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- Hegmar, Hannes, et al.
(author)
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Performance of novel collagen turnover biomarkers to detect increased liver stiffness in MASLD
- 2024
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In: Journal of Internal Medicine. - : Wiley-Blackwell. - 0954-6820 .- 1365-2796. ; 296:2, s. 177-186
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Journal article (peer-reviewed)abstract
- BACKGROUND: Cleavage products from collagen formation and degradation hold potential as first-line biomarkers for the risk of advanced fibrosis in patients with metabolic dysfunction-associated steatotic liver disease (MASLD). Here, we evaluated the performance of PRO-C3, PRO-C6, C4M, PRO-C18L, and the clinical score ADAPT (age, diabetes, PRO-C3, and platelet count) to detect patients with an LSM >8 kPa or >12 kPa in comparison to the Fibrosis-4 Index (FIB-4).METHODS: Serum from patients with MASLD (n = 269) from six Swedish University Hospitals was analyzed using enzyme-linked immunosorbent assay-based methods. Liver stiffness measurement (LSM) by vibration-controlled transient elastography was performed. The area under the curve (AUC), calibration curves, and net benefit analysis were used.RESULTS: An LSM >8 kPa was found in 108 (40.1%) patients. PRO-C3, PRO-C6, C4M, and PRO-C18L had AUCs ranging from 0.48 to 0.62. ADAPT had the highest AUC (0.73, 95% confidence interval [CI] = 0.67-0.79) to detect patients >8 kPa, compared to FIB-4 (0.71, (95%CI = 0.64-0.77, p = 0.35), and had a higher net benefit compared to FIB-4 from a probability threshold of 15%. FIB-4 and ADAPT performed equally well to detect patients with an LSM >12 kPa, AUC 0.76 versus 0.76, p = 0.93.CONCLUSIONS: ADAPT seems to be marginally better than FIB-4 in identifying patients with an LSM >8 kPa. However, the clinical utility of ADAPT as a first line test is uncertain, especially in low-risk populations. The overall performance of FIB-4 was similar to that of ADAPT in detecting patients with an LSM of >12 kPa. Altogether, the results suggest that ADAPT might be useful to detect earlier stages of fibrosis in MASLD, but that FIB-4 remains a first-line test for advanced fibrosis.
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- Lee, Jenny, et al.
(author)
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Machine learning algorithm improves the detection of NASH (NAS-based) and at-risk NASH: A development and validation study
- 2023
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In: Hepatology. - : LIPPINCOTT WILLIAMS & WILKINS. - 0270-9139 .- 1527-3350. ; 78:1, s. 258-271
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Journal article (peer-reviewed)abstract
- Background and Aims: Detecting NASH remains challenging, while at-risk NASH (steatohepatitis and F >= 2) tends to progress and is of interest for drug development and clinical application. We developed prediction models by supervised machine learning techniques, with clinical data and biomarkers to stage and grade patients with NAFLD. Approach and Results: Learning data were collected in the Liver Investigation: Testing Marker Utility in Steatohepatitis metacohort (966 biopsy-proven NAFLD adults), staged and graded according to NASH CRN. Conditions of interest were the clinical trial definition of NASH (NAS >= 4;53%), at-risk NASH (NASH with F >= 2;35%), significant (F >= 2;47%), and advanced fibrosis (F >= 3;28%). Thirty-five predictors were included. Missing data were handled by multiple imputations. Data were randomly split into training/validation (75/25) sets. A gradient boosting machine was applied to develop 2 models for each condition: clinical versus extended (clinical and biomarkers). Two variants of the NASH and at-risk NASH models were constructed: direct and composite models.Clinical gradient boosting machine models for steatosis/inflammation/ballooning had AUCs of 0.94/0.79/0.72. There were no improvements when biomarkers were included. The direct NASH model produced AUCs (clinical/extended) of 0.61/0.65. The composite NASH model performed significantly better (0.71) for both variants. The composite at-risk NASH model had an AUC of 0.83 (clinical and extended), an improvement over the direct model. Significant fibrosis models had AUCs (clinical/extended) of 0.76/0.78. The extended advanced fibrosis model (0.86) performed significantly better than the clinical version (0.82). Conclusions: Detection of NASH and at-risk NASH can be improved by constructing independent machine learning models for each component, using only clinical predictors. Adding biomarkers only improved the accuracy of fibrosis.
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- Nielsen, Signe Holm, et al.
