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Background & Aims: Strategies to reduce liver biopsy (LB) screen failures through better patient selection are needed for clinical trials. Standard fibrosis biomarkers were not derived to detect "at-risk" metabolic dysfunction-associated steatohepatitis (MASH; MASH with metabolic dysfunction-associated steatotic liver disease score ≥4 and fibrosis stage ≥2). We compared the performance of screening pathways that incorporate NIS2+™, an optimized version of the blood-based NIS4® technology designed to identify at-risk MASH, with those incorporating fibrosis (FIB)-4 within the RESOLVE-IT clinical trial (NCT02704403), aiming for optimized selection of patients for LB., Methods: A retrospective simulation analysis was conducted in the RESOLVE-IT screening pathway (RSP) cohort. LB failure rate (LBFR), number of patients needed to screen, and overall cost estimations of different pathways were calculated for a range of NIS2+™ and FIB-4 cut-offs and compared with those of the RSP, which relied on investigators' local practices. An analysis of potential recruitment bias based on histology, sex, age, or comorbidities was performed., Results: The analysis cohort included 1,929 patients, 765 (40%) with at-risk MASH. The NIS2+™ pathway resulted in a significantly lower LBFR (39%) compared with the FIB-4 pathway (58%) or the RSP (60%) when using cost-optimized cut-offs (NIS2+™, 0.53; FIB-4, 0.58). For every 1,000 inclusions, NIS2+™ significantly reduced unnecessary LBs (632 vs. 1,522; -58%) and screening costs (US$12.7 million vs. US$15.0 million) vs. the RSP, while the number of patients needed to screen increased moderately (3,220 to 4,033). NIS2+™ alone is better than FIB-4 alone or combined with FIB-4., Conclusions: This analysis demonstrated that patient selection for LB using NIS2+™ significantly reduced unnecessary biopsies and screening costs, which could greatly improve the feasibility of MASH clinical trials., Impact and Implications: Simple and accurate non-invasive strategies to optimize the selection of patients who should be referred for liver biopsy for inclusion in MASH clinical trials is critical to reduce the high liver biopsy failure rates. While the use of the Fibrosis-4 index alone did not lead to a significant improvement of the screening process, selecting patients using NIS2+™, a recently developed optimization of the NIS4® technology for the detection of at-risk MASH, showed improved performance by simultaneously reducing liver biopsy failure rates and the overall cost of the trial, while maintaining the number of patients needed to screen at a manageable level and not generating any bias in included patients' characteristics. This makes NIS2+™ an accurate and reliable screening tool that could improve the recruitment of patients in future MASH clinical trials, and would lead to increased patient comfort and security, ensuring timely and cost-efficient trial completion., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Background & Aims: Robust performance of non-invasive tests (NITs) across ages is critical to assess liver disease among patients with metabolic dysfunction-associated liver disease (MASLD). We evaluated the impact of age on the performance of NIS2+™ vs. other NITs., Methods: An analysis cohort (N = 1,926) with biopsy-proven MASLD was selected among individuals screened for the phase III RESOLVE-IT clinical trial and divided into ≤45, 46-55, 56-64, and ≥65 years groups. To avoid potential confounding effects, a well-balanced