Katherine E. Lowe, MSc1 Elizabeth A. Regan, MD, PhD2 Antonio Anzueto, MD3 Erin Austin, PhD4 John H. M. Austin, MD5 Terri H. Beaty, PhD6 Panayiotis V. Benos, PhD7 Christopher J. Benway, PhD8 Surya P. Bhatt, MD9 Eugene R. Bleecker, MD10 Sandeep Bodduluri, PhD9 Jessica Bon, MD, MS7,11 Aladin M. Boriek, PhD12 Adel RE. Boueiz, MD8 Russell P. Bowler, MD, PhD2 Matthew Budoff, MD13 Richard Casaburi, PhD, MD13 Peter J. Castaldi, MD, MSc8 Jean-Paul Charbonnier, PhD14 Michael H. Cho, MD, MPH8 Alejandro Comellas, MD15 Douglas Conrad, MD16 Corinne Costa Davis, MBA17 Gerard J. Criner, MD18 Douglas Curran-Everett, PhD2 Jeffrey L. Curtis, MD19 Dawn L. DeMeo, MD, MPH8 Alejandro A. Diaz, MD8 Mark T. Dransfield, MD9 Jennifer G. Dy, PhD20 Ashraf Fawzy, MD, MPH6 Margaret Fleming, PhD21 Eric L. Flenaugh, MD22 Marilyn G. Foreman, MD, MS22 Spyridon Fortis, MD15 Hirut Gebrekristos, PhD22 Sarah Grant, MD21 Philippe A. Grenier, MD23 Tian Gu, MS24 Abhya Gupta, MD25 MeiLan K. Han, MD, MS24 Nicola A. Hanania, MD, MS12 Nadia N. Hansel, MD, MPH6 Lystra P. Hayden, MD, MMSc8 Craig P. Hersh, MD, MPH8 Brian D. Hobbs, MD8 Eric A. Hoffman, PhD15 James C. Hogg, MD26 John E. Hokanson, MPH, PhD27 Karin F. Hoth, PhD15 Albert Hsiao, MD, PhD28 Stephen Humphries, PhD2 Kathleen Jacobs, MD16 Francine L. Jacobson, MD, MPH8 Ella A. Kazerooni, MD, MS24 Victor Kim, MD18 Woo Jin Kim, MD, PhD29 Gregory L. Kinney, MPH, PhD27 Harald Koegler, MD30 Sharon M. Lutz, PhD31 David A. Lynch, MB2 Neil R. MacIntye Jr, MD32 Barry J. Make, MD2 Nathaniel Marchetti, DO18 Fernando J. Martinez, MD, MS33 Diego J. Maselli, MD3 Anne M. Mathews, MD32 Meredith C. McCormack, MD, MHS6 Merry-Lynn N. McDonald, MSc, PhD9 Charlene E. McEvoy, MD, MPH34 Matthew Moll, MD8 Sarah S. Molye, PhD35 Susan Murray, ScD24 Hrudaya Nath, MD9 John D. Newell Jr, MD15,36,37 Mariaelena Occhipinti, MD, PhD38 Matteo Paoletti, PhD38 Trisha Parekh, DO9 Massimo Pistolesi, MD38 Katherine A. Pratte, PhD2 Nirupama Putcha, MD, MHS6 Margaret Ragland, MD, MS27 Joseph M. Reinhardt, PhD15 Stephen I. Rennard, MD39,40 Richard A. Rosiello, MD41 James C. Ross, PhD8 Harry B. Rossiter, PhD13,42 Ingo Ruczinski, PhD6 Raul San Jose Estepar, PhD8 Frank C. Sciurba, MD7 Jessica C. Sieren, PhD15 Harjinder Singh, MD3 Xavier Soler, MD16,43 Robert M. Steiner, MD18 Matthew J. Strand, PhD2 William W. Stringer, MD13 Ruth Tal-Singer, PhD44 Byron Thomashow, MD5 Gonzalo Vegas Sánchez-Ferrero, PhD8 John W. Walsh45† Emily S. Wan, MD8,46 George R. Washko, MD8 J. Michael Wells, MD, MSPH9 Chris H. Wendt, MD47 Gloria Westney, MD, MS22 Ava Wilson, MSPH9 Robert A. Wise, MD6 Andrew Yen, MD16 Kendra Young, MSPH, PhD27 Jeong Yun, MD, MPH8 Edwin K. Silverman, MD, PhD8 James D. Crapo, MD2
Author Affiliations
- Cleveland Clinic Lerner College of Medicine of Case Western Reserve School of Medicine, Cleveland, Ohio
- National Jewish Health, Denver, Colorado
- University of Texas Health, San Antonio
- University of Colorado at Denver
- Columbia University, New York, New York
- Johns Hopkins University, Baltimore, Maryland
- University of Pittsburgh, Pittsburgh, Pennsylvania
- Brigham and Women's Hospital, Boston, Massachusetts
- University of Alabama at Birmingham
- University of Arizona Health Sciences, Tucson
- VA Pittsburgh Healthcare System, Pittsburgh, Pennsylvania
- Baylor College of Medicine, Houston, Texas
- Los Angeles Biomedical Research Institute at Harbor- University of California Los Angeles Medical Center, Torrance
- Thirona, Nijmegen, The Netherlands
- University of Iowa, Iowa City
- University of California at San Diego
- COPD Foundation, Washington, DC
- Temple University, Philadelphia, Pennsylvania
- Ann Arbor VA Medical Center, Ann Arbor, Michigan
- Northeastern University, Boston, Massachusetts
