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. 2016 Oct 4;188(14):1004-1011.
doi: 10.1503/cmaj.151483. Epub 2016 Aug 2.

Individualized prediction of lung-function decline in chronic obstructive pulmonary disease

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Individualized prediction of lung-function decline in chronic obstructive pulmonary disease

Zafar Zafari et al. CMAJ. .

Abstract

Background: The rate of lung-function decline in chronic obstructive pulmonary disease (COPD) varies substantially among individuals. We sought to develop and validate an individualized prediction model for forced expiratory volume at 1 second (FEV1) in current smokers with mild-to-moderate COPD.

Methods: Using data from a large long-term clinical trial (the Lung Health Study), we derived mixed-effects regression models to predict future FEV1 values over 11 years according to clinical traits. We modelled heterogeneity by allowing regression coefficients to vary across individuals. Two independent cohorts with COPD were used for validating the equations.

Results: We used data from 5594 patients (mean age 48.4 yr, 63% men, mean baseline FEV1 2.75 L) to create the individualized prediction equations. There was significant between-individual variability in the rate of FEV1 decline, with the interval for the annual rate of decline that contained 95% of individuals being -124 to -15 mL/yr for smokers and -83 to 15 mL/yr for sustained quitters. Clinical variables in the final model explained 88% of variation around follow-up FEV1. The C statistic for predicting severity grades was 0.90. Prediction equations performed robustly in the 2 external data sets.

Interpretation: A substantial part of individual variation in FEV1 decline can be explained by easily measured clinical variables. The model developed in this work can be used for prediction of future lung health in patients with mild-to-moderate COPD.

Trial registration: Lung Health Study - ClinicalTrials.gov, no. NCT00000568; Pan-Canadian Early Detection of Lung Cancer Study - ClinicalTrials.gov, no. NCT00751660.

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Figures

Figure 1:
Figure 1:
Prediction results based on baseline FEV1 and clinical traits for an example patient (a 55-year-old man who is a continuous smoker, weight 75 kg, height 170 cm, baseline FEV1 2.75 L). A) Mean estimates and 95% prediction intervals for future FEV1 and B) 11-year prediction of GOLD grades if the patient continues smoking. C) Mean estimates and 95% prediction intervals for future FEV1 and D) 11-year prediction of GOLD grades if the patient stops smoking. This is an illustrative case only. The reader can use the online FEV1 calculator (http://resp.med.ubc.ca/software/ipress/epic/fev1pred) to estimate future FEV1 decline in patients with different clinical features. Note: COPD = chronic obstructive pulmonary disease, FEV1 = forced expiratory volume in 1 second.
Figure 2:
Figure 2:
Internal validation of the model in (A) LHS smokers (RMSE 0.24, actual 95% coverage probability 94%) and (B) LHS sustained quitters (RMSE 0.24, actual 95% coverage probability 93%). External validation of the model in (C) EUROSCOP smokers (EUROSCOP included only smokers) (RMSE 0.22, actual 95% coverage probability 91%), (D) PanCan smokers (RMSE 0.25, actual 95% coverage probability 90%) and (E) PanCan sustained quitters (RMSE 0.19, actual 95% coverage probability 93%). Note: EUROSCOP = European Respiratory Society Study on Chronic Obstructive Pulmonary Disease, FEV1 = forced expiratory volume in 1 second, LHS = Lung Health Study, PanCan = Pan-Canadian Early Detection of Lung Cancer Study, RMSE = root mean squared error.

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