Mortality prediction in chronic obstructive pulmonary disease comparing the GOLD 2015 and GOLD 2019 staging: a pooled analysis of individual patient data

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Abstract

In 2019, The Global Initiative for Chronic Obstructive Lung Disease (GOLD) modified the grading system for patients with COPD, creating 16 subgroups (1A–4D). As part of the COPD Cohorts Collaborative International Assessment (3CIA) initiative, we aim to compare the mortality prediction of the 2015 and 2019 COPD GOLD staging systems.

We studied 17 139 COPD patients from the 3CIA study, selecting those with complete data. Patients were classified by the 2015 and 2019 GOLD ABCD systems, and we compared the predictive ability for 5-year mortality of both classifications.

In total, 17 139 patients with COPD were enrolled in 22 cohorts from 11 countries between 2003 and 2017; 8823 of them had complete data and were analysed. Mean± sd age was 63.9±9.8 years and 62.9% were male. GOLD 2019 classified the patients in milder degrees of COPD. For both classifications, group D had higher mortality. 5-year mortality did not differ between groups B and C in GOLD 2015; in GOLD 2019, mortality was greater for group B than C. Patients classified as group A and B had better sensitivity and positive predictive value with the GOLD 2019 classification than GOLD 2015. GOLD 2015 had better sensitivity for group C and D than GOLD 2019. The area under the curve values for 5-year mortality were only 0.67 (95% CI 0.66–0.68) for GOLD 2015 and 0.65 (95% CI 0.63–0.66) for GOLD 2019.

The new GOLD 2019 classification does not predict mortality better than the previous GOLD 2015 system.

Abstract

GOLD 2019 staging system created 16 subgroups. GOLD 2015 and GOLD 2019 are not strong predictors of mortality, and do not have sufficient discriminatory power to be used as a tool for risk classification of mortality in patients with COPD. https://bit.ly/3idBuaN

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Most cited references 34

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Standardisation of spirometry.

M Miller, J. Hankinson, V Brusasco … (2005)

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Global, regional, and national deaths, prevalence, disability-adjusted life years, and years lived with disability for chronic obstructive pulmonary disease and asthma, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015

Joan B Soriano, Amanuel Abajobir, Kalkidan Hassen Abate … (2018)

Summary Background Chronic obstructive pulmonary disease (COPD) and asthma are common diseases with a heterogeneous distribution worldwide. Here, we present methods and disease and risk estimates for COPD and asthma from the Global Burden of Diseases, Injuries, and Risk Factors (GBD) 2015 study. The GBD study provides annual updates on estimates of deaths, prevalence, and disability-adjusted life years (DALYs), a summary measure of fatal and non-fatal disease outcomes, for over 300 diseases and injuries, for 188 countries from 1990 to the most recent year. Methods We estimated numbers of deaths due to COPD and asthma using the GBD Cause of Death Ensemble modelling (CODEm) tool. First, we analysed data from vital registration and verbal autopsy for the aggregate category of all chronic respiratory diseases. Subsequently, models were run for asthma and COPD relying on covariates to predict rates in countries that have incomplete or no vital registration data. Disease estimates for COPD and asthma were based on systematic reviews of published papers, unpublished reports, surveys, and health service encounter data from the USA. We used the Global Initiative of Chronic Obstructive Lung Disease spirometry-based definition as the reference for COPD and a reported diagnosis of asthma with current wheeze as the definition of asthma. We used a Bayesian meta-regression tool, DisMod-MR 2.1, to derive estimates of prevalence and incidence. We estimated population-attributable fractions for risk factors for COPD and asthma from exposure data, relative risks, and a theoretical minimum exposure level. Results were stratified by Socio-demographic Index (SDI), a composite measure of income per capita, mean years of education over the age of 15 years, and total fertility rate. Findings In 2015, 3·2 million people (95% uncertainty interval [UI] 3·1 million to 3·3 million) died from COPD worldwide, an increase of 11·6% (95% UI 5·3 to 19·8) compared with 1990. There was a decrease in age-standardised death rate of 41·9% (37·7 to 45·1) but this was counteracted by population growth and ageing of the global population. From 1990 to 2015, the prevalence of COPD increased by 44·2% (41·7 to 46·6), whereas age-standardised prevalence decreased by 14·7% (13·5 to 15·9). In 2015, 0·40 million people (0·36 million to 0·44 million) died from asthma, a decrease of 26·7% (−7·2 to 43·7) from 1990, and the age-standardised death rate decreased by 58·8% (39·0 to 69·0). The prevalence of asthma increased by 12·6% (9·0 to 16·4), whereas the age-standardised prevalence decreased by 17·7% (15·1 to 19·9). Age-standardised DALY rates due to COPD increased until the middle range of the SDI before reducing sharply. Age-standardised DALY rates due to asthma in both sexes decreased monotonically with rising SDI. The relation between with SDI and DALY rates due to asthma was attributed to variation in years of life lost (YLLs), whereas DALY rates due to COPD varied similarly for YLLs and years lived with disability across the SDI continuum. Smoking and ambient particulate matter were the main risk factors for COPD followed by household air pollution, occupational particulates, ozone, and secondhand smoke. Together, these risks explained 73·3% (95% UI 65·8 to 80·1) of DALYs due to COPD. Smoking and occupational asthmagens were the only risks quantified for asthma in GBD, accounting for 16·5% (14·6 to 18·7) of DALYs due to asthma. Interpretation Asthma was the most prevalent chronic respiratory disease worldwide in 2015, with twice the number of cases of COPD. Deaths from COPD were eight times more common than deaths from asthma. In 2015, COPD caused 2·6% of global DALYs and asthma 1·1% of global DALYs. Although there are laudable international collaborative efforts to make surveys of asthma and COPD more comparable, no consensus exists on case definitions and how to measure disease severity for population health measurements like GBD. Comparisons between countries and over time are important, as much of the chronic respiratory burden is either preventable or treatable with affordable interventions. Funding Bill & Melinda Gates Foundation.

