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- Blach, S., et al.
(författare)
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Global change in hepatitis C virus prevalence and cascade of care between 2015 and 2020: a modelling study
- 2022
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Ingår i: Lancet Gastroenterology & Hepatology. - : Elsevier BV. - 2468-1253. ; 7:5, s. 396-415
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Tidskriftsartikel (refereegranskat)abstract
- Background Since the release of the first global hepatitis elimination targets in 2016, and until the COVID-19 pandemic started in early 2020, many countries and territories were making progress toward hepatitis C virus (HCV) elimination. This study aims to evaluate HCV burden in 2020, and forecast HCV burden by 2030 given current trends. Methods This analysis includes a literature review, Delphi process, and mathematical modelling to estimate HCV prevalence (viraemic infection, defined as HCV RNA-positive cases) and the cascade of care among people of all ages (age =0 years from birth) for the period between Jan 1, 2015, and Dec 31, 2030. Epidemiological data were collected from published sources and grey literature (including government reports and personal communications) and were validated among country and territory experts. A Markov model was used to forecast disease burden and cascade of care from 1950 to 2050 for countries and territories with data. Model outcomes were extracted from 2015 to 2030 to calculate population-weighted regional averages, which were used for countries or territories without data. Regional and global estimates of HCV prevalence, cascade of care, and disease burden were calculated based on 235 countries and territories. Findings Models were built for 110 countries or territories: 83 were approved by local experts and 27 were based on published data alone. Using data from these models, plus population-weighted regional averages for countries and territories without models (n=125), we estimated a global prevalence of viraemic HCV infection of 0.7% (95% UI 0.7-0.9), corresponding to 56.8 million (95% UI 55.2-67.8) infections, on Jan 1, 2020. This number represents a decrease of 6.8 million viraemic infections from a 2015 (beginning of year) prevalence estimate of 63.6 million (61.8-75.8) infections (0.9% [0.8-1.0] prevalence). By the end of 2020, an estimated 12.9 million (12.5-15.4) people were living with a diagnosed viraemic infection. In 2020, an estimated 641 000 (623 000-765 000) patients initiated treatment. Interpretation At the beginning of 2020, there were an estimated 56.8 million viraemic HCV infections globally. Although this number represents a decrease from 2015, our forecasts suggest we are not currently on track to achieve global elimination targets by 2030. As countries recover from COVID-19, these findings can help refocus efforts aimed at HCV elimination. Copyright (C) 2022 Elsevier Ltd. All rights reserved.
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- Razavi, H., et al.
(författare)
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Hepatitis C virus prevalence and level of intervention required to achieve the WHO targets for elimination in the European Union by 2030: a modelling study
- 2017
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Ingår i: Lancet Gastroenterology & Hepatology. - : Elsevier BV. - 2468-1253. ; 2:5, s. 325-336
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Tidskriftsartikel (refereegranskat)abstract
- Background Hepatitis C virus (HCV) is a leading cause of liver-related morbidity and mortality worldwide. In the European Union (EU), treatment and cure of HCV with direct-acting antiviral therapies began in 2014. WHO targets are to achieve a 65% reduction in liver-related deaths, a 90% reduction of new viral hepatitis infections, and 90% of patients with viral hepatitis infections being diagnosed by 2030. This study assessed the prevalence of HCV in the EU and the level of intervention required to achieve WHO targets for HCV elimination. Methods We populated country Markov models for the 28 EU countries through a literature search of PubMed and Embase between Jan 1, 2000, and March 31, 2016, and a Delphi process to gain expert consensus and validate inputs. We aggregated country models to create a regional EU model. We used the EU model to forecast HCV disease progression (considering the effect of immigration) and developed a strategy to acehive WHO targets. We used weighted average sustained viral response rates and fibrosis restrictions to model the effect of current therapeutic guidelines. We used the EU model to forecast HCV disease progression (considering the effect of immigration) under current screening and therapeutic guidelines. Additionally, we back-calculated the total number of patients needing to be screened and treated to achieve WHO targets. Findings We estimated the number of viraemic HCV infections in 2015 to be 3 238 000 (95% uncertainty interval [UI] 2 106 000-3 795 000) of a total population of 509 868 000 in the EU, equating to a prevalence of viraemic HCV of 0.64% (95% UI 0.41-0.74). We estimated that 1 180 000 (95% UI 1 003 000-1 357 000) people were diagnosed with viraemia (36.4%), 150 000 (12 000-180 000) were treated (4.6% of the total infected population or 12.7% of the diagnosed population), 133 000 (106 000-160 000) were cured (4.1%), and 57 900 (43 900-67 300) were newly infected (1.8%) in 2015. Additionally, 30 400 (26 600-42 500) HCV-positive immigrants entered the EU. To achieve WHO targets, unrestricted treatment needs to increase from 150 000 patients in 2015 to 187 000 patients in 2025 and diagnosis needs to increase from 88 800 new cases annually in 2015 to 180 000 in 2025. Interpretation Given its advanced health-care infrastructure, the EU is uniquely poised to eliminate HCV; however, expansion of screening programmes is essential to increase treatment to achieve the WHO targets. A united effort, grounded in sound epidemiological evidence, will also be necessary.
