Adult Severe Asthma Registries: A Global and Growing Inventory
Bibliographic record
Abstract
Breda Cushen,1,* Mariko Siyue Koh,2,* Trung N Tran,3 Neil Martin,3,4 Ruth Murray,5 Thendral Uthaman,6 Celine Yun Yi Goh,5,6 Rebecca Vella,7 Neva Eleangovan,5,6 Lakmini Bulathsinhala,5,6 Jorge F Maspero,8,9 Matthew J Peters,10 Florence Schleich,11 Paulo Pitrez,12 George Christoff,13 Mohsen Sadatsafavi,14 Carlos A Torres-Duque,15,16 Celeste Porsbjerg,17 Alan Altraja,18 Lauri Lehtimäki,19 Arnaud Bourdin,20 Christian Taube,21 Nikolaos G Papadopoulos,22,23 Csoma Zsuzsanna,24 Unnur Björnsdóttir,25 Sundeep Salvi,26 Enrico Heffler,27 Takashi Iwanaga,28 Mona al-Ahmad,29 Désirée Larenas-Linnemann,30 Job FM van Boven,31 Bernt Bøgvald Aarli,32,33 Piotr Kuna,34 Cláudia Chaves Loureiro,35,36 Riyad Al-lehebi,37 Jae Ha Lee,38 Nuria Marina,39 Leif Bjermer,40 Chau-Chyun Sheu,41,42 Bassam Mahboub,43 John Busby,44 Andrew Menzies-Gow,45 Eileen Wang,46 David B Price5,6,47 On behalf of ISAR Inventory Study Group1Department of Respiratory Medicine, Beaumont Hospital, Dublin, Ireland; 2Department of Respiratory and Critical Care Medicine, Singapore General Hospital, Singapore, Singapore; 3AstraZeneca, Gaithersburg, MD, USA; 4Department of Respiratory Medicine, University of Leicester, Leicester, UK; 5Optimum Patient Care Global, Cambridge, UK; 6Observational Pragmatic Research Institute, Singapore, Singapore; 7Optimum Patient Care, Brisbane, Queensland, Australia; 8Clinical Research for Allergy and Respiratory Medicine, CIDEA Foundation, Buenos Aires, Argentina; 9University Career of Specialists in Allergy and Clinical Immunology at the Buenos Aires University School of Medicine, Buenos Aires, Argentina; 10Department of Thoracic Medicine, Concord Hospital, Sydney, Australia; 11CHU Sart-Tilman, GIGA I3, University of Liege, Liège, Wallonia, Belgium; 12Pulmonology Division, Hospital Santa Casa de Porto Alegre, Porto Alegre, Brazil; 13Faculty of Public Health, Medical University, Sofia, Bulgaria; 14Respiratory Evaluation Sciences Program, Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, Canada; 15CINEUMO, Respiratory Research Center, Fundación Neumológica Colombiana, Bogotá, Colombia; 16Universidad de La Sabana, Chia, Colombia; 17Department of Respiratory Medicine and Infectious Diseases, Research Unit, Bispebjerg Hospital, Copenhagen, Denmark; 18Department of Pulmonology, University of Tartu and Lung Clinic, Tartu University Hospital, Tartu, Estonia; 19Allergy Centre, Tampere University Hospital, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland; 20PhyMedExp, Univ Montpellier, CNRS, INSERM, CHU Montpellier, Montpellier, France; 21Department of Pulmonary Medicine, University Medical Center Essen-Ruhrlandklinik, Essen, Germany; 22Division of Infection, Immunity & Respiratory Medicine, University of Manchester, Manchester, UK; 23Allergy Department, 2nd Pediatric Clinic, University of Athens, Athens, Greece; 24Asthma Outpatient Clinic, National Koranyi Institute for Pulmonology, Budapest, Hungary; 25Department of Allergy and Respiratory Medicine, University Hospital, Reykjavik, Iceland; 26Pulmocare Research and Education Foundation, Pune, India; 27Personalized Medicine, Asthma and Allergy, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy; 28Kindai University Hospital, Osakasayama, Japan; 29Microbiology Department, College of Medicine, Kuwait University, Kuwait, Al-Rashed Allergy Center, Ministry of Health, Kuwait City, Kuwait; 30Centro de Excelencia en Asma y Alergia, Hospital Médica Sur, Ciudad de México, Mexico; 31University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD (GRIAC), Department of Clinical Pharmacy & Pharmacology, Groningen, the Netherlands; 32Department of Thoracic Medicine, Haukeland University Hospital, Bergen, Norway; 33Department of Clinical Science, University of Bergen, Bergen, Norway; 