Stephen A Harrison1, Vlad Ratziu2, Jérôme Boursier3, Sven Francque4, Pierre Bedossa5, Zouher Majd6, Geneviève Cordonnier6, Fouad Ben Sudrik6, Raphael Darteil7, Roman Liebe8, Jérémy Magnanensi6, Yacine Hajji6, John Brozek6, Alice Roudot6, Bart Staels9, Dean W Hum6, Sophie Jeannin Megnien10, Suneil Hosmane6, Noémie Dam6, Pierre Chaumat6, Rémy Hanf11, Quentin M Anstee12, Arun J Sanyal13. 1. Summit Clinical Research, San Antonio, TX, USA; Radcliffe Department of Medicine, University of Oxford, Oxford, UK. 2. Sorbonne Université, Institute for Cardiometabolism and Nutrition, Hôpital Pitié-Salpêtrière, Paris, France. 3. Service d'Hépato-Gastroentérologie, Centre Hospitalier Universitaire d'Angers, Angers, France; Laboratoire HIFIH, UPRES EA3859, SFR 4208, Université d'Angers, Angers, France. 4. Department of Gastroenterology and Hepatology, Antwerp University Hospital, Antwerp, Belgium; Translational Sciences in Inflammation and Immunology & InflaMed Consortium of Excellence, University of Antwerp, Antwerp, Belgium. 5. Liverpat, Paris, France; Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK. 6. Genfit, Loos, France. 7. Genfit, Loos, France; ENYO Pharma, Lyon, France. 8. Genfit, Loos, France; Klinik für Gastroenterologie, Hepatologie und Infektiologie, Universitätsklinikum Düsseldorf, Düsseldorf, Germany. 9. Université de Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1011 - EGID, F-59000 Lille, France. 10. Summit Clinical Research, San Antonio, TX, USA; Genfit, Loos, France. 11. Genfit, Loos, France. Electronic address: remy.hanf@genfit.com. 12. Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK; Newcastle NIHR Biomedical Research Centre, Newcastle upon Tyne Hospitals NHS Foundation Trust, Freeman Hospital, Newcastle upon Tyne, UK. 13. Department of Internal Medicine, Virginia Commonwealth University School of Medicine, Richmond, VA, USA.
Abstract
BACKGROUND: Non-invasive tests that can identify patients with non-alcoholic steatohepatitis (NASH) at higher risk of disease progression are lacking. We report the development and validation of a blood-based diagnostic test to non-invasively rule in and rule out at-risk NASH (defined as non-alcoholic fatty liver disease [NAFLD] activity score [NAS] ≥4 and fibrosis stage ≥2). METHODS: In this prospective derivation and global validation study, blood samples, clinical data, and liver biopsy results from three independent cohorts with suspected NAFLD were used to develop and validate a non-invasive blood-based diagnostic test, called NIS4. Derivation was done in the discovery cohort, which comprised 239 prospectively recruited patients with biopsy-confirmed NASH (NAFLD NAS ≥3; fibrosis stage 0-3) from the international GOLDEN-505 phase 2b clinical trial. A complete matrix based on 23 variables selected for univariate association with the presence of at-risk NASH and avoiding high multi-collinearity was used to derive the model in a bootstrap-based process that minimised the Akaike information criterion. The overall diagnostic performance of NIS4 was externally validated in two independent cohorts: RESOLVE-IT diag and Angers. The RESOLVE-IT diag cohort comprised the first 475 patients screened for potential inclusion into the RESOLVE-IT phase 3 clinical trial. Angers was a retrospective cohort of 227 prospectively recruited patients with suspected NAFLD and clinical risk factors for NASH or fibrosis stage 2 or more according to abnormal elastography results or abnormal liver biochemistry. Both external validation cohorts were independently analysed and were combined into a pooled validation cohort (n=702) to assess clinical performance of NIS4 and other non-invasive tests. FINDINGS: The derived NIS4 algorithm comprised four independent NASH-associated biomarkers (miR-34a-5p, alpha-2 macroglobulin, YKL-40, and glycated haemoglobin; area under the receiver operating characteristics curve [AUROC] 0·80, 95% CI 0·73-0·85), and did not require adjustment for age, sex, body-mass index (BMI), or aminotransferase concentrations. Clinical cutoffs were established within the discovery cohort to optimise both rule out and rule in clinical performance while minimising indeterminate results. NIS4 was validated in the RESOLVE-IT diag cohort (AUROC 0·83, 95% CI 0·79-0·86) and the Angers cohort (0·76, 0·69-0·82). In the pooled validation cohort, patients with a NIS4 value less than 0·36 were classified as not having at-risk NASH (ruled out) with 81·5% (95% CI 76·9-85·3) sensitivity, 63·0% (57·8-68·0) specificity, and a negative predictive value of 77·9% (72·5-82·4), whereas those with a NIS4 value of more than 0·63 were classified as having at-risk NASH (ruled in) with 87·1% (83·1-90·3) specificity, 50·7% (45·3-56·1) sensitivity, and a positive predictive value of 79·2% (73·1-84·2). The diagnostic performance of NIS4 within the external validation cohorts was not influenced by age, sex, BMI, or aminotransferase concentrations. INTERPRETATION:NIS4 is a novel blood-based diagnostic that provides an effective way to non-invasively rule in or rule out at-risk NASH in patients with metabolic risk factors and suspected disease. Use of NIS4 in clinical trials or in the clinic has the potential to greatly reduce unnecessary liver biopsies in patients with lower risk of disease progression. FUNDING: Genfit.