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- Hardy, Timothy, et al.
(författare)
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The European NAFLD Registry : A real-world longitudinal cohort study of nonalcoholic fatty liver disease
- 2020
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Ingår i: Contemporary Clinical Trials. - : Elsevier. - 1551-7144 .- 1559-2030. ; 98
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Tidskriftsartikel (refereegranskat)abstract
- Non-Alcoholic Fatty Liver Disease (NAFLD), a progressive liver disease that is closely associated with obesity, type 2 diabetes, hypertension and dyslipidaemia, represents an increasing global public health challenge. There is significant variability in the disease course: the majority exhibit only fat accumulation in the liver but a significant minority develop a necroinflammatory form of the disease (non-alcoholic steatohepatitis, NASH) that may progress to cirrhosis and hepatocellular carcinoma. At present our understanding of pathogenesis, disease natural history and long-term outcomes remain incomplete. There is a need for large, well characterised patient cohorts that may be used to address these knowledge gaps and to support the development of better biomarkers and novel therapies. The European NAFLD Registry is an international, prospectively recruited observational cohort study that aims to establish a large, highly-phenotyped patient cohort and linked bioresource. Here we describe the infrastructure, data management and monitoring plans, and the standard operating procedures implemented to ensure the timely and systematic collection of high-quality data and samples. Already recruiting subjects at secondary/tertiary care centres across Europe, the Registry is supporting the European Union IMI2-funded LITMUS Liver Investigation: Testing Marker Utility in Steatohepatitis consortium, which is a major international effort to robustly validate biomarkers that diagnose, risk stratify and/or monitor NAFLD progression and liver fibrosis stage. The European NAFLD Registry has the demonstrable capacity to support research and biomarker development at scale and pace.
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- Lee, Jenny, et al.
(författare)
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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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Ingår i: Hepatology. - : LIPPINCOTT WILLIAMS & WILKINS. - 0270-9139 .- 1527-3350. ; 78:1, s. 258-271
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Tidskriftsartikel (refereegranskat)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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- Mcteer, Matthew, et al.
(författare)
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Machine learning approaches to enhance diagnosis and staging of patients with MASLD using routinely available clinical information
- 2024
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Ingår i: PLOS ONE. - : PUBLIC LIBRARY SCIENCE. - 1932-6203. ; 19:2
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Tidskriftsartikel (refereegranskat)abstract
- Aims Metabolic dysfunction Associated Steatotic Liver Disease (MASLD) outcomes such as MASH (metabolic dysfunction associated steatohepatitis), fibrosis and cirrhosis are ordinarily determined by resource-intensive and invasive biopsies. We aim to show that routine clinical tests offer sufficient information to predict these endpoints.Methods Using the LITMUS Metacohort derived from the European NAFLD Registry, the largest MASLD dataset in Europe, we create three combinations of features which vary in degree of procurement including a 19-variable feature set that are attained through a routine clinical appointment or blood test. This data was used to train predictive models using supervised machine learning (ML) algorithm XGBoost, alongside missing imputation technique MICE and class balancing algorithm SMOTE. Shapley Additive exPlanations (SHAP) were added to determine relative importance for each clinical variable.Results Analysing nine biopsy-derived MASLD outcomes of cohort size ranging between 5385 and 6673 subjects, we were able to predict individuals at training set AUCs ranging from 0.719-0.994, including classifying individuals who are At-Risk MASH at an AUC = 0.899. Using two further feature combinations of 26-variables and 35-variables, which included composite scores known to be good indicators for MASLD endpoints and advanced specialist tests, we found predictive performance did not sufficiently improve. We are also able to present local and global explanations for each ML model, offering clinicians interpretability without the expense of worsening predictive performance.Conclusions This study developed a series of ML models of accuracy ranging from 71.9-99.4% using only easily extractable and readily available information in predicting MASLD outcomes which are usually determined through highly invasive means.
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- Vali, Yasaman, et al.
(författare)
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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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Ingår i: The Lancet Gastroenterology & Hepatology. - : Elsevier Ltd. - 2468-1253. ; 8:8, s. 714-725
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Tidskriftsartikel (refereegranskat)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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