Skip to main navigation Skip to search Skip to main content

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

  • Jennifer L. Perret
  • , Don Vicendese
  • , Koen Simons
  • , Debbie L. Jarvis
  • , Adrian J. Lowe
  • , Caroline J. Lodge
  • , Dinh S. Bui
  • , Daniel Tan
  • , John A. Burgess
  • , Bircan Erbas
  • , Adrian Bickerstaffe
  • , Kerry Hancock
  • , Bruce R. Thompson
  • , Garun S. Hamilton
  • , Robert Adams
  • , Geza P. Benke
  • , Paul S. Thomas
  • , Peter Frith
  • , Christine F. Mcdonald
  • , Tony Blakely
  • Michael J. Abramson, E. Haydn Walters, Cosetta Minelli, Shyamali C. Dharmage, on behalf of the TAHS and ECRHS Investigator Groups

Research output: Contribution to journalArticleResearchpeer-review

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 (AUC ROC) 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 (AUC ROC 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.

Original languageEnglish
Article numbere001138
Number of pages12
JournalBMJ Open Respiratory Research
Volume8
Issue number1
DOIs
Publication statusPublished - Dec 2021

Keywords

  • clinical epidemiology
  • COPD epidemiology

Cite this