(author)
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Markers of basement membrane remodeling are associated with higher mortality in patients with known atherosclerosis
- 2018
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In: Journal of the American Heart Association. - 2047-9980. ; 7:21
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Journal article (peer-reviewed)abstract
- Background-Patients with atherosclerosis have a high risk of cardiovascular events and death. Atherosclerosis is characterized by accumulation of lipids, cells and extracellular matrix proteins in the intima. We hypothesized that dysregulated remodeling of the basement membrane proteins may be associated with clinical outcomes in patients with atherosclerosis. Methods and Results-Neoepitope fragments of collagen type IV (C4M) and laminin (LG1M) were assessed by ELISAs in serum from 787 endarterectomy patients. Matrix metalloproteinases were measured using proximity extension assay and correlated to C4M and LG1M levels using Spearman correlations. A total of 473 patients were followed up for 6 years using national registers, medical charts, and telephone interviews. The incidence of cardiovascular events, cardiovascular mortality, and all-cause mortality were associated to levels of C4M and LG1M using Kaplan–Meier curves and Cox regression analyses. A total of 101 patients had cardiovascular events, 39 died of cardiovascular mortality, and 64 patients died from all-cause mortality. C4M levels were increased in patients with symptomatic carotid atherosclerotic disease before surgery (P=0.048). High C4M and LG1M levels were associated with increased risk of all-cause mortality (P=0.020 and 0.031, respectively) and predicted all-cause death together with glomerular filtration rate and diabetes mellitus. Conclusions-High LG1M and C4M levels were associated with all-cause mortality, together with glomerular filtration rate and diabetes mellitus. These novel biomarkers need further evaluation but might be tools to identify high-risk patients.
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- Qadri, Sami, et al.
(author)
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Obesity Modifies the Performance of Fibrosis Biomarkers in Nonalcoholic Fatty Liver Disease
- 2022
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In: Journal of Clinical Endocrinology and Metabolism. - : Oxford University Press. - 0021-972X .- 1945-7197. ; 107:5, s. e2008-e2020
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Journal article (peer-reviewed)abstract
- Context: Guidelines recommend blood-based fibrosis biomarkers to identify advanced nonalcoholic fatty liver disease (NAFLD), which is particularly prevalent in patients with obesity. Objective: To study whether the degree of obesity affects the performance of liver fibrosis biomarkers in NAFLD. Design: Cross-sectional cohort study comparing simple fibrosis scores [Fibrosis-4 Index (FIB-4); NAFLD Fibrosis Score (NFS); aspartate aminotransferase to platelet ratio index; BARD (body mass index, aspartate-to-alanine aminotransferase ratio, diabetes); Hepamet Fibrosis Score (HFS)] and newer scores incorporating neo-epitope biomarkers PRO-C3 (ADAPT, FIBC3) or cytokeratin 18 (MACK-3). Setting: Tertiary referral center. Patients: We recruited overweight/obese patients from endocrinology (n = 307) and hepatology (n = 71) clinics undergoing a liver biopsy [median body mass index (BMI) 40.3 (interquartile range 36.0-44.7) kg/m(2)]. Additionally, we studied 859 less obese patients with biopsy-proven NAFLD to derive BMI-adjusted cutoffs for NFS. Main Outcome Measures: Biomarker area under the receiver operating characteristic (AUROC), sensitivity, specificity, and predictive values to identify histological stage >= F3 fibrosis or nonalcoholic steatohepatitis with >= F2 fibrosis [fibrotic nonalcoholic steatohepatitis (NASH)]. Results: The scores with an AUROC >= 0.85 to identify >= F3 fibrosis were ADAPT, FIB-4, FIBC3, and HFS. For fibrotic NASH, the best predictors were MACK-3 and ADAPT. The specificities of NFS, BARD, and FIBC3 deteriorated as a function of BMI. We derived and validated new cutoffs for NFS to rule in/out >= F3 fibrosis in groups with BM Is <30.0, 30.0 to 39.9, and >= 40.0 kg/m(2). This optimized its performance at all levels of BMI. Sequentially combining FIB-4 with ADAPT or FIBC3 increased specificity to diagnose >= F3 fibrosis. Conclusions: In obese patients, the best-performing fibrosis biomarkers are ADAPT and the inexpensive FIB-4, which are unaffected by BMI. The widely used NFS loses specificity in obese individuals, which may be corrected with BMI-adjusted cutoffs.
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- Vali, Yasaman, et al.
