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dc.contributor.authorMatheson, Melanie C-
dc.contributor.authorBowatte, Gayan-
dc.contributor.authorPerret, Jennifer L-
dc.contributor.authorLowe, Adrian J-
dc.contributor.authorSenaratna, Chamara V-
dc.contributor.authorHall, Graham L-
dc.contributor.authorde Klerk, Nick-
dc.contributor.authorKeogh, Louise A-
dc.contributor.authorMcDonald, Christine F-
dc.contributor.authorWaidyatillake, Nilakshi T-
dc.contributor.authorSly, Peter D-
dc.contributor.authorJarvis, Deborah-
dc.contributor.authorAbramson, Michael J-
dc.contributor.authorLodge, Caroline J-
dc.contributor.authorDharmage, Shyamali C-
dc.identifier.citationInternational Journal of Chronic Obstructive Pulmonary Disease 2018; 13: 1927-1935en_US
dc.description.abstractEarly identification of people at risk of developing COPD is crucial for implementing preventive strategies. We aimed to systematically review and assess the performance of all published models that predicted development of COPD. A search was conducted to identify studies that developed a prediction model for COPD development. The Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies was followed when extracting data and appraising the selected studies. Of the 4,481 records identified, 30 articles were selected for full-text review, and only four of these were eligible to be included in the review. The only consistent predictor across all four models was a measure of smoking. Sex and age were used in most models; however, other factors varied widely. Two of the models had good ability to discriminate between people who were correctly or incorrectly classified as at risk of developing COPD. Overall none of the models were particularly useful in accurately predicting future risk of COPD, nor were they good at ruling out future risk of COPD. Further studies are needed to develop new prediction models and robustly validate them in external cohorts.en_US
dc.subjectearly detectionen_US
dc.subjectpredictors and risk prediction modelsen_US
dc.titlePrediction models for the development of COPD: a systematic review.en_US
dc.typeJournal Articleen_US
dc.identifier.journaltitleInternational Journal of Chronic Obstructive Pulmonary Diseaseen_US
dc.identifier.affiliationAllergy and Lung Health Unit, Centre for Epidemiology and Biostatistics, School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australiaen_US
dc.identifier.affiliationSchool of Public Health & Preventive Medicine, Monash University, Melbourne, Victoria, Australiaen_US
dc.identifier.affiliationMurdoch Children's Research Institute, Melbourne, Victoria, Australiaen_US
dc.identifier.affiliationNational Institute of Fundamental Studies, Kandy, Sri Lankaen_US
dc.identifier.affiliationDepartment of Community Medicine, University of Sri Jayewardenepura, Nugegoda, Sri Lankaen_US
dc.identifier.affiliationTelethon Kids Institute, Perth, WA, Australiaen_US
dc.identifier.affiliationSchool of Physiotherapy and Exercise Science, Curtin University, Perth, WA, Australiaen_US
dc.identifier.affiliationCentre of Child Health Research, University of Western Australia, Perth, WA, Australiaen_US
dc.identifier.affiliationCentre for Health Equity, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australiaen_US
dc.identifier.affiliationChild Health Research Centre, The University of Queensland, Brisbane, QLD, Australiaen_US
dc.identifier.affiliationMRC-PHE Centre for Environment and Health, Imperial College London, London, UKen_US
dc.identifier.affiliationPopulation Health and Occupational Diseases, National Heart and Lung Institute, Imperial College London, London, UKen_US
dc.identifier.affiliationInstitute for Breathing and Sleepen_US
dc.identifier.affiliationRespiratory and Sleep Medicineen_US
dc.type.austinJournal Article-, Christine F
item.openairetypeJournal Article-
item.fulltextWith Fulltext-
item.openairecristype for Breathing and Sleep- for Breathing and Sleep- and Sleep Medicine-
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