Validation of the GOLD 2017 and new 16 subgroups (1A–4D) classifications in predicting exacerbation and mortality in COPD patients
Received 3 July 2018
Accepted for publication 13 September 2018
Published 18 October 2018 Volume 2018:13 Pages 3425—3433
Checked for plagiarism Yes
Review by Single-blind
Peer reviewers approved by Dr Cristina Weinberg
Peer reviewer comments 2
Editor who approved publication: Prof. Dr. Chunxue Bai
Meng-Zhi Han,1,2 Tzuen-Ren Hsiue,3 Sheng-Han Tsai,1 Tang-Hsiu Huang,2,3 Xin-Min Liao,2,3 Chiung-Zuei Chen3
1Division of General Medicine, Department of Internal Medicine, National Cheng Kung University, College of Medicine and Hospital, Tainan, Taiwan; 2Institute of Clinical Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan; 3Division of Pulmonary Medicine, Department of Internal Medicine, National Cheng Kung University, College of Medicine and Hospital, Tainan, Taiwan
Background and objective: A multidimensional assessment of COPD was recommended by the Global Initiative for Chronic Obstructive Lung Disease (GOLD) in 2013 and revised in 2017. We examined the ability of the GOLD 2017 and the new 16 subgroup (1A–4D) classifications to predict clinical outcomes, including exacerbation and mortality, and compared them with the GOLD 2013 classifications.
Methods: Patients with COPD were recruited from January 2006 to December 2017. The predictive abilities of grades 1–4 and groups A–D were examined through a logistic regression analysis with receiver operating curve estimations and area under the curve (AUC).
Results: A total of 553 subjects with COPD were analyzed. The mortality rate was 48.6% during a median follow-up period of 5.2 years. Both the GOLD 2017 and the 2013 group A–D classifications had good predictive ability for total and severe exacerbations, for which the AUCs were 0.79 vs 0.77 and 0.79 vs 0.78, respectively. The AUCs for the GOLD 2017 groups A–D, grades 1–4, and the GOLD 2013 group A–D classifications were 0.70, 0.66, and 0.70 for all-cause mortality and 0.73, 0.71, and 0.74 for respiratory cause mortality, respectively. Combining the spirometric staging with the grouping for the GOLD 2017 subgroups (1A–4D), the all-cause mortality rate for group B and D patients was significantly increased from subgroups 1B–4B (27.7%, 50.6%, 53.3%, and 69.2%, respectively) and groups 1D–4D (55.0%, 68.8%, 82.1%, and 90.5%, respectively). The AUCs of subgroups (1A–4D) were 0.73 and 0.77 for all-cause and respiratory mortality, respectively; the new classification was determined more accurate than the GOLD 2017 for predicting mortality (P<0.0001).
Conclusion: The GOLD 2017 classification performed well by identifying individuals at risk of exacerbation, but its predictive ability for mortality was poor among COPD patients. Combining the spirometric staging with the grouping increased the predictive ability for all-cause and respiratory mortality.
Summary at a glance: We validate the ability of the GOLD 2017 and 16 subgroup (1A–4D) classifications to predict clinical outcome for COPD patients. The GOLD 2017 classification performed well by identifying individuals at risk of exacerbation, but its predictive ability for mortality was poor. The new 16 subgroup (1A–4D) classification combining the spirometric 1–4 staging and the A–D grouping increased the predictive ability for mortality and was better than the GOLD 2017 for predicting all-cause and respiratory mortality among COPD patients.
Keywords: multidimensional assessment, clinical outcomes, spirometric grade, predictive ability, logistic regression analysis, receiver operating curve
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