(author)
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Biomarkers for staging fibrosis and non-alcoholic steatohepatitis in non-alcoholic fatty liver disease (the LITMUS project) : a comparative diagnostic accuracy study
- 2023
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In: The Lancet Gastroenterology & Hepatology. - : Elsevier Ltd. - 2468-1253. ; 8:8, s. 714-725
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Journal article (peer-reviewed)abstract
- Background: The reference standard for detecting non-alcoholic steatohepatitis (NASH) and staging fibrosis—liver biopsy—is invasive and resource intensive. Non-invasive biomarkers are urgently needed, but few studies have compared these biomarkers in a single cohort. As part of the Liver Investigation: Testing Marker Utility in Steatohepatitis (LITMUS) project, we aimed to evaluate the diagnostic accuracy of 17 biomarkers and multimarker scores in detecting NASH and clinically significant fibrosis in patients with non-alcoholic fatty liver disease (NAFLD) and identify their optimal cutoffs as screening tests in clinical trial recruitment. Methods: This was a comparative diagnostic accuracy study in people with biopsy-confirmed NAFLD from 13 countries across Europe, recruited between Jan 6, 2010, and Dec 29, 2017, from the LITMUS metacohort of the prospective European NAFLD Registry. Adults (aged ≥18 years) with paired liver biopsy and serum samples were eligible; those with excessive alcohol consumption or evidence of other chronic liver diseases were excluded. The diagnostic accuracy of the biomarkers was expressed as the area under the receiver operating characteristic curve (AUC) with liver histology as the reference standard and compared with the Fibrosis-4 index for liver fibrosis (FIB-4) in the same subgroup. Target conditions were the presence of NASH with clinically significant fibrosis (ie, at-risk NASH; NAFLD Activity Score ≥4 and F≥2) or the presence of advanced fibrosis (F≥3), analysed in all participants with complete data. We identified thres holds for each biomarker for reducing the number of biopsy-based screen failures when recruiting people with both NASH and clinically significant fibrosis for future trials. Findings: Of 1430 participants with NAFLD in the LITMUS metacohort with serum samples, 966 (403 women and 563 men) were included after all exclusion criteria had been applied. 335 (35%) of 966 participants had biopsy-confirmed NASH and clinically significant fibrosis and 271 (28%) had advanced fibrosis. For people with NASH and clinically significant fibrosis, no single biomarker or multimarker score significantly reached the predefined AUC 0·80 acceptability threshold (AUCs ranging from 0·61 [95% CI 0·54–0·67] for FibroScan controlled attenuation parameter to 0·81 [0·75–0·86] for SomaSignal), with accuracy mostly similar to FIB-4. Regarding detection of advanced fibrosis, SomaSignal (AUC 0·90 [95% CI 0·86–0·94]), ADAPT (0·85 [0·81–0·89]), and FibroScan liver stiffness measurement (0·83 [0·80–0·86]) reached acceptable accuracy. With 11 of 17 markers, histological screen failure rates could be reduced to 33% in trials if only people who were marker positive had a biopsy for evaluating eligibility. The best screening performance for NASH and clinically significant fibrosis was observed for SomaSignal (number needed to test [NNT] to find one true positive was four [95% CI 4–5]), then ADAPT (six [5–7]), MACK-3 (seven [6–8]), and PRO-C3 (nine [7–11]). Interpretation: None of the single markers or multimarker scores achieved the predefined acceptable AUC for replacing biopsy in detecting people with both NASH and clinically significant fibrosis. However, several biomarkers could be applied in a prescreening strategy in clinical trial recruitment. The performance of promising markers will be further evaluated in the ongoing prospective LITMUS study cohort. Funding: The Innovative Medicines Initiative 2 Joint Undertaking. © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license
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- Vali, Yasaman, et al.
(author)
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Enhanced liver fibrosis test for the non-invasive diagnosis of fibrosis in patients with NAFLD : A systematic review and meta-analysis
- 2020
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In: Journal of Hepatology. - : Elsevier. - 0168-8278 .- 1600-0641. ; 73:2, s. 252-262
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Research review (peer-reviewed)abstract
- BACKGROUND AND AIMS: The Enhanced Liver Fibrosis (ELF) test is a non-invasive biomarker, suggested as an appropriate test for advanced liver fibrosis in non-alcoholic fatty liver disease (NAFLD). This systematic review aimed to provide summary estimates of the accuracy of this test against biopsy.METHODS: In this systematic review, we searched MEDLINE, Embase, Web of Science and the Cochrane Library, for studies included NAFLD patients and undertook both liver biopsy as the reference standard and the ELF test. Two authors independently screened the references, extracted the data and assessed the quality of included studies. Due to the variation in reported thresholds, we used a multiple thresholds random effects model for meta-analysis (diagmeta R-package).RESULTS: The meta-analysis of 11 studies reporting advanced fibrosis and five studies reporting significant fibrosis showed sensitivity of >0.90 of the ELF test for excluding fibrosis at threshold of 7.7. However, as a diagnostic test at high thresholds, the test showed specificity and positive predictive value >0.80, only in very high-prevalence settings (>50%). Desiring specificity of 0.90 for advanced and significant fibrosis resulted in thresholds of 10.18 (sensitivity: 0.57) and 9.86 (sensitivity: 0.55), respectively.CONCLUSION: The ELF test showed high sensitivity but limited specificity to exclude advanced and significant fibrosis at low cutoffs. The diagnostic performance of the test at higher thresholds was found to be more limited in low prevalence settings. We conclude that clinicians should carefully consider the likely disease prevalence in their practice setting and adopt suitable test thresholds to achieve the desired test performance.
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