TY - JOUR T1 - Ten-year prediction model for post-bronchodilator airflow obstruction and early detection of COPD: development and validation in two middle-aged population-based cohorts JF - BMJ Open Respiratory Research JO - BMJ Open Resp Res DO - 10.1136/bmjresp-2021-001138 VL - 8 IS - 1 SP - e001138 AU - Jennifer L Perret AU - Don Vicendese AU - Koen Simons AU - Debbie L Jarvis AU - Adrian J Lowe AU - Caroline J Lodge AU - Dinh S Bui AU - Daniel Tan AU - John A Burgess AU - Bircan Erbas AU - Adrian Bickerstaffe AU - Kerry Hancock AU - Bruce R Thompson AU - Garun S Hamilton AU - Robert Adams AU - Geza P Benke AU - Paul S Thomas AU - Peter Frith AU - Christine F McDonald AU - Tony Blakely AU - Michael J Abramson AU - E Haydn Walters AU - Cosetta Minelli AU - Shyamali C Dharmage A2 - , Y1 - 2021/12/01 UR - http://bmjopenrespres.bmj.com/content/8/1/e001138.abstract N2 - 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.Data are available upon reasonable request. TAHS is a cohort study with data that has been prospectively collected since 1968 and will be an ongoing resource for future epidemiological analyses. Data collection protocols have been detailed in the TAHS cohort profile paper published in 2016 (Matheson et al 2016 doi: 10.1093/ije/dyw028). The raw data have not been made widely available, but expressions of interest can be discussed with the corresponding author, Dr J Perret, and/or principal investigator, Professor S Dharmage, on an individual basis. ECRHS is a cohort study with data that has been prospectively collected since 1990 and will be an ongoing resource for future epidemiological analyses. Data collection protocols are detailed at https://www.ecrhs.org/. The raw data have not been made widely available, but expressions of interest can be discussed with the principal investigator, Professor D Jarvis, on an individual basis. ER -