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Ten-year prediction model for post-bronchodilator airflow obstruction and early detection of COPD: Development and validation in two middle-aged population-based cohorts

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Perret, JL and Vicendese, D and Simons, K and Jarvis, DL and Lowe, AJ and Lodge, CJ and Bui, DS and Tan, D and Burgess, JA and Erbas, B and Bickerstaffe, A and Hancock, K and Thompson, BR and Hamilton, GS and Adams, R and Benke, GP and Thomas, PS and Frith, P and Mcdonald, CF and Blakely, T and Abramson, MJ and Walters, EH and Minelli, C and Dharmage, SC, TAHS and ECRHS Investigator Groups, Ten-year prediction model for post-bronchodilator airflow obstruction and early detection of COPD: Development and validation in two middle-aged population-based cohorts, BMJ Open Respiratory Research, 8, (1) pp. 1-12. ISSN 2052-4439 (2021) [Refereed Article]


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Author(s) (or their employer(s)) 2021 This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) http://creativecommons.org/licenses/by-nc/4.0/. license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial.

DOI: doi:10.1136/bmjresp-2021-001138

Abstract

Background: Classifying individuals at high chronic obstructive pulmonary disease (COPD)-risk creates opportunities for early COPD detection and active intervention.

Objective: To develop and validate a statistical model to predict 10-year probabilities of COPD defined by post-bronchodilator airflow obstruction (post-BD-AO; forced expiratory volume in 1 s/forced vital capacity<5th percentile).

Setting: General Caucasian populations from Australia and Europe, 10 and 27 centres, respectively.

Participants: For the development cohort, questionnaire data on respiratory symptoms, smoking, asthma, occupation and participant sex were from the Tasmanian Longitudinal Health Study (TAHS) participants at age 41-45 years (n=5729) who did not have self-reported COPD/emphysema at baseline but had post-BD spirometry and smoking status at age 51-55 years (n=2407). The validation cohort comprised participants from the European Community Respiratory Health Survey (ECRHS) II and III (n=5970), restricted to those of age 40-49 and 50-59 with complete questionnaire and spirometry/smoking data, respectively (n=1407).

Statistical method: Risk-prediction models were developed using randomForest then externally validated.

Results: Area under the receiver operating characteristic curve (AUCROC) of the final model was 80.8% (95% CI 80.0% to 81.6%), sensitivity 80.3% (77.7% to 82.9%), specificity 69.1% (68.7% to 69.5%), positive predictive value (PPV) 11.1% (10.3% to 11.9%) and negative predictive value (NPV) 98.7% (98.5% to 98.9%). The external validation was fair (AUCROC 75.6%), with the PPV increasing to 17.9% and NPV still 97.5% for adults aged 40-49 years with ≥1 respiratory symptom. To illustrate the model output using hypothetical case scenarios, a 43-year-old female unskilled worker who smoked 20 cigarettes/day for 30 years had a 27% predicted probability for post-BD-AO at age 53 if she continued to smoke. The predicted risk was 42% if she had coexistent active asthma, but only 4.5% if she had quit after age 43.

Conclusion: This novel and validated risk-prediction model could identify adults aged in their 40s at high 10-year COPD-risk in the general population with potential to facilitate active monitoring/intervention in predicted 'COPD cases' at a much earlier age.

Item Details

Item Type:Refereed Article
Keywords:COPD epidemiology, clinical epidemiology
Research Division:Biomedical and Clinical Sciences
Research Group:Cardiovascular medicine and haematology
Research Field:Respiratory diseases
Objective Division:Health
Objective Group:Clinical health
Objective Field:Prevention of human diseases and conditions
UTAS Author:Walters, EH (Professor Haydn Walters)
ID Code:152307
Year Published:2021
Web of Science® Times Cited:1
Deposited By:Menzies Institute for Medical Research
Deposited On:2022-08-17
Last Modified:2022-09-15
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