- Novartis Institute for Biomedical Research, Cambridge, Massachusetts
- Morehouse School of Medicine, Atlanta, Georgia
- Hôpital Foch, Suresnes, France
- University of Michigan, Ann Arbor
- Boehringer Ingelheim, Biberach an der Riss, Germany
- University of British Columbia, Vancouver, Canada
- University of Colorado Anschutz Medical Campus, Aurora
- University of California-San Diego, La Jolla
- Kangwon National University, Chuncheon, Korea
- Boehringer-Ingelheim, Ingelheim, Germany
- Harvard Medical School, Boston, Massachusetts
- Duke University Health, Durham, North Carolina
- Weill-Cornell Medicine, New York, New York
- Minnesota Health Partners, St. Paul
- AstraZeneca, Denver, Colorado
- University of Washington, Seattle
- VIDA Diagnostics, Inc, Coralville, Iowa
- University of Florence, Florence, Italy
- AstraZeneca, Cambridge, United Kingdom
- University of Nebraska Medical Center, Omaha
- Reliant Medical Group, Worcester, Massachusetts
- University of Leeds, Leeds, United Kingdom
- GlaxoSmithKline, Research Triangle Park, North Carolina
- GlaxoSmithKline, Collegeville, Pennsylvania
- COPD Foundation, Miami, Florida
- VA Boston Healthcare System, Jamaica Plain, Massachusetts
- Minneapolis VA, Minneapolis, Minnesota
† deceased
Address correspondence to:
James D. Crapo, MD
1400 Jackson St, K701
Denver, CO 80209
303-398-1657
Email: CrapoJ@NJHealth.org
Abstract
Background: Chronic obstructive pulmonary disease (COPD) remains a major cause of morbidity and mortality. Present-day diagnostic criteria are largely based solely on spirometric criteria. Accumulating evidence has identified a substantial number of individuals without spirometric evidence of COPD who suffer from respiratory symptoms and/or increased morbidity and mortality. There is a clear need for an expanded definition of COPD that is linked to physiologic, structural (computed tomography [CT]) and clinical evidence of disease. Using data from the COPD Genetic Epidemiology study (COPDGene®), we hypothesized that an integrated approach that includes environmental exposure, clinical symptoms, chest CT imaging and spirometry better defines disease and captures the likelihood of progression of respiratory obstruction and mortality.
Methods: Four key disease characteristics – environmental exposure (cigarette smoking), clinical symptoms (dyspnea and/or chronic bronchitis), chest CT imaging abnormalities (emphysema, gas trapping and/or airway wall thickening), and abnormal spirometry – were evaluated in a group of 8784 current and former smokers who were participants in COPDGene® Phase 1. Using these 4 disease characteristics, 8 categories of participants were identified and evaluated for odds of spirometric disease progression (FEV1 > 350 ml loss over 5 years), and the hazard ratio for all-cause mortality was examined.
Results: Using smokers without symptoms, CT imaging abnormalities or airflow obstruction as the reference population, individuals were classified as Possible COPD, Probable COPD and Definite COPD. Current Global initiative for obstructive Lung Disease (GOLD) criteria would diagnose 4062 (46%) of the 8784 study participants with COPD. The proposed COPDGene® 2019 diagnostic criteria would add an additional 3144 participants. Under the new criteria, 82% of the 8784 study participants would be diagnosed with Possible, Probable or Definite COPD. These COPD groups showed increased risk of disease progression and mortality. Mortality increased in patients as the number of their COPD characteristics increased, with a maximum hazard ratio for all cause-mortality of 5.18 (95% confidence interval [CI]: 4.15–6.48) in those with all 4 disease characteristics.