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Prevalence and attributable health burden of chronic respiratory diseases, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017

Joan B Soriano, Parkes J Kendrick, Katherine R Paulson … (2020)

Summary Background Previous attempts to characterise the burden of chronic respiratory diseases have focused only on specific disease conditions, such as chronic obstructive pulmonary disease (COPD) or asthma. In this study, we aimed to characterise the burden of chronic respiratory diseases globally, providing a comprehensive and up-to-date analysis on geographical and time trends from 1990 to 2017. Methods Using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, we estimated the prevalence, morbidity, and mortality attributable to chronic respiratory diseases through an analysis of deaths, disability-adjusted life-years (DALYs), and years of life lost (YLL) by GBD super-region, from 1990 to 2017, stratified by age and sex. Specific diseases analysed included asthma, COPD, interstitial lung disease and pulmonary sarcoidosis, pneumoconiosis, and other chronic respiratory diseases. We also assessed the contribution of risk factors (smoking, second-hand smoke, ambient particulate matter and ozone pollution, household air pollution from solid fuels, and occupational risks) to chronic respiratory disease-attributable DALYs. Findings In 2017, 544·9 million people (95% uncertainty interval [UI] 506·9–584·8) worldwide had a chronic respiratory disease, representing an increase of 39·8% compared with 1990. Chronic respiratory disease prevalence showed wide variability across GBD super-regions, with the highest prevalence among both males and females in high-income regions, and the lowest prevalence in sub-Saharan Africa and south Asia. The age-sex-specific prevalence of each chronic respiratory disease in 2017 was also highly variable geographically. Chronic respiratory diseases were the third leading cause of death in 2017 (7·0% [95% UI 6·8–7·2] of all deaths), behind cardiovascular diseases and neoplasms. Deaths due to chronic respiratory diseases numbered 3 914 196 (95% UI 3 790 578–4 044 819) in 2017, an increase of 18·0% since 1990, while total DALYs increased by 13·3%. However, when accounting for ageing and population growth, declines were observed in age-standardised prevalence (14·3% decrease), age-standardised death rates (42·6%), and age-standardised DALY rates (38·2%). In males and females, most chronic respiratory disease-attributable deaths and DALYs were due to COPD. In regional analyses, mortality rates from chronic respiratory diseases were greatest in south Asia and lowest in sub-Saharan Africa, also across both sexes. Notably, although absolute prevalence was lower in south Asia than in most other super-regions, YLLs due to chronic respiratory diseases across the subcontinent were the highest in the world. Death rates due to interstitial lung disease and pulmonary sarcoidosis were greater than those due to pneumoconiosis in all super-regions. Smoking was the leading risk factor for chronic respiratory disease-related disability across all regions for men. Among women, household air pollution from solid fuels was the predominant risk factor for chronic respiratory diseases in south Asia and sub-Saharan Africa, while ambient particulate matter represented the leading risk factor in southeast Asia, east Asia, and Oceania, and in the Middle East and north Africa super-region. Interpretation Our study shows that chronic respiratory diseases remain a leading cause of death and disability worldwide, with growth in absolute numbers but sharp declines in several age-standardised estimators since 1990. Premature mortality from chronic respiratory diseases seems to be highest in regions with less-resourced health systems on a per-capita basis. Funding Bill & Melinda Gates Foundation.

