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      Minimal clinically important difference for asthma endpoints: an expert consensus report

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          Abstract

          Minimal clinically important difference (MCID) can be defined as the smallest change or difference in an outcome measure that is perceived as beneficial and would lead to a change in the patient's medical management.

          The aim of the current expert consensus report is to provide a “state-of-the-art” review of the currently available literature evidence about MCID for end-points to monitor asthma control, in order to facilitate optimal disease management and identify unmet needs in the field to guide future research.

          A series of MCID cut-offs are currently available in literature and validated among populations of asthmatic patients, with most of the evidence focusing on outcomes as patient reported outcomes, lung function and exercise tolerance. On the contrary, only scant and partial data are available for inflammatory biomarkers. These clearly represent the most interesting target for future development in diagnosis and clinical management of asthma, particularly in view of the several biologic drugs in the pipeline, for which regulatory agencies will soon require personalised proof of efficacy and treatment response predictors.

          Abstract

          Minimal clinically important difference (MCID) cut-offs in asthma are validated for patient reported outcomes and lung function, but not for inflammatory biomarkers. MCID represents a key target for future development in asthma management . http://bit.ly/33hcWIe

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          Most cited references110

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          ATS statement: guidelines for the six-minute walk test.

          (2002)
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            Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010

            Non-fatal health outcomes from diseases and injuries are a crucial consideration in the promotion and monitoring of individual and population health. The Global Burden of Disease (GBD) studies done in 1990 and 2000 have been the only studies to quantify non-fatal health outcomes across an exhaustive set of disorders at the global and regional level. Neither effort quantified uncertainty in prevalence or years lived with disability (YLDs). Of the 291 diseases and injuries in the GBD cause list, 289 cause disability. For 1160 sequelae of the 289 diseases and injuries, we undertook a systematic analysis of prevalence, incidence, remission, duration, and excess mortality. Sources included published studies, case notification, population-based cancer registries, other disease registries, antenatal clinic serosurveillance, hospital discharge data, ambulatory care data, household surveys, other surveys, and cohort studies. For most sequelae, we used a Bayesian meta-regression method, DisMod-MR, designed to address key limitations in descriptive epidemiological data, including missing data, inconsistency, and large methodological variation between data sources. For some disorders, we used natural history models, geospatial models, back-calculation models (models calculating incidence from population mortality rates and case fatality), or registration completeness models (models adjusting for incomplete registration with health-system access and other covariates). Disability weights for 220 unique health states were used to capture the severity of health loss. YLDs by cause at age, sex, country, and year levels were adjusted for comorbidity with simulation methods. We included uncertainty estimates at all stages of the analysis. Global prevalence for all ages combined in 2010 across the 1160 sequelae ranged from fewer than one case per 1 million people to 350,000 cases per 1 million people. Prevalence and severity of health loss were weakly correlated (correlation coefficient -0·37). In 2010, there were 777 million YLDs from all causes, up from 583 million in 1990. The main contributors to global YLDs were mental and behavioural disorders, musculoskeletal disorders, and diabetes or endocrine diseases. The leading specific causes of YLDs were much the same in 2010 as they were in 1990: low back pain, major depressive disorder, iron-deficiency anaemia, neck pain, chronic obstructive pulmonary disease, anxiety disorders, migraine, diabetes, and falls. Age-specific prevalence of YLDs increased with age in all regions and has decreased slightly from 1990 to 2010. Regional patterns of the leading causes of YLDs were more similar compared with years of life lost due to premature mortality. Neglected tropical diseases, HIV/AIDS, tuberculosis, malaria, and anaemia were important causes of YLDs in sub-Saharan Africa. Rates of YLDs per 100,000 people have remained largely constant over time but rise steadily with age. Population growth and ageing have increased YLD numbers and crude rates over the past two decades. Prevalences of the most common causes of YLDs, such as mental and behavioural disorders and musculoskeletal disorders, have not decreased. Health systems will need to address the needs of the rising numbers of individuals with a range of disorders that largely cause disability but not mortality. Quantification of the burden of non-fatal health outcomes will be crucial to understand how well health systems are responding to these challenges. Effective and affordable strategies to deal with this rising burden are an urgent priority for health systems in most parts of the world. Bill & Melinda Gates Foundation. Copyright © 2012 Elsevier Ltd. All rights reserved.
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              Measurement of health status. Ascertaining the minimal clinically important difference.