cohort (n = 708; n = 177/age group) was obtained by applying a propensity score-matching algorithm to the analysis cohort. Baseline values of biomarkers and NITs were compared across age groups using one-way ANOVA, and the impact of age and histology were compared through three-way ANOVA. The impact of age on NIT performance for the detection of at-risk metabolic dysfunction-associated steatohepatitis (MASH; MASLD activity score [MAS] ≥4 and fibrosis stage [F] ≥2) was also evaluated., Results: Age did not affect the distributions of NIS2+™ and APRI (aspartate aminotransferase-to-platelet ratio index), but significantly ( p <0.0001) impacted those of NFS (NAFLD fibrosis score), FIB-4 (Fibrosis-4 index), and Enhanced Liver Fibrosis (ELF™) score. NIS2+™ was the only NIT on which fibrosis and MAS exerted a moderate to large effect. While the impact of fibrosis on APRI was moderate, that of MAS was low. The impact of age on FIB-4 and NFS was larger than that of fibrosis. NIS2+™ exhibited the highest AUROC values for detecting at-risk MASH across age groups, with stable performances irrespective of cut-offs., Conclusions: NIS2+™ was not significantly impacted by age and was sensitive to both fibrosis and MAS grade, demonstrating a robust performance to rule in/out at-risk MASH with fixed cut-offs., Impact and Implications: While metabolic dysfunction-associated steatotic liver disease (MASLD) can affect individuals of all ages, patient age could represent an important confounding factor when interpreting non-invasive test (NIT) results, highlighting the need for reliable and efficient NITs that are not impacted by age and that could be interpreted with fixed cut-offs, irrespective of patient age. We report the impact of age on different well-established NITs - among those tested, only two panels, NIS2+™ and APRI, were not impacted by age and can be used and interpreted independently of patient age. NIS2+™ was also sensitive to both fibrosis and MAS, further confirming its efficiency for the detection of the composite endpoint of at-risk MASH and its potential as a valuable candidate for large-scale implementation in clinical practice and clinical trials., Competing Interests: QMA: research support from LITMUS (Liver Investigation: Testing Marker Utility in Steatohepatitis) consortium funded by the Innovative Medicines Initiative Program of the European Union under Grant Agreement 777377 (this multistakeholder consortium includes industry partners and received funding from EFPIA); grants or contracts from AstraZeneca, Boehringer Ingelheim, and Intercept Pharmaceuticals; royalties or licenses from Elsevier Ltd.; consulting fees (on behalf of Newcastle University) from Alimentiv, Akero Therapeutics, Inc., AstraZeneca, Axcella Health, Inc., 89bio, Inc., Boehringer Ingelheim, Bristol Myers Squibb, Galmed Pharmaceuticals, Genfit S.A., Genentech, Gilead Sciences Inc., GlaxoSmithKline, Hanmi, HistoIndex Pte Ltd., Intercept Pharmaceuticals, Inventiva, Ionis, IQVIA, Janssen, Madrigal Pharmaceuticals, Medpace, Merck, NGM Biopharmaceuticals, Novartis Pharmaceuticals, Novo Nordisk, PathAI, Pfizer, Prosciento, Poxel S.A., Resolution Therapeutics, Roche, Ridgeline Therapeutics, RTI, Shionogi, and Terns Pharmaceuticals; payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Fishawack, Integritas Communications, Kenes, Novo Nordisk, Madrigal Pharmaceuticals, Medscape, and Springer Healthcare; served on advisory boards or data safety monitoring boards (on behalf of Newcastle University) for Medpace (NorthSea Therapeutics B.V., DSMB). BS: