Amin Adibi1, Don D Sin2, Abdollah Safari1, Kate M Johnson1, Shawn D Aaron3, J Mark FitzGerald4, Mohsen Sadatsafavi5. 1. Respiratory Evaluation Sciences Program, Collaboration for Outcomes Research and Evaluation, Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC, Canada. 2. Division of Respiratory Medicine, Department of Medicine, The UBC Centre for Heart Lung Innovation, St. Paul's Hospital, University of British Columbia, Vancouver, BC, Canada. Electronic address: don.sin@hli.ubc.ca. 3. Ottawa Hospital Research Institute, University of Ottawa, Ontario, Canada. 4. Institute for Heart and Lung Health, Division of Respiratory Medicine, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada. 5. Respiratory Evaluation Sciences Program, Collaboration for Outcomes Research and Evaluation, Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC, Canada; Institute for Heart and Lung Health, Division of Respiratory Medicine, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada; Centre for Clinical Epidemiology and Evaluation, University of British Columbia, Vancouver, BC, Canada.
Abstract
BACKGROUND: Accurate prediction of exacerbation risk enables personalised care for patients with chronic obstructive pulmonary disease (COPD). We developed and validated a generalisable model to predict individualised rate and severity of COPD exacerbations. METHODS: In this risk modelling study, we pooled data from three COPD trials on patients with a history of exacerbations. We developed a mixed-effect model to predict exacerbations over 1 year. Severe exacerbations were those requiring inpatient care. Predictors were history of exacerbations, age, sex, body-mass index, smoking status, domiciliary oxygen therapy, lung function, symptom burden, and current medication use. Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points (ECLIPSE), a multicentre cohort study, was used for external validation. RESULTS: The development dataset included 2380 patients, 1373 (58%) of whom were men. Mean age was 64·7 years (SD 8·8). Mean exacerbation rate was 1·42 events per year and 0·29 events per year were severe. When validated against all patients with COPD in ECLIPSE (mean exacerbation rate was 1·20 events per year, 0·27 events per year were severe), the area-under-curve (AUC) was 0·81 (95% CI 0·79-0·83) for at least two exacerbations and 0·77 (95% CI 0·74-0·80) for at least one severe exacerbation. Predicted exacerbation and observed exacerbation rates were similar (1·31 events per year for all exacerbations and 0·25 events per year for severe exacerbations vs 1·20 events per year and 0·27 events per year). In ECLIPSE, in patients with previous exacerbation history (mean exacerbation rate was 1·82 events per year, 0·40 events per year were severe), AUC was 0·73 (95% CI 0·70-0·76) for two or more exacerbations and 0·74 (95% CI 0·70-0·78) for at least one severe exacerbation. Calibration was accurate for severe exacerbations (predicted 0·37 events per year vs observed 0·40 events per year) and all exacerbations (predicted 1·80 events per year vs observed 1·82 events per year). INTERPRETATION: This model can be used as a decision tool to personalise COPD treatment and prevent exacerbations. FUNDING: Canadian Institutes of Health Research.
BACKGROUND: Accurate prediction of exacerbation risk enables personalised care for patients with chronic obstructive pulmonary disease (COPD). We developed and validated a generalisable model to predict individualised rate and severity of COPD exacerbations. METHODS: In this risk modelling study, we pooled data from three COPD trials on patients with a history of exacerbations. We developed a mixed-effect model to predict exacerbations over 1 year. Severe exacerbations were those requiring inpatient care. Predictors were history of exacerbations, age, sex, body-mass index, smoking status, domiciliary oxygen therapy, lung function, symptom burden, and current medication use. Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points (ECLIPSE), a multicentre cohort study, was used for external validation. RESULTS: The development dataset included 2380 patients, 1373 (58%) of whom were men. Mean age was 64·7 years (SD 8·8). Mean exacerbation rate was 1·42 events per year and 0·29 events per year were severe. When validated against all patients with COPD in ECLIPSE (mean exacerbation rate was 1·20 events per year, 0·27 events per year were severe), the area-under-curve (AUC) was 0·81 (95% CI 0·79-0·83) for at least two exacerbations and 0·77 (95% CI 0·74-0·80) for at least one severe exacerbation. Predicted exacerbation and observed exacerbation rates were similar (1·31 events per year for all exacerbations and 0·25 events per year for severe exacerbations vs 1·20 events per year and 0·27 events per year). In ECLIPSE, in patients with previous exacerbation history (mean exacerbation rate was 1·82 events per year, 0·40 events per year were severe), AUC was 0·73 (95% CI 0·70-0·76) for two or more exacerbations and 0·74 (95% CI 0·70-0·78) for at least one severe exacerbation. Calibration was accurate for severe exacerbations (predicted 0·37 events per year vs observed 0·40 events per year) and all exacerbations (predicted 1·80 events per year vs observed 1·82 events per year). INTERPRETATION: This model can be used as a decision tool to personalise COPD treatment and prevent exacerbations. FUNDING: Canadian Institutes of Health Research.
Authors: Mohsen Sadatsafavi; James McCormack; John Petkau; Larry D Lynd; Tae Yoon Lee; Don D Sin Journal: Eur Respir J Date: 2021-02-11 Impact factor: 16.671