• Lancet Respir Med · Mar 2018

    Prediction of mortality in patients with chronic obstructive pulmonary disease with the new Global Initiative for Chronic Obstructive Lung Disease 2017 classification: a cohort study.

    • Anne Gedebjerg, Szimonetta Komjáthiné Szépligeti, Laura-Maria Holm Wackerhausen, Erzsébet Horváth-Puhó, Ronald Dahl, Jens Georg Hansen, Henrik Toft Sørensen, Mette Nørgaard, Peter Lange, and Reimar Wernich Thomsen.
    • Department of Clinical Epidemiology, Institute of Clinical Medicine, Aarhus University Hospital, Aarhus, Denmark. Electronic address: aged@clin.au.dk.
    • Lancet Respir Med. 2018 Mar 1; 6 (3): 204-212.

    BackgroundThe Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2017 classification separates the spirometric 1-4 staging from the ABCD groups defined by symptoms and exacerbations. Little is known about how this new classification predicts mortality in patients with chronic obstructive pulmonary disease (COPD). We aimed to establish the predictive ability of the GOLD 2017 classification, compared with earlier classifications, for all-cause and respiratory mortality, both when using its main ABCD groups and when further subdividing according to spirometric 1-4 staging.MethodsIn this nationwide cohort study, we enrolled patients with COPD with data available in the Danish registry for COPD. To be included in this registry, individuals must have been outpatients in hospital-based pulmonary clinics in Denmark. Eligible patients were aged 30 years or older; had received a primary diagnosis of COPD (International Classification of Diseases [ICD]-10 J44.X) or acute respiratory failure (ICD-10 J96.X) in combination with COPD (ICD-10 J44.X) as a secondary diagnosis; and had complete data on FEV1, body-mass index, modified Medical Research Council dyspnoea scale score, and smoking status. We categorised eligible patients with complete data according to the 2007, 2011, and 2017 GOLD classifications at the first contact with an outpatient clinic. For the GOLD 2017 classification, we further subdivided the patients by spirometry into 16 subgroups (1A to 4D). We calculated adjusted hazard ratios (HRs) for all-cause and respiratory mortality and compared the predictive ability of the three GOLD classifications (2007, 2011, and 2017) using receiver operating curves.FindingsWe enrolled 33 765 patients with COPD, who were outpatients in Danish hospitals between Jan 1, 2008, and Nov 30, 2013, in the main cohort assessed for all-cause mortality. 22 621 of these patients had data available on cause-specific mortality (respiratory) and were included in a subcohort followed from Jan 1, 2008, to Dec 31, 2011. For the GOLD 2017 classification, 3 year mortality increased with increasing exacerbations and dyspnoea from group A (all-cause mortality 10·0%, respiratory mortality 3·0%) to group D (all-cause mortality 36·9%, respiratory mortality 18·0%). However, 3 year mortality was higher for group B patients (all-cause mortality 23·8%, respiratory mortality 9·7%) than for group C patients (all-cause mortality 17·4%, respiratory mortality 6·4%). Compared with group A, adjusted HRs for all-cause mortality ranged from 2·05 (95% CI 1·87-2·26) for group B, to 1·47 (1·31-1·65) for group C, and to 3·01 (2·75-3·30) for group D. Area under the curve for all-cause mortality was 0·61 (95% CI 0·60-0·61) for GOLD 2007, 0·61 (0·60-0·62) for GOLD 2011, and 0·63 (0·53-0·73) for GOLD 2017. Area under the curve for respiratory mortality was 0·64 (0·62-0·65) for GOLD 2007, 0·63 (0·62-0·64) for GOLD 2011, and 0·65 (0·53-0·78) for GOLD 2017. The GOLD 2017 classification based on ABCD groups only did not predict mortality better than the earlier 2007 and 2011 GOLD classifications. However, when 16 subgroups (1A to 4D) were defined, the new classification predicted mortality more accurately than the previous systems (p<0·0001).InterpretationWe showed that the new GOLD 2017 ABCD classification does not predict all-cause and respiratory mortality more accurately than the previous GOLD systems from 2007 and 2011.FundingDanish Lung Association, Program for Clinical Research Infrastructure.Copyright © 2018 Elsevier Ltd. All rights reserved.

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