consulting fees from Genfit S.A. MAC: Labcorp employee. RL: grants/funding support from the National Center for Advancing Translational Sciences, the National Institute of Diabetes and Digestive and Kidney Diseases, the National Heart, Lung, and Blood Institute, Arrowhead Pharmaceuticals, AstraZeneca, Boehringer Ingelheim, Bristol Myers Squibb, Eli Lilly, Galectin Therapeutics, Inc., Galmed Pharmaceuticals, Gilead Sciences, Inc., Hanmi, Intercept Pharmaceuticals, Inventiva, Ionis, Janssen, Madrigal Pharmaceuticals, Merck, NGM Biopharmaceuticals, Novo Nordisk, Pfizer, Sonic Incytes, and Terns Pharmaceuticals; consulting fees from Aardvark Therapeutics, Altimmune, Anylam/Regeneron, Amgen, Arrowhead Pharmaceuticals, AstraZeneca, Bristol Myers Squibb, CohBar, Inc., Eli Lilly, Galmed Pharmaceuticals, Gilead Sciences, Inc., Glympse Bio, HighTide Therapeutics, Ini Pharma, Intercept Pharmaceuticals, Intercept Pharmaceuticals, Ionis, Janssen, Madrigal Pharmaceuticals, Metacrine, NGM Biopharmaceuticals, Novartis Pharmaceuticals, Novo Nordisk, Merck, Pfizer, Sagimet Biosciences, Theratechnologies, Inc., 89bio, Inc., Terns Pharmaceuticals, and Viking Therapeutics; other financial interests: LipoNexus, Inc. (co-founder). SAH: grants or contracts from Akero Therapeutics, Alentis Therapeutics, Altimmune, B. Riley FBR, ChronWell, Corcept Therapeutics, Echosens, Axcella Health, Cirius Therapeutics, CiVi Biopharma, Cymabay Therapeutics, Inc., Enyo Pharma S.A., Galectin Therapeutics, Inc., Galmed Research & Development, Ltd., Genfit S.A., Gilead Sciences, Inc., Hepion Pharmaceuticals, Inc., Hepta Bio, HighTide Therapeutics, Inc, HistoIndex, Intercept Pharmaceuticals, Ionis, Madrigal Pharmaceuticals, Medpace, NGM Biopharmaceuticals, Inc., NeuroBo, NorthSea Therapeutics B.V., Novartis Pharmaceuticals, Novo Nordisk, Path AI, Perspectum, Poxel S.A., Sagimet Biosciences, Sonic Incytes, Terns Pharmaceuticals, and Viking Therapeutics; stock or stock options for Akero Therapeutics, ChronWell, Cirius Therapeutics, Galectin Therapeutics, Inc., Genfit S.A., Hepion Pharmaceuticals, Inc., HistoIndex Pte Ltd., Metacrine, NGM Biopharmaceuticals, Inc., NorthSea Therapeutics B.V. VR: grants or contracts from Intercept Pharmaceuticals, and Gilead Sciences, Inc.; consulting fees from Boehringer Ingelheim, Novo Nordisk, Poxel S.A., Enyo Pharma S.A., Madrigal Pharmaceuticals, Terns Pharmaceuticals, Intercept Pharmaceuticals, NGM Biopharmaceuticals Inc., and Pfizer. AJS: stock options in Genfit S.A., Tiziana, Indalo, Durect, Inversago, and Galmed Pharmaceuticals; consultant to AstraZeneca, Salix, Tobira, Takeda, Jannsen, Gilead Sciences, Inc., Terns Pharmaceuticals, Merck, Madrigal Pharmaceuticals, NGM Biopharmaceuticals, Inc., Sagimet Biosciences, Valeant, Boehringer Ingelheim, Bristol Myers Squibb, Eli Lilly, Hemoshear, Novartis Pharmaceuticals, Inventiva, Enyo, Akero Therapeutics, 89bio, Inc., Novo Nordisk, Pfizer, Amgen, Genentech, Regeneron, Alnylam, Hanmi, LG Chem, Histoindex, Thera Technologies, Intercept Pharmaceuticals, Target-RWE, Surrozen, Zydus, Path AI, Exhalenz, and Genfit S.A.; his institution has received grant support from Gilead Sciences, Inc., Salix, Tobira, Bristol Myers Squibb, Pfizer, Intercept Pharmaceuticals, Merck, AstraZeneca, Mallinckrodt, and Novartis Pharmaceuticals; royalties received from Elsevier and UpToDate. JM, YH, AC, ZM, CR, and DWH: stock or stock options from Genfit S.A. and serve as Genfit S.A. employees. Please refer to the accompanying ICMJE disclosure forms for further details., (© 2024 The Author(s).)

