NIS2+™, an optimisation of the blood-based biomarker NIS4® technology for the detection of at-risk NASH: A prospective derivation and validation study

混淆 医学 稳健性(进化) 接收机工作特性 生物标志物 逻辑回归 脂肪性肝炎 内科学 脂肪肝 统计 疾病 数学 生物化学 化学 基因
作者
Stephen A. Harrison,Vlad Ratziu,Jérémy Magnanensi,Yacine Hajji,Sylvie Deledicque,Zouher Majd,Christian Rosenquist,Dean W. Hum,Bart Staels,Quentin M. Anstee,Arun J. Sanyal
出处
期刊:Journal of Hepatology [Elsevier]
卷期号:79 (3): 758-767 被引量:19
标识
DOI:10.1016/j.jhep.2023.04.031
摘要

•Non-invasive tools for large-scale diagnosis of at-risk NASH are needed.•We developed NIS2+™, a two-biomarker test corrected for sex, to detect at-risk NASH.•NIS2+™ clinical performance was superior to that of NIS4®.•NIS2+™ showed a strong performance to rule in/out at-risk NASH at fixed cutoffs.•NIS2+™ was not impacted by patients’ characteristics of interest for NAFLD. Background & AimsNIS4® 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.MethodsA 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.ResultsUsing 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.ConclusionNIS2+™ constitutes a robust optimisation of NIS4® technology for the detection of at-risk NASH.Impact and implicationsThe 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. 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. 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. 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. NIS2+™ constitutes a robust optimisation of NIS4® technology for the detection of at-risk NASH.
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