34Division of Internal Medicine Asthma and Allergy, Medical University of Lodz, Lodz, Poland; 35Pneumology Unit, Hospitais da Universidade de Coimbra, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal; 36Centre of Pneumology, Faculty of Medicine, University of Coimbra, Coimbra, Portugal; 37Department of Pulmonology, King Fahad Medical City, Riyadh, Saudi Arabia, Alfaisal University, Riyadh, Saudi Arabia; 38Division of Pulmonology and Critical Care Medicine, Department of Internal Medicine, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea; 39Pneumology Service, Biocruces, Cruces University Hospital, Barakaldo, Spain; 40Respiratory Medicine and Allergology, Department of Clinical Sciences, Skåne University Hospital, Lund University, Lund, Sweden; 41Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan; 42Department of Internal Medicine, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan; 43Rashid Hospital, Dubai Health Authority (DHA), Dubai, United Arab Emirates; 44Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen’s University Belfast, Belfast, Northern Ireland, UK; 45Lung Division, Royal Brompton & Harefield Hospital, London, UK; 46Division of Allergy and Clinical Immunology, Department of Medicine, National Jewish Health and University of Colorado School of Medicine, Denver and Aurora, CO, USA; 47Centre of Academic Primary Care, Division of Applied Health Sciences, University of Aberdeen, Aberdeen, Scotland, UK*These authors contributed equally to this workCorrespondence: David B Price, Observational and Pragmatic Research Institute (OPRI) Pte Ltd, 22 Sin Ming Lane, #06-76, Midview City, 573969, Singapore, Tel +65 3105 1489, Email dprice@opri.sgAim: The International Severe Asthma Registry (ISAR; http://isaregistries.org/) uses standardised variables to enable multi-country and adequately powered research in severe asthma. This study aims to look at the data countries within ISAR and non-ISAR countries reported collecting that enable global research that support individual country interests.Methods: Registries were identified by online searches and approaching severe asthma experts. Participating registries provided data collection specifications or confirmed variables collected. Core variables (results from ISAR’s Delphi study), steroid-related comorbidity variables, biologic safety variables (serious infection, anaphylaxis, and cancer), COVID-19 variables and additional variables (not belonging to the aforementioned categories) that registries reported collecting were summarised.Results: Of the 37 registries identified, 26 were ISAR affiliates and 11 non-ISAR affiliates. Twenty-five ISAR-registries and 4 non-ISAR registries reported collecting > 90% of the 65 core variables. Twenty-three registries reported collecting all optional steroid-related comorbidity variables. Twenty-nine registries reported collecting all optional safety variables. Ten registries reported collecting COVID-19 variables. Twenty-four registries reported collecting additional variables including data from asthma questionnaires (10 Asthma Control Questionnaire, 20 Asthma Control Test, 11 Asthma Quality of Life Questionnaire, and 4 EuroQol 5-dimension 5-level Questionnaire). Eight registries are linked to databases such as electronic medical records and national claims or disease databases.Conclusion: Standardised data collection has enabled individual severe asthma registries to collect unified data and increase statistical power for severe asthma research irrespective of ISAR affiliations.Keywords: Asia-Pacific, biologics, COVID-19, Europe, ISAR, International Severe Asthma Registry, oral corticosteroids, Registry, Middle East, Severe Asthma, Latin America, USA
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.014 | 0.019 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".