              In recent years quality of life instruments have been featured as primary outcomes in many randomized trials. One of the challenges facing the investigator using such measures is determining the significance of any differences observed, and communicating that significance to clinicians who will be applying the trial results. We have developed an approach to elucidating the significance of changes in score in quality of life instruments by comparing them to global ratings of change. Using this approach we have established a plausible range within which the minimal clinically important difference (MCID) falls. In three studies in which instruments measuring dyspnea, fatigue, and emotional function in patients with chronic heart and lung disease were applied the MCID was represented by mean change in score of approximately 0.5 per item, when responses were presented on a seven point Likert scale. Furthermore, we have established ranges for changes in questionnaire scores that correspond to moderate and large changes in the domains of interest. This information will be useful in interpreting questionnaire scores, both in individuals and in groups of patients participating in controlled trials, and in the planning of new trials.
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                Author and article information

                Journal
                Eur Respir Rev
                Eur Respir Rev
                ERR
                errev
                European Respiratory Review
                European Respiratory Society
                0905-9180
                1600-0617
                30 June 2020
                03 June 2020
                : 29
                : 156
                : 190137
                Affiliations
                [1 ]National Heart and Lung Institute, Royal Brompton Hospital & Imperial College London, London, UK
                [2 ]UOC Pneumologia, Istituto di Medicina Interna, F. Policlinico Gemelli IRCCS, Università Cattolica del Sacro Cuore, Rome, Italy
                [3 ]Allergy and Respiratory diseases, University of Genoa, Dept of Internal Medicine (DiMI), Ospedale Policlinico San Martino, Genoa, Italy
                [4 ]Dept of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy
                [5 ]Dept of Medicine, University of Verona, Verona, Italy
                [6 ]Asthma Center and Allergy Unit, Verona University Hospital, Verona, Italy
                [7 ]Division of Respiratory Diseases, Dept of Medical and Surgical Sciences, University of Foggia, Italy
                [8 ]Section of Internal and Cardiorespiratory Medicine, Dept of Medical Sciences, University of Ferrara, Ferrara, Italy
                [9 ]Division of Respiratory Diseases, IRCCS Policlinico San Matteo Foundation - Dept of Internal Medicine and Therapeutics, University of Pavia, Pavia, Italy
                [10 ]Dept of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
                [11 ]Personalized Medicine, Asthma and Allergy - Humanitas Research Hospital, Rozzano, Italy
                [12 ]Departmental Unit of Pneumology & Allergology, Istituto Ospedaliero Fondazione Poliambulanza, Brescia, Italy
                [13 ]Dept of Cardiovascular, Respiratory, Nephrology, Anaesthesiology and Geriatric Science, “Sapienza” University, Rome, Italy
                [14 ]Division of Pulmonology, S Corona Hospital, Savona, Italy
                [15 ]AOUP Policlinico Universitario, DIBIMIS, Università di Palermo, Palermo, Italy
                Author notes
                Marco Caminati, Dept of Medicine, University of Verona, Piazzale Stefani 1, 37126 Verona, Italy. E-mail: ma.caminati@ 123456gmail.com
                Author information
                https://orcid.org/0000-0001-9123-1389
                https://orcid.org/0000-0002-4517-1749
                https://orcid.org/0000-0001-6400-6573
                Article
                ERR-0137-2019
                10.1183/16000617.0137-2019
                9488652
                32499305
                48509b38-ef16-4c81-9d6f-04289a8cc73f
                Copyright ©ERS 2020.

                This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial Licence 4.0.

                History
                : 25 October 2019
                : 09 March 2020
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