RCT Entities:
BACKGROUND: Non-invasive tests that can identify patients with non-alcoholic steatohepatitis (NASH) at higher risk of disease progression are lacking. We report the development and validation of a blood-based diagnostic test to non-invasively rule in and rule out at-risk NASH (defined as non-alcoholic fatty liver disease [NAFLD] activity score [NAS] ≥4 and fibrosis stage ≥2). METHODS: In this prospective derivation and global validation study, blood samples, clinical data, and liver biopsy results from three independent cohorts with suspected NAFLD were used to develop and validate a non-invasive blood-based diagnostic test, called NIS4. Derivation was done in the discovery cohort, which comprised 239 prospectively recruited patients with biopsy-confirmed NASH (NAFLD NAS ≥3; fibrosis stage 0-3) from the international GOLDEN-505 phase 2b clinical trial. A complete matrix based on 23 variables selected for univariate association with the presence of at-risk NASH and avoiding high multi-collinearity was used to derive the model in a bootstrap-based process that minimised the Akaike information criterion. The overall diagnostic performance of NIS4 was externally validated in two independent cohorts: RESOLVE-IT diag and Angers. The RESOLVE-IT diag cohort comprised the first 475 patients screened for potential inclusion into the RESOLVE-IT phase 3 clinical trial. Angers was a retrospective cohort of 227 prospectively recruited patients with suspected NAFLD and clinical risk factors for NASH or fibrosis stage 2 or more according to abnormal elastography results or abnormal liver biochemistry. Both external validation cohorts were independently analysed and were combined into a pooled validation cohort (n=702) to assess clinical performance of NIS4 and other non-invasive tests. FINDINGS: The derived NIS4 algorithm comprised four independent NASH-associated biomarkers (miR-34a-5p, alpha-2 macroglobulin, YKL-40, and glycated haemoglobin; area under the receiver operating characteristics curve [AUROC] 0·80, 95% CI 0·73-0·85), and did not require adjustment for age, sex, body-mass index (BMI), or aminotransferase concentrations. Clinical cutoffs were established within the discovery cohort to optimise both rule out and rule in clinical performance while minimising indeterminate results. NIS4 was validated in the RESOLVE-IT diag cohort (AUROC 0·83, 95% CI 0·79-0·86) and the Angers cohort (0·76, 0·69-0·82). In the pooled validation cohort, patients with a NIS4 value less than 0·36 were classified as not having at-risk NASH (ruled out) with 81·5% (95% CI 76·9-85·3) sensitivity, 63·0% (57·8-68·0) specificity, and a negative predictive value of 77·9% (72·5-82·4), whereas those with a NIS4 value of more than 0·63 were classified as having at-risk NASH (ruled in) with 87·1% (83·1-90·3) specificity, 50·7% (45·3-56·1) sensitivity, and a positive predictive value of 79·2% (73·1-84·2). The diagnostic performance of NIS4 within the external validation cohorts was not influenced by age, sex, BMI, or aminotransferase concentrations. INTERPRETATION:NIS4 is a novel blood-based diagnostic that provides an effective way to non-invasively rule in or rule out at-risk NASH in patients with metabolic risk factors and suspected disease. Use of NIS4 in clinical trials or in the clinic has the potential to greatly reduce unnecessary liver biopsies in patients with lower risk of disease progression. FUNDING: Genfit.
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