vs. 0.789 for F≥3 and 0.855 vs. 0.810 for F4, respectively)⁴⁶ as well as approximate LSM by multiple VCTE systems (e.g., FibroScan³⁵ and FibroMeter⁴⁶). While not as effective at assessing degree of fibrosis, the NIS4 is more attuned to identifying at-risk MASH (AUROC 0.815 for NIS4 vs. 0.704 for FIB-4 and 0.726 for ALT)⁴⁶; while similar in the <65-year-old population, the NIS2+ has improved specificity of 0.811 in those >65 compared to 0.677 for NIS4.⁴⁴ Research and development remain ongoing and it is expected that additional evidence will be accumulated in the near future.⁴⁶

In summary, MASLD represents a significant public health burden applicable to the Medicare population that is often not adequately addressed by reliance on basic laboratory testing formulas, imaging techniques, and liver biopsy. The clinical utility of accurate stratification for risk of fibrosis has been broadly accepted by the hepatology community, and non-invasive assessment of disease through the use of blood-based testing is increasingly incorporated into best practices. This contractor will provide coverage for molecular or proteomic tests which fulfill all criteria outlined in this policy based on the evaluation of pertinent peer-reviewed scientific literature as well as professional society and nationally recognized guidelines; the reference to any specific biomarkers in this document does not imply coverage.

N/A

N/A

1. Kanwal F, Neuschwander-Tetri BA, Loomba R, Rinella ME. Metabolic dysfunction-associated steatotic liver disease: update and impact of new nomenclature on the American Association for the Study of Liver Diseases practice guidance on nonalcoholic fatty liver disease. Hepatology. 2024;79(5):1212-1219. doi:10.1097/HEP.0000000000000670

2. Younossi ZM, Paik JM, Stepanova M, Ong J, Alqahtani S, Henry L. Clinical profiles and mortality rates are similar for metabolic dysfunction-associated steatotic liver disease and non-alcoholic fatty liver disease. J Hepatol. 2024;80(5):694-701. doi:10.1016/j.jhep.2024.01.014

3. Rinella ME, Lazarus JV, Ratziu V, et al. A multisociety Delphi consensus statement on new fatty liver disease nomenclature. Ann Hepatol. 2024;29(1):101133. doi:10.1016/j.aohep.2023.101133

4. Jinjuvadia R, Antaki F, Lohia P, Liangpunsakul S. The association between nonalcoholic fatty liver disease and metabolic abnormalities in the United States population. J Clin Gastroenterol. 2017;51(2):160-166. doi:10.1097/MCG.0000000000000666

5. Younossi ZM, Koenig AB, Abdelatif D, Fazel Y, Henry L, Wymer M. Global epidemiology of nonalcoholic fatty liver disease-meta-analytic assessment of prevalence, incidence, and outcomes. Hepatology. 2016;64(1):73-84. doi:10.1002/hep.28431

6. Dulai PS, Singh S, Patel J, et al. Increased risk of mortality by fibrosis stage in nonalcoholic fatty liver disease: systematic review and meta-analysis. Hepatology. 2017;65(5):1557-1565. doi:10.1002/hep.29085

7. Miao L, Targher G, Byrne CD, Cao YY, Zheng MH. Current status and future trends of the global burden of MASLD. Trends Endocrinol Metab. 2024;35(8):697-707. doi:10.1016/j.tem.2024.02.007

8. Teng ML, Ng CH, Huang DQ, et al. Global incidence and prevalence of nonalcoholic fatty liver disease. Clin Mol Hepatol. 2023;29(Suppl):S32-S42. doi:10.3350/cmh.2022.0365

9. Lomonaco R, Godinez Leiva E, Bril F, et al. Advanced liver fibrosis is common in patients with type 2 diabetes followed in the outpatient setting: the need for systematic screening. Diabetes Care. 2021;44(2):399-406. doi:10.2337/dc20-1997

10. Younossi ZM, Stepanova M, Al Shabeeb R, et al. The changing epidemiology of adult liver transplantation in the United States in 2013-2022: the dominance of metabolic dysfunction-associated steatotic liver disease and alcohol-associated liver disease. Hepatol Commun. 2023;8(1):e0352. doi:10.1097/HC9.0000000000000352

11. Belfort R, Harrison SA, Brown K, et al. A placebo-controlled trial of pioglitazone in subjects with nonalcoholic steatohepatitis. N Engl J Med. 2006;355(22):2297-2307. doi:10.1056/NEJMoa060326

12. Cusi K, Orsak B, Bril F, et al. Long-term pioglitazone treatment for patients with nonalcoholic steatohepatitis and prediabetes or type 2 diabetes mellitus: a randomized trial. Ann Intern Med. 2016;165(5):305-315. doi:10.7326/M15-1774

