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Record W4226102981

Real World Biologic Use and Switch Patterns in Severe Asthma: Data from the International Severe Asthma Registry and the US CHRONICLE Study

2022· article· en· W4226102981 on OpenAlexaffabout
Andrew Menzies‐Gow, Claire McBrien, Bindhu Unni, Celeste Porsbjerg, Mona Al‐Ahmad, Christopher S. Ambrose, Karin Dahl Assing, Anna von Bülow, John Busby, Borja G. Cosío, J. Mark FitzGerald, Esther García Gil, Susanne Hansen, Liam G. Heaney, Mark Hew, David J. Jackson, Maria Kallieri, Stelios Loukides, Njira Lugogo, Andriana Ι. Papaioannou, Désirée Larenas‐Linnemann, Wendy C. Moore, Luis Pérez de Llano, Linda Makowska Rasmussen, Johannes Martin Schmid, Salman Siddiqui, Marianna Alacqua, Trung N. Tran, Charlotte Suppli Ulrik, John W. Upham, Eileen Wang, Lakmini Bulathsinhala, Victoria Carter, Isha Chaudhry, Neva Eleangovan, Ruth Murray, Chris Price, David Price

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2022
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsVancouver Coastal Health Research InstituteVancouver Coastal Health
Fundersnot available
KeywordsMedicineAsthmaIntensive care medicineFamily medicineInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Andrew N Menzies-Gow,1 Claire McBrien,2 Bindhu Unni,3 Celeste M Porsbjerg,4 Mona Al-Ahmad,5 Christopher S Ambrose,6 Karin Dahl Assing,7 Anna von Bülow,4 John Busby,8 Borja G Cosio,9 J Mark FitzGerald,10 Esther Garcia Gil,11 Susanne Hansen,12 Liam G aHeaney,8 Mark Hew,13,14 David J Jackson,15,16 Maria Kallieri,17 Stelios Loukides,17 Njira L Lugogo,18 Andriana I Papaioannou,17 Désirée Larenas-Linnemann,19 Wendy C Moore,20 Luis A Perez-de-Llano,21 Linda M Rasmussen,22 Johannes M Schmid,23 Salman Siddiqui,24 Marianna Alacqua,25 Trung N Tran,6 Charlotte Suppli Ulrik,26 John W Upham,27 Eileen Wang,28,29 Lakmini Bulathsinhala,3,30 Victoria A Carter,3,30 Isha Chaudhry,3,30 Neva Eleangovan,3,30 Ruth B Murray,3,30 Chris A Price,3,30 David B Price3,30,31 1UK Severe Asthma Network and National Registry, Royal Brompton & Harefield Hospitals, London, UK; 2Kingston Hospital, London, UK; 3Observational and Pragmatic Research Institute, Singapore, Singapore; 4Respiratory Research Unit, Bispebjerg University Hospital, Copenhagen, Denmark; 5Al-Rashed Allergy Center, Ministry of Health, Microbiology Department, Faculty of Medicine, Kuwait University, Kuwait, Kuwait; 6AstraZeneca, Gaithersburg, MD, USA; 7Department of Respiratory Medicine, Aalborg University Hospital, Aalborg, Denmark; 8UK Severe Asthma Network and National Registry, Queen’s University Belfast, Belfast, Northern Ireland; 9Son Espases University Hospital-IdISBa-Ciberes, Mallorca, Spain; 10The Centre for Lung Health, Vancouver Coastal Health Research Institute, UBC, Vancouver, Canada; 11AstraZeneca, Barcelona, Spain; 12Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark; 13Allergy, Asthma & Clinical Immunology Service, Alfred Health, Melbourne, Australia; 14Public Health and Preventive Medicine, Monash University, Melbourne, Australia; 15UK Severe Asthma Network andNational Registry, Guy’s and St Thomas’ NHS Trust, London, UK; 16School of Immunology & Microbial Sciences, King’s College London, London, UK; 17 2nd Respiratory Medicine Department, National and Kapodistrian University of Athens Medical School, Attikon University Hospital, Athens, Greece; 18Department of Medicine, Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, MI, USA; 19Directora Centro de Excelencia en Asma y Alergia, Hospital Médica Sur, Ciudad de México, Mexico; 20Pulmonary, Critical Care, Allergy, and Immunologic Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA; 21Department of Respiratory Medicine, Hospital Universitario Lucus Augusti, Lugo, Spain; 22Allergy Clinic, Department of Dermato-Allergology, Gentofte Hospital, Copenhagen, Denmark; 23University Hospital of Aarhus, Aarhus, Denmark; 24University of Leicester, Department of Respiratory Sciences & NIHR Leicester Biomedical Research Centre (Respiratory Theme), Leicester, UK; 25AstraZeneca, Cambridge, UK; 26Department of Respiratory Medicine, Copenhagen University Hospital-Hvidovre, Hvidovre, Denmark; 27Diamantina Institute & PA-Southside Clinical Unit, The University of Queensland, Brisbane, Australia; 28Division of Allergy & Clinical Immunology, Department of Medicine, National Jewish Health, Denver, CO, USA; 29Division of Allergy & Clinical Immunology, Department of Internal Medicine, University of Colorado School of Medicine, Aurora, CO, USA; 30Optimum Patient Care, Cambridge, UK; 31Centre of Academic Primary Care, Division of Applied Health Sciences, University of Aberdeen, Aberdeen, UKCorrespondence: David B PriceObservational and Pragmatic Research Institute, 22 Sin Ming Lane, #06 Midview City, Singapore, 573969 Tel +65 3105 1489Email dprice@opri.sgIntroduction: International registries provide opportunities to describe use of biologics for treating severe asthma in current clinical practice. Our aims were to describe real-life global patterns of biologic use (continuation, switches, and discontinuations) for severe asthma, elucidate reasons underlying these patterns, and examine associated patient-level factors.Methods: This was a historical cohort study including adults with severe asthma enrolled into the International Severe Asthma Registry (ISAR; http://isaregistries.org, 2015– 2020) or the CHRONICLE Study (2018– 2020) and treated with a biologic. Eleven countries were included (Bulgaria, Canada, Denmark, Greece, Italy, Japan, Kuwait, South Korea, Spain, UK, and USA). Biologic utilization patterns were defined: 1) continuing initial biologic; 2) stopping biologic treatment; or 3) switching to another biologic. Reasons for discontinuation/switching were recorded and comparisons drawn between groups.Results: A total of 3531 patients were included. Omalizumab was the most common initial biologic in 2015 (88.2%) and benralizumab in 2019 (29.6%). Most patients (79%; 2791/3531) continued their first biologic; 10.2% (356/3531) stopped; 10.8% (384/3531) switched. The most frequent first switch was from omalizumab to an anti–IL-5/5R (49.6%; 187/377). The most common subsequent switch was from one anti–IL-5/5R to another (44.4%; 20/45). Insufficient efficacy and/or adverse effects were the most frequent reasons for stopping/switching. Patients who stopped/switched were more likely to have a higher baseline blood eosinophil count and exacerbation rate, lower lung function, and greater health care resource utilization.Conclusion: The description of real-life patterns of continuing, stopping, or switching biologics enhances our understanding of global biologic use. Prospective studies involving structured switching criteria could ascertain optimal strategies to identify patients who may benefit from switching.Keywords: severe asthma, biologics, prescribing, cohort study, management, international

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0030.005
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.211
GPT teacher head0.494
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations83
Published2022
Admission routes2
Has abstractyes

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