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Fulvio Braido,1,2 Enrico Arnaboldi,1,2 Sara Barile,3 Luca Cavalieri,4 Eleonora Ingrassia,4 Maria Russo,1,2 Alessio Piraino4 1Respiratory Unit for Continuity of Care, IRCCS, Ospedale Policlinico San Martino, Genova, Italy; 2Department of Internal Medicine (DiMI), University of Genova, Genova, Italy; 3Chiesi Farmaceutici S.p.A., Parma, Italy; 4Chiesi Italia S.p.A ., Parma, ItalyCorrespondence: Fulvio Braido, Respiratory Unit for Continuity of Care, IRCCS, Ospedale Policlinico San Martino, Genova, Italy, Email fulvio.braido@unige.itAbstract: In this article, we discuss the importance of real-world data in the treatment of patients with asthma and specifically the role of maintenance and reliever therapy (MART) with beclometasone dipropionate (BDP)/formoterol fumarate dihydrate (FF) delivered through a dry-powder inhaler (DPI) that contains an extrafine formulation. We also present the design of the NEWTON study. This multinational, multicenter, prospective, observational study will evaluate the real-world use of extrafine BDP/FF via a DPI as maintenance therapy and MART in patients with moderate to severe asthma. The study’s primary outcome will be the proportion of patients improving their asthma control. Digitally collected patient-reported outcomes, such as the 5-item Asthma Control Questionnaire, the EuroQol 5-dimension 5-level, and the Test of the Adherence to Inhalers, will be used to assess the patient’s asthma control, quality of life, and treatment adherence. Moreover, a new patient-reported outcome, the “Speed of change in health feeling” questionnaire, will be validated in a subgroup of patients. Overall, the results of this study will provide a real-life assessment of patients who perceived clinical benefits in a large cohort of asthmatics in Europe treated as per current clinical practice.Keywords: asthma, dry-powder inhaler, beclometasone dipropionate/formoterol fumarate, observational study

Objective Clinical diagnosis and approval of new medications for non-alcoholic steatohepatitis (NASH) require invasive liver biopsies. The aim of our study was to identify non-invasive biomarkers of NASH and/or liver fibrosis. Design This multicentre study includes 250 patients (discovery cohort, n=100 subjects (Bariatric Surgery Versus Non-alcoholic Steato-hepatitis - BRAVES trial); validation cohort, n=150 (Liquid Biopsy for NASH and Liver Fibrosis - LIBRA trial)) with histologically proven non-alcoholic fatty liver (NAFL) or NASH with or without fibrosis. Proteomics was performed in monocytes and hepatic stellate cells (HSCs) with iTRAQ-nano- Liquid Chromatography - Mass Spectrometry/Mass Spectrometry (LC-MS/MS), while flow cytometry measured perilipin-2 (PLIN2) and RAB14 in peripheral blood CD14 + CD16 - monocytes. Neural network classifiers were used to predict presence/absence of NASH and NASH stages. Logistic bootstrap-based regression was used to measure the accuracy of predicting liver fibrosis. Results The algorithm for NASH using PLIN2 mean florescence intensity (MFI) combined with waist circumference, triglyceride, alanine aminotransferase (ALT) and presence/absence of diabetes as covariates had an accuracy of 93% in the discovery cohort and of 92% in the validation cohort. Sensitivity and specificity were 95% and 90% in the discovery cohort and 88% and 100% in the validation cohort, respectively. The area under the receiver operating characteristic (AUROC) for NAS level prediction ranged from 83.7% (CI 75.6% to 91.8%) in the discovery cohort to 97.8% (CI 95.8% to 99.8%) in the validation cohort. The algorithm including RAB14 MFI, age, waist circumference, high-density lipoprotein cholesterol, plasma glucose and ALT levels as covariates to predict the presence of liver fibrosis yielded an AUROC of 95.9% (CI 87.9% to 100%) in the discovery cohort and 99.3% (CI 98.1% to 100%) in the validation cohort, respectively. Accuracy was 99.25%, sensitivity 100% and

OBJECTIVE Clinical diagnosis and approval of new medications for non-alcoholic steatohepatitis (NASH) require invasive liver biopsies. The aim of our study was to identify non-invasive biomarkers of NASH and/or liver fibrosis. DESIGN This multicentre study includes 250 patients (discovery cohort, n=100 subjects (Bariatric Surgery Versus Non-alcoholic Steato-hepatitis - BRAVES trial); validation cohort, n=150 (Liquid Biopsy for NASH and Liver Fibrosis - LIBRA trial)) with histologically proven non-alcoholic fatty liver (NAFL) or NASH with or without fibrosis. Proteomics was performed in monocytes and hepatic stellate cells (HSCs) with iTRAQ-nano- Liquid Chromatography - Mass Spectrometry/Mass Spectrometry (LC-MS/MS), while flow cytometry measured perilipin-2 (PLIN2) and RAB14 in peripheral blood CD14$^{+}$CD16$^{-}$ monocytes. Neural network classifiers were used to predict presence/absence of NASH and NASH stages. Logistic bootstrap-based regression was used to measure the accuracy of predicting liver fibrosis. RESULTS The algorithm for NASH using PLIN2 mean florescence intensity (MFI) combined with waist circumference, triglyceride, alanine aminotransferase (ALT) and presence/absence of diabetes as covariates had an accuracy of 93% in the discovery cohort and of 92% in the validation cohort. Sensitivity and specificity were 95% and 90% in the discovery cohort and 88% and 100% in the validation cohort, respectively.The area under the receiver operating characteristic (AUROC) for NAS level prediction ranged from 83.7% (CI 75.6% to 91.8%) in the discovery cohort to 97.8% (CI 95.8% to 99.8%) in the validation cohort.The algorithm including RAB14 MFI, age, waist circumference, high-density lipoprotein cholesterol, plasma glucose and ALT levels as covariates to predict the presence of liver fibrosis yielded an AUROC of 95.9% (CI 87.9% to 100%) in the discovery cohort and 99.3% (CI 98.1% to 100%) in the validation cohort, respectively. Accuracy was 99.25%, sensitivity 100