13. Harrison SA, Bedossa P, Guy CD, et al. A phase 3, randomized, controlled trial of resmetirom in NASH with liver fibrosis. N Engl J Med. 2024;390(6):497-509. doi:10.1056/NEJMoa2309000

14. U.S. Food and Drug Administration (FDA). Rezdiffra Prescribing Information. Accessed 4/29/2025.

15. Ciardullo S, Muraca E, Vergani M, Invernizzi P, Perseghin G. Advancements in pharmacological treatment of NAFLD/MASLD: a focus on metabolic and liver-targeted interventions. Gastroenterol Rep (Oxf). 2024;12:goae029. doi:10.1093/gastro/goae029

16. Janes CH, Lindor KD. Outcome of patients hospitalized for complications after outpatient liver biopsy. Ann Intern Med. 1993;118(2):96-98. doi:10.7326/0003-4819-118-2-199301150-00003

17. Poynard T, Lenaour G, Vaillant JC, et al. Liver biopsy analysis has a low level of performance for diagnosis of intermediate stages of fibrosis. Clin Gastroenterol Hepatol. 2012;10(6):657-63.e7. doi:10.1016/j.cgh.2012.01.023

18. Ratziu V, Charlotte F, Heurtier A, et al. Sampling variability of liver biopsy in nonalcoholic fatty liver disease. Gastroenterology. 2005;128(7):1898-1906. doi:10.1053/j.gastro.2005.03.084

19. Rinella ME, Neuschwander-Tetri BA, Siddiqui MS, et al. AASLD practice guidance on the clinical assessment and management of nonalcoholic fatty liver disease. Hepatology. 2023;77(5):1797-1835. doi:10.1097/HEP.0000000000000323

20. Rinella ME, Lominadze Z, Loomba R, et al. Practice patterns in NAFLD and NASH: real life differs from published guidelines. Therap Adv Gastroenterol. 2016;9(1):4-12. doi:10.1177/1756283X15611581

21. Wattacheril JJ, Abdelmalek MF, Lim JK, Sanyal AJ. AGA clinical practice update on the role of noninvasive biomarkers in the evaluation and management of nonalcoholic fatty liver disease: expert review. Gastroenterology. 2023;165(4):1080-1088. doi:10.1053/j.gastro.2023.06.013

22. Cusi K, Isaacs S, Barb D, et al. American Association of Clinical Endocrinology clinical practice guideline for the diagnosis and management of nonalcoholic fatty liver disease in primary care and Endocrinology Clinical Settings: co-Sponsored by the American Association for the Study of Liver Diseases (AASLD). Endocr Pract. 2022;28(5):528-562. doi:10.1016/j.eprac.2022.03.010

23. ElSayed NA, Aleppo G, Aroda VR, et al. 4. Comprehensive medical evaluation and assessment of comorbidities: standards of care in diabetes-2023 [published correction appears in Diabetes Care. 2023 Sep 1;46(9):1722. doi: 10.2337/dc23-er09a.] [published correction appears in Diabetes Care. 2023 Sep 01;46(9):1718-1720. doi: 10.2337/dc23-ad09.]. Diabetes Care. 2023;46(Suppl 1):S49-S67. doi:10.2337/dc23-S004

24. Glen J, Floros L, Day C, Pryke R; Guideline Development Group. Non-alcoholic fatty liver disease (NAFLD): summary of NICE guidance. BMJ. 2016;354(i4428). doi:10.1136/bmj.i4428

25. National Guideline Centre (UK). Non-Alcoholic Fatty Liver Disease: Assessment and Management. London: National Institute for Health and Care Excellence (NICE); July 2016.

26. Chen VL, Morgan TR, Rotman Y, et al. Resmetirom therapy for metabolic dysfunction-associated steatotic liver disease: October 2024 updates to AASLD Practice Guidance. Hepatology. 2025;81(1):312-320. doi:10.1097/HEP.0000000000001112

27. Shah AG, Lydecker A, Murray K, et al. Comparison of noninvasive markers of fibrosis in patients with nonalcoholic fatty liver disease. Clin Gastroenterol Hepatol. 2009;7(10):1104-1112. doi:10.1016/j.cgh.2009.05.033

28. Patel K, Sebastiani G. Limitations of non-invasive tests for assessment of liver fibrosis. JHEP Rep. 2020;2(2):100067. doi:10.1016/j.jhepr.2020.100067

29. van Kleef LA, Sonneveld MJ, de Man RA, de Knegt RJ. Poor performance of FIB-4 in elderly individuals at risk for chronic liver disease - implications for the clinical utility of the EASL NIT guideline. J Hepatol. 2022;76(1):245-246. doi:10.1016/j.jhep.2021.08.017

30. McPherson S, Hardy T, Dufour JF, et al. Age as a confounding factor for the accurate non-invasive diagnosis of advanced NAFLD fibrosis. Am J Gastroenterol. 2017;112(5):740-751. doi:10.1038/ajg.2016.453