Conclusions: A substantial portion of smokers with respiratory symptoms and imaging abnormalities do not manifest spirometric obstruction as defined by population normals. These individuals are at significant risk of death and spirometric disease progression. We propose to redefine the diagnosis of COPD through an integrated approach using environmental exposure, clinical symptoms, CT imaging and spirometric criteria. These expanded criteria offer the potential to stimulate both current and future interventions that could slow or halt disease progression in patients before disability or irreversible lung structural changes develop.
Citation
Citation: Lowe KE, Regan EA, Anzueto A, et al. COPDGene 2019: redefining the diagnosis of chronic obstructive pulmonary disease. Chronic Obstr Pulm Dis. 2019; 6(5): 384-399. doi: http://dx.doi.org/10.15326/jcopdf.6.5.2019.0149
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Kendra A. Young, PhD1 Elizabeth A. Regan, MD, PhD2 MeiLan K. Han, MD3 Sharon M. Lutz, PhD4 Margaret Ragland, MD1 Peter J. Castaldi, MD5 George R. Washko, MD5 Michael H. Cho, MD5 Mathew Strand, PhD6 Douglas Curran-Everett, PhD6 Terri H. Beaty, PhD7 Russell P. Bowler, MD2 Emily S. Wan, MD4,8 David A. Lynch, MB9 Barry J. Make, MD2 Edwin K. Silverman, MD, PhD5 James D. Crapo, MD2 John E. Hokanson, PhD1 Gregory L. Kinney, PhD1 and the COPDGene Investigators
Author Affiliations
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora
- Department of Medicine, National Jewish Health, Denver, Colorado
- Division of Pulmonary and Critical Care, University of Michigan, Ann Arbor
- Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, Aurora
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Biostatistics and Bioinformatics, Office of Academic Affairs, National Jewish Health, Denver, Colorado
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore Maryland
- VA Boston Healthcare System, Boston, Massachusetts
- Department of Radiology, National Jewish Health, Denver, Colorado
Address correspondence to:
Kendra A. Young, MSPH, PhD
Department of Epidemiology
Colorado School of Public Health
University of Colorado Anschutz Medical Campus
13001 East 17th Avenue
Room W3142, Campus Box B-119
Aurora, CO 80045
Phone: 303-724-4441
Email: Kendra.Young@UCDenver.edu
Abstract
Background: Previous attempts to explore the heterogeneity of chronic obstructive pulmonary disease (COPD) clustered individual patients using clinical, demographic, and disease features. We developed continuous multidimensional disease axes based on radiographic and spirometric variables that split into an airway-predominant axis and an emphysema-predominant axis.
Methods: The COPD Genetic Epidemiology study (COPDGene®) is a cohort of current and former smokers, > 45 years, with at least 10 pack years of smoking history. Spirometry measures, blood pressure and body mass were directly measured. Mortality was assessed through continuing longitudinal follow-up and cause of death was adjudicated. Among 8157 COPDGene® participants with complete spirometry and computed tomography (CT) measures, the top 2 deciles of the airway-predominant and emphysema-predominant axes previously identified were used to categorize individuals into 3 groups having the highest risk for mortality using Cox proportional hazard ratios. These groups were also assessed for causal mortality. Biomarkers of COPD (fibrinogen, soluble receptor for advanced glycation end products [sRAGE], C-reactive protein [CRP], clara cell secretory protein [CC16], surfactant-D [SP-D]) were compared by group.
Findings: High-risk subtype classification was defined for 2638 COPDGene® participants who were in the highest 2 deciles of either the airway-predominant and/or emphysema-predominant axis (32% of the cohort). These high-risk participants fell into 3 groups: airway-predominant disease only (APD-only), emphysema-predominant disease only (EPD-only) and combined APD-EPD. There was 26% mortality for the APD-only group, 21% mortality for the EPD-only group, and 54% mortality for the combined APD-EPD group. The APD-only group (n=1007) was younger, had a lower forced expiratory volume in 1 second (FEV1) percent (%) predicted and a strong association with the preserved ratio-impaired spirometry (PRISm) quadrant. The EPD-only group (n=1006) showed a relatively higher FEV1 % predicted and included largely GOLD stage 0, 1 and 2 partipants. Individuals in each of the 3 high-risk groups were at greater risk for respiratory mortality, while those in the APD-only group were additionally at greater risk for cardiovascular mortality. Biomarker analysis demonstrated a significant association of the APD-only group with CRP, and sRAGE demonstrated greatest significance with both the EPD-only and the combined APD-EPD groups.
Interpretation: Among current and former smokers, individuals in the highest 2 deciles for mortality risk on the airway-predominant axis and the emphysema-predominant axis have unique associations to spirometric patterns, different imaging characteristics, biomarkers and causal mortality.
Citation
Citation: Young KA, Regan EA, Han MK, et al and the COPDGene Investigators. Subtypes of COPD have unique distributions and differential risk of mortality. Chronic Obstr Pulm Dis. 2019; 6(5): 400-413. doi: http://dx.doi.org/10.15326/jcopdf.6.5.2019.0150
Keywords
COPD, chronic obstructive pulmonary disease, biomarkers, mortality, COPD Genetic Epidemiology, COPDGene, PRISm, preserved ratio-impaired spirometry, subtypes, airway-predominant disease, emphysema-predominant disease
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Kendra A. Young, PhD1 Matthew J. Strand, PhD2 Margaret F. Ragland, MD, MS3 Gregory L. Kinney, PhD1 Erin E. Austin, PhD4 Elizabeth A. Regan, MD, PhD5 Katherine E. Lowe, MSc1 Barry J. Make, MD5 Edwin K. Silverman, MD, PhD6 James D. Crapo, MD5 John E. Hokanson, PhD1 for the COPDGene Investigators
Author Affiliations
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora
- Division of Biostatistics and Bioinformatics, Office of Academic Affairs, National Jewish Health, Denver, Colorado
- Department of Pulmonary Sciences and Critical Care Medicine, University of Colorado School of Medicine, Aurora
- Department of Mathematical and Statistical Sciences, University of Colorado at Denver
- Department of Medicine, National Jewish Health, Denver, Colorado
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
Address correspondence to:
Kendra A. Young, MSPH, PhD
Department of Epidemiology
Colorado School of Public Health
University of Colorado Anschutz Medical Campus
13001 East 17th Avenue
Room W3142, Campus Box B-119
Aurora, CO 80045
Phone: 303-724-4441
Email: Kendra.Young@cuanschutz.edu
Abstract
Rationale: We classified individuals into pulmonary disease subtypes based on 2 underlying pathophysiologic disease axes (airway-predominant and emphysema-predominant) and their increased mortality risk. Our next objective was to determine whether some subcomponents of these subtypes are additionally associated with unique patterns of Global initiative for chronic Obstructive Lung Disease (GOLD) spirometry stage progression.
Methods: After accounting for intra-individual measurement variability in spirometry measures between baseline (Phase 1) and the 5-year follow up (Phase 2) of the COPD Genetic Epidemiology (COPDGene®) study, 4615 individuals had complete data that would characterize patterns of disease progression over 5 years (2033 non-Hispanic whites; 827 African Americans; 48% female). Individuals could express increased risk for mortality on one or both of the primary subtype axes (airway-predominant or emphysema-predominant) and thus they were further classified into 6 groups: high-risk airway-predominant disease only (APD-only), moderate-risk airway-predominant disease only (MR-APD-only), high-risk emphysema-predominant disease only (EPD-only), combined high-risk airway- and emphysema-predominant disease (combined APD-EPD), combined moderate-risk airway- and emphysema-predominant disease (combined MR-APD-EPD), and no high-risk pulmonary subtype. Outcomes were dichotomized for GOLD spirometry stage progression from Phase 1 to Phase 2. Logistic regression of the progression outcomes on the pulmonary subtypes were adjusted for age, sex, race, and change in smoking status.
Results: The MR-APD-only group was associated with conversion from GOLD 0 to preserved ratio-impaired spirometry (PRISm) status (odds ratio [OR] 11.3, 95% confidence interval [CI] 5.7–22.1) and GOLD 0 to GOLD 2–4 (OR 6.0, 95% CI 2.0–18.0). The EPD-only group was associated with conversion from GOLD 0 to GOLD 1 (OR 2.4, 95% CI 1.2–4.6), and GOLD 1 to GOLD 2–4 (OR 2.6, 95% CI 1.0–6.9). Conversion between PRISm and GOLD 2–4 (31%–38%) occurred in both the APD-only and the MR-APD-only groups.
Conclusion: Differential conversion occurs from GOLD 0 to PRISm and GOLD 0 to GOLD 1 based on groups expressing airway-predominant disease or emphysema-predominant disease independently or in combination. Airway-predominant and emphysema-predominant subtypes are highly important in determining patterns of early disease progression.
Citation
Citation: Young KA, Strand MJ, Ragland MF, et al for the COPDGene® Investigators. Pulmonary subtypes exhibit differential Global Initiative for Chronic Obstructive Lung Disease spirometry stage progression: the COPDGene® study. Chronic Obstr Pulm Dis. 2019; 6(5): 414-429. doi: http://dx.doi.org/10.15326/jcopdf.6.5.2019.0155
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