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      Clinical remission in severe asthma with biologic therapy: an analysis from the UK Severe Asthma Registry

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          Abstract

          Background

          Novel biologic therapies have revolutionised the management of severe asthma with more ambitious treatment aims. Here we analyse the definition of clinical remission as a suggested treatment goal and consider the characteristics associated with clinical remission in a large, real-world severe asthma cohort.

          Methods

          This was a retrospective analysis of severe asthma patients registered in the UK Severe Asthma Registry (UKSAR) who met strict national access criteria for biologics. Patients had a pre-biologics baseline assessment and annual review. The primary definition of clinical remission applied included Asthma Control Questionnaire (ACQ)-5 <1.5 and no oral corticosteroids for disease control and forced expiratory volume in 1 s above lower limit of normal or no more than 100 mL less than baseline.

          Results

          18.3% of patients achieved the primary definition of remission. The adjusted odds of remission on biologic therapy were 7.44 (95% CI 1.73–31.95)-fold higher in patients with type 2 (T2)-high biomarkers. The adjusted odds of remission were lower in patients who were female (OR 0.61, 95% CI 0.45–0.93), obese (OR 0.49, 95% CI 0.24–0.65) or had ACQ-5 ≥1.5 (OR 0.19, 95% CI 0.12–0.31) pre-biologic therapy. The likelihood of remission reduced by 14% (95% CI 0.76–0.97) for every 10-year increase in disease duration. 12–21% of the cohort attained clinical remission depending on the definition applied; most of those who did not achieve remission failed to meet multiple criteria.

          Conclusions

          18.3% of patients achieved the primary definition of clinical remission. Remission was more likely in T2-high biomarker patients with shorter duration of disease and less comorbidity. Further research on the optimum time to commence biologics in severe asthma is required.

          Tweetable abstract

          Analysis of a real-world severe asthma registry shows clinical remission rates of 18%; associated pre-biologic characteristics include male sex, never smoking, BMI <30 kg·m −2, shorter disease duration, T2-high biomarkers and lower symptom burden https://bit.ly/46JLeDb

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          Most cited references43

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          Multi-ethnic reference values for spirometry for the 3-95-yr age range: the global lung function 2012 equations.

          The aim of the Task Force was to derive continuous prediction equations and their lower limits of normal for spirometric indices, which are applicable globally. Over 160,000 data points from 72 centres in 33 countries were shared with the European Respiratory Society Global Lung Function Initiative. Eliminating data that could not be used (mostly missing ethnic group, some outliers) left 97,759 records of healthy nonsmokers (55.3% females) aged 2.5-95 yrs. Lung function data were collated and prediction equations derived using the LMS method, which allows simultaneous modelling of the mean (mu), the coefficient of variation (sigma) and skewness (lambda) of a distribution family. After discarding 23,572 records, mostly because they could not be combined with other ethnic or geographic groups, reference equations were derived for healthy individuals aged 3-95 yrs for Caucasians (n=57,395), African-Americans (n=3,545), and North (n=4,992) and South East Asians (n=8,255). Forced expiratory value in 1 s (FEV(1)) and forced vital capacity (FVC) between ethnic groups differed proportionally from that in Caucasians, such that FEV(1)/FVC remained virtually independent of ethnic group. For individuals not represented by these four groups, or of mixed ethnic origins, a composite equation taken as the average of the above equations is provided to facilitate interpretation until a more appropriate solution is developed. Spirometric prediction equations for the 3-95-age range are now available that include appropriate age-dependent lower limits of normal. They can be applied globally to different ethnic groups. Additional data from the Indian subcontinent and Arabic, Polynesian and Latin American countries, as well as Africa will further improve these equations in the future.
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            International ERS/ATS guidelines on definition, evaluation and treatment of severe asthma.