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Author and article information

Journal

Journal ID (nlm-ta): ERJ Open Res

Journal ID (iso-abbrev): ERJ Open Res

Journal ID (publisher-id): ERJOR

Journal ID (hwp): erjor

Title: ERJ Open Research

Publisher: European Respiratory Society

ISSN (Electronic): 2312-0541

Publication date Collection: October 2020

Publication date (Electronic): 02 November 2020

Volume: 6

Issue: 4

Electronic Location Identifier: 00253-2020

Affiliations

[1 ]Pneumology Dept, Hospital Universitario de la Princesa, Instituto de Investigación Hospital Universitario de la Princesa (IISP), Universidad Autónoma de Madrid, Madrid, Spain

[2 ]Internal Medicine Department, Mútua Terrassa University Hospital, Barcelona, Spain

[3 ]Geisel School of Medicine at Dartmouth, Hanover, NH, USA

[4 ]Pneumology Dept, Hospital Universitary Vall d'Hebron, CIBER de Enfermedades Respiratorias (CIBERES), Barcelona, Spain

[5 ]Pneumology Service, Hospital Universitari Mútua Terrassa, Barcelona, Spain

[6 ]Dept of Pulmonary Medicine, Kepler-University-Hospital, Faculty of Medicine, Johannes-Kepler-University Linz, Linz, Austria

[7 ]Facultad de Medicina, Universidad Autónoma de San Luis Potosí, San Luis Potosí, Mexico

[8 ]Dept of Pulmonary Medicine, Paracelsus Medical University Hospital, Salzburg, Austria

[9 ]Departamento de Medicina, Universidad de Sevilla, HU Virgen de Valme, Seville, Spain

[10 ]Pulmonology Department, Hospital Galdakao-Usansolo, Galdakao, Spain

[11 ]Pulmonary Department, Research Unit, Hospital Universitario Nuestra Señora de La Candelaria, Universidad de La Laguna, Tenerife, Spain

[12 ]Servicio de Neumología, Hospital Arnau de Vilanova, Valencia, Spain

[13 ]Clinica Universidad de Navarra, Pamplona, Spain

[14 ]Respirology and Sleep Medicine Division, Queen's University, Kingston, Canada

[15 ]Pulmonary and Critical Care Medicine, Harvard University, Brigham and Women's Hospital, Boston, MA, USA

[16 ]Hospital Universitario Miguel Servet, Zaragoza, Spain

[17 ]Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III, Madrid, Spain

[18 ]Urban Vitality – Centre of Expertise, Faculty of Health, Amsterdam University of Applied Sciences, Amsterdam, The Netherlands

[19 ]Dept of Cardiology, Amsterdam UMC, location Academic Medical Center, Amsterdam, The Netherlands

[20 ]University Hospital of Cruces in Barakaldo, Barakaldo, Spain

[21 ]Section of Social Medicine, Dept of Public Health, Copenhagen University, Copenhagen City Heart Study, Frederiksberg Hospital, Copenhagen, Denmark

[22 ]ISGlobal, Barcelona, Spain

[23 ]Universitat Pompeu Fabra (UPF), Barcelona, Spain

[24 ]CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain

[25 ]Institute of Applied Health Research, University of Birmingham, Edgbaston, UK

[26 ]Internal Medicine, Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, MI, USA

[27 ]Dept of Public Health and Nursing, NTNU (Norwegian University of Science and Technology), Trondheim, Norway

[28 ]Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway

[29 ]Dept of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

[30 ]Centre for Clinical Documentation and Evaluation, Northern Norway Regional Health Authority, Tromso, Norway

[31 ]Dept of Clinical Science, University of Bergen, Bergen, Norway

[32 ]Dept of Global Public Health and Primary Care, University of Bergen, Bergen, Norway

[33 ]Dept of Respiratory Care and Sleep Control Medicine, Kyoto University, Kyoto, Japan

[34 ]Hospital Universitario Son Espases-IdISPa, Mallorca, Spain

[35 ]Servicio de Neumonología, Hospital San Juan de Dios de La Plata, Buenos Aires, Argentina

[36 ]Respiratory Medicine, Cochin Hospital, APHP Centre–University of Paris, Cochin Institute (INSERM UMR1016), Paris, France

[37 ]UBC Centre for Heart Lung Innovation, Vancouver, BC, Canada

[38 ]Division of Respiratory Medicine, Dept of Medicine, University of British Columbia, Vancouver, BC, Canada

[39 ]Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland

[40 ]Unidad Médico Quirúrgica de Enfermedades Respiratorias, Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/Universidad de Sevilla, Seville, Spain

[41 ]These authors contributed equally

Author notes

Joan B. Soriano, Hospital Universitario de la Princesa, Diego de León 62, Neumología 6ª planta, 28006-Madrid, Spain. E-mail: jbsoriano2@ 123456gmail.com