31. Tapper EB, Castera L, Afdhal NH. FibroScan (vibration-controlled transient elastography): where does it stand in the United States practice. Clin Gastroenterol Hepatol. 2015;13(1):27-36. doi:10.1016/j.cgh.2014.04.039

32. Fang JM, Cheng J, Chang MF, Ahn J, Westerhoff M. Transient elastography versus liver biopsy: discordance in evaluations for fibrosis and steatosis from a pathology standpoint. Mod Pathol. 2021;34(10):1955-1962. doi:10.1038/s41379-021-00851-5

33. EVALUATION OF AUTOMATIC CLASS III DESIGNATION FOR ADVIA Centaur Enhanced Liver Fibrosis (ELF) DECISION MEMORANDUM (2021). https://www.accessdata.fda.gov/cdrh_docs/reviews/DEN190056.pdf. Accessed 4/29/2025.

34. Vali Y, Lee J, Boursier J, et al. Enhanced liver fibrosis test for the non-invasive diagnosis of fibrosis in patients with NAFLD: a systematic review and meta-analysis. J Hepatol. 2020;73(2):252-262. doi:10.1016/j.jhep.2020.03.036

35. Inadomi C, Takahashi H, Ogawa Y, et al. Accuracy of the enhanced liver fibrosis test, and combination of the enhanced liver fibrosis and non-invasive tests for the diagnosis of advanced liver fibrosis in patients with non-alcoholic fatty liver disease. Hepatol Res. 2020;50(6):682-692. doi:10.1111/hepr.13495

36. Younossi ZM, Felix S, Jeffers T, et al. Performance of the enhanced liver fibrosis test to estimate advanced fibrosis among patients with nonalcoholic fatty liver disease. JAMA Netw Open. 2021;4(9):e2123923. doi:10.1001/jamanetworkopen.2021.23923

37. Poynard T, Peta V, Munteanu M, et al. The diagnostic performance of a simplified blood test (SteatoTest-2) for the prediction of liver steatosis. Eur J Gastroenterol Hepatol. 2019;31(3):393-402. doi:10.1097/MEG.0000000000001304

38. Poynard T, Munteanu M, Charlotte F, et al. Diagnostic performance of a new noninvasive test for nonalcoholic steatohepatitis using a simplified histological reference. Eur J Gastroenterol Hepatol. 2018;30(5):569-577. doi:10.1097/MEG.0000000000001064

39. Ratziu V, Massard J, Charlotte F, et al. Diagnostic value of biochemical markers (FibroTest-FibroSURE) for the prediction of liver fibrosis in patients with non-alcoholic fatty liver disease. BMC Gastroenterol. 2006;6:6. doi:10.1186/1471-230X-6-6

40. Decraecker M, Dutartre D, Hiriart JB, et al. Long-term prognosis of patients with metabolic (dysfunction)-associated fatty liver disease by non-invasive methods. Aliment Pharmacol Ther. 2022;55(5):580-592. doi:10.1111/apt.16760

41. Loomba R, Jain A, Diehl AM, et al. Validation of serum test for advanced liver fibrosis in patients with nonalcoholic steatohepatitis. Clin Gastroenterol Hepatol. 2019;17(9):1867-1876.e3. doi:10.1016/j.cgh.2018.11.004

42. Harrison SA, Ratziu V, Boursier J, et al. A blood-based biomarker panel (NIS4) for non-invasive diagnosis of non-alcoholic steatohepatitis and liver fibrosis: a prospective derivation and global validation study. Lancet Gastroenterol Hepatol. 2020;5(11):970-985. doi:10.1016/S2468-1253(20)30252-1

43. Harrison SA, Ratziu V, Magnanensi J, et al. NIS2+, an optimisation of the blood-based biomarker NIS4; technology for the detection of at-risk NASH: a prospective derivation and validation study. J Hepatol. 2023;79(3):758-767. doi:10.1016/j.jhep.2023.04.031

44. Sanyal AJ, Magnanensi J, Majd Z, et al. NIS2+™, an effective blood-based test for the diagnosis of at-risk nonalcoholic steatohepatitis in adults 65 years and older. Hepatol Commun. 2023;7(9):e0223. doi:10.1097/HC9.0000000000000223

45. Noureddin M, Truong E, Mayo R, et al. Serum identification of at-risk MASH: the metabolomics-advanced steatohepatitis fibrosis score (MASEF). Hepatology. 2024;79(1):135-148. doi:10.1097/HEP.0000000000000542

46. Sanyal AJ, Shankar SS, Yates KP, et al. Diagnostic performance of circulating biomarkers for non-alcoholic steatohepatitis. Nat Med. 2023;29(10):2656-2664. doi:10.1038/s41591-023-02539-6

• Provider Education/Guidance

• MASLD
• MASH
• Metabolic Dysfunction-Associated Steatotic Liver Disease
• Metabolic Dysfunction-Associated Steatohepatitis