Background & Aims: NIS4® is a blood-based non-invasive test designed to effectively rule in/rule out at-risk non-alcoholic steatohepatitis (NASH), defined as non-alcoholic fatty liver disease activity score ≥4 and significant fibrosis (stage ≥2), among patients with metabolic risk factors. Robustness of non-invasive test scores across characteristics of interest including age, type 2 diabetes mellitus, and sex, and optimised analytical aspects are critical for large-scale implementation in clinical practice. We developed and validated NIS2+™, an optimisation of NIS4®, specifically designed to improve score robustness., Methods: A well-balanced training cohort (n = 198) included patients from the GOLDEN-505 trial. The validation (n = 684) and test (n = 2,035) cohorts included patients from the RESOLVE-IT trial. Well-matched subgroups were created to avoid potential confounding effects during modelling and analysis of score robustness. Models were trained using logistic regressions for at-risk NASH detection and compared using Bayesian information criteria. Performance of NIS2+™ was compared with that of NIS4®, Fibrosis-4, and alanine aminotransferase using area under the receiver operating characteristic curve, and robustness was analysed through score distribution., Results: Using the training cohort to compare all combinations of NIS4® biomarkers, NIS2 (miR-34a-5p, YKL-40) was identified as the best combination of parameters. To correct for the sex effect on miR-34a-5p (validation cohort), sex and sex ∗ miR-34a-5p parameters were added, creating NIS2+™. In the test cohort, NIS2+™ exhibited a statistically higher area under the receiver operating characteristic curve (0.813) vs. NIS4® (0.792; p = 0.0002), Fibrosis-4 (0.653; p <0.0001), and alanine aminotransferase (0.699; p <0.0001). NIS2+™ scores were not affected by age, sex, BMI, or type 2 diabetes mellitus status, providing robust clinical performances irrespective of patient characteristics., Conclusion: NIS2+™ constitutes a robust optimisation of NIS4® technology for the detection of at-risk NASH., Impact and Implications: The development of non-invasive tests for accurate, large-scale detection of patients with at-risk non-alcoholic steatohepatitis (NASH; defined as NASH with non-alcoholic fatty liver disease activity score ≥4 and fibrosis stage ≥2) - who are at higher risk for disease progression and for developing liver-related life-threatening outcomes - is critical for identifying this patient population in the clinical setting and improving the screening process of NASH clinical trials. We report the development and validation of NIS2+™, a diagnostic test designed as an optimisation of NIS4® technology, a blood-based panel currently used to detect at-risk NASH in patients with metabolic risk factors. NIS2+™ showed improved performance for the detection of at-risk NASH compared with NIS4® and other non-invasive liver tests that was not impacted by patients' characteristics of interest, such as age, sex, type 2 diabetes mellitus, BMI, dyslipidaemia, and hypertension. This makes NIS2+™ a robust and reliable tool for the diagnosis of at-risk NASH among patients with metabolic risk factors, and an effective candidate for large-scale implementation in clinical practice and clinical trials., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Older patients are at increased risk for at-risk NASH, defined as NASH with NAFLD activity scores (NAS) ≥4 and significant fibrosis (F ≥ 2). The aim of this study was to compare the performance of 2 new blood tests, NIS4® and NIS2+™, with FIB-4, NFS, ELF™, and alanine aminotransferase (ALT) for the diagnosis of at-risk NASH in a cohort of patients aged ≥65 years., Methods: The clinical performance of multiple blood-based tests was assessed for their ability to detect at-risk NASH using the RESOLVE-IT diag cohort, a large population of patients with metabolic risk who were screened for potential inclusion in the RESOLVE-IT phase 3 trial., Results: The study cohort (n = 2053) included patients with the full histological spectrum of NAFLD, with patients having liver fibrosis stages F0-4 and NAS scores 0-8. NIS4® and NIS2+™ showed similar assay performance in patients who were <65 versus ≥65 years of age (AUROC = 0.80 vs. 0.78, p = 0.47; 0.81 vs. 0.83 p = 0.45, respectively) for the identification of at-risk NASH. In patients ≥65 (n = 410), NIS2+™ exhibited the highest AUROC compared to NIS4®, FIB-4, NFS, ELF™, and ALT (AUROC = 0.83 vs. 0.78, 0.68, 0.58, 0.69, 0.74, respectively; all p ≤ 0.0009). For NIS2+™, the sensitivity and NPV for ruling-out at-risk NASH at the 0.46 cutoff were 90.2% and 86.0%, and the specificity and PPV for ruling-in at-risk NASH at the 0.68 cutoff were81.1% and 76.3%, respectively., Conclusions: The clinical performance of NIS2+™ was superior for the diagnosis of at-risk NASH in patients ≥65 years of age. These data support the clinical value of this blood-based test for the diagnosis of at-risk NASH in older adults., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Association for the Study of Liver Diseases.)

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., (Copyright © 2020 Elsevier Ltd. All rights reserved.)