            Severe or therapy-resistant asthma is increasingly recognised as a major unmet need. A Task Force, supported by the European Respiratory Society and American Thoracic Society, reviewed the definition and provided recommendations and guidelines on the evaluation and treatment of severe asthma in children and adults. A literature review was performed, followed by discussion by an expert committee according to the GRADE (Grading of Recommendations, Assessment, Development and Evaluation) approach for development of specific clinical recommendations. When the diagnosis of asthma is confirmed and comorbidities addressed, severe asthma is defined as asthma that requires treatment with high dose inhaled corticosteroids plus a second controller and/or systemic corticosteroids to prevent it from becoming "uncontrolled" or that remains "uncontrolled" despite this therapy. Severe asthma is a heterogeneous condition consisting of phenotypes such as eosinophilic asthma. Specific recommendations on the use of sputum eosinophil count and exhaled nitric oxide to guide therapy, as well as treatment with anti-IgE antibody, methotrexate, macrolide antibiotics, antifungal agents and bronchial thermoplasty are provided. Coordinated research efforts for improved phenotyping will provide safe and effective biomarker-driven approaches to severe asthma therapy.
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              Overadjustment bias and unnecessary adjustment in epidemiologic studies.

              Overadjustment is defined inconsistently. This term is meant to describe control (eg, by regression adjustment, stratification, or restriction) for a variable that either increases net bias or decreases precision without affecting bias. We define overadjustment bias as control for an intermediate variable (or a descending proxy for an intermediate variable) on a causal path from exposure to outcome. We define unnecessary adjustment as control for a variable that does not affect bias of the causal relation between exposure and outcome but may affect its precision. We use causal diagrams and an empirical example (the effect of maternal smoking on neonatal mortality) to illustrate and clarify the definition of overadjustment bias, and to distinguish overadjustment bias from unnecessary adjustment. Using simulations, we quantify the amount of bias associated with overadjustment. Moreover, we show that this bias is based on a different causal structure from confounding or selection biases. Overadjustment bias is not a finite sample bias, while inefficiencies due to control for unnecessary variables are a function of sample size.
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                Author and article information

                Journal
                Eur Respir J
                Eur Respir J
                ERJ
                erj
                The European Respiratory Journal
                European Respiratory Society
                0903-1936
                1399-3003
                December 2023
                14 December 2023
                : 62
                : 6
                : 2300819
                Affiliations
                [1 ]Wellcome Wolfson Centre for Experimental Medicine, School of Medicine, Dentistry and Biomedical Sciences, Queen's University, Belfast, UK
                [2 ]Belfast Health and Social Care NHS Trust, Belfast, UK
                [3 ]Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen's University, Belfast, UK
                [4 ]Royal Brompton and Harefield Hospitals, London, UK
                [5 ]Guy's Severe Asthma Centre, Guy's Hospital, School of Immunology and Microbial Sciences, King's College London, London, UK
                [6 ]University of Birmingham and Heartlands Hospital, Birmingham, UK
                [7 ]Department of Respiratory Medicine, University Hospitals Plymouth NHS Trust, Derriford Hospital, Plymouth, UK
                [8 ]Royal Liverpool University Hospital, Liverpool, UK
                [9 ]The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
                [10 ]NHS Greater Glasgow and Clyde Health Board, Gartnavel Hospital, Glasgow, UK
                [11 ]Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
                [12 ]Academic Respiratory Unit, University of Bristol, Bristol, UK
                [13 ]University Hospitals of Derby and Burton NHS Foundation Trust, Derby, UK
                [14 ]Portsmouth Hospitals NHS Trust, Portsmouth, UK
                Author notes
                Corresponding author: P. Jane McDowell ( janemcdowell@ 123456doctors.org.uk )
                Author information
                https://orcid.org/0000-0003-2063-7992
                https://orcid.org/0000-0003-4805-5759
                Article
                ERJ-00819-2023
                10.1183/13993003.00819-2023
                10719453
                37857423
                b1ff6ba1-53a1-42ec-ba3f-8477a602dc73
                Copyright ©The authors 2023.

                This version is distributed under the terms of the Creative Commons Attribution Licence 4.0.

                History
                : 16 May 2023
                : 05 October 2023
                Categories
                Original Research Articles
                Asthma
                2

                Respiratory medicine
                Respiratory medicine

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