INTRODUCTION: The concept of phenotyping emerged, reflecting specific clinical, pulmonary and extrapulmonary features of each particular chronic obstructive pulmonary disease (COPD) case. Our aim was to analyze prognostic utility of: "Czech" COPD phenotypes and their most frequent combinations, "Spanish" phenotypes and Global Initiative for Chronic Obstructive Lung Disease (GOLD) stages + groups in relation to long-term mortality risk. METHODS: Data were extracted from the Czech Multicenter Research Database (CMRD) of COPD. Kaplan-Meier (KM) estimates (at 60 months from inclusion) were used for mortality assessment. Survival rates were calculated for the six elementary "Czech" phenotypes and their most frequent and relevant combinations, "Spanish" phenotypes, GOLD grades and groups. Statistically significant differences were tested by Log Rank test. An analysis of factors underlying mortality risk (the role of confounders) has been assessed with the use of classification and regression tree (CART) analysis. Basic factors showing significant differences between deceased and living patients were entered into the CART model. This showed six different risk groups, the differences in risk were tested by a Log Rank test. RESULTS: The cohort (n=720) was 73.1% men, with a mean age of 66.6 years and mean FEV1 44.4% pred. KM estimates showed bronchiectases/COPD overlap (HR 1.425, p=0.045), frequent exacerbator (HR 1.58, p<0.001), cachexia (HR 2.262, p<0.001) and emphysematous (HR 1.786, p=0.015) phenotypes associated with higher mortality risk. Co-presence of multiple phenotypes in a single patient had additive effect on risk; combination of emphysema, cachexia and frequent exacerbations translated into poorest prognosis (HR 3.075; p<0.001). Of the "Spanish" phenotypes, AE CB and AE non-CB were associated with greater risk of mortality (HR 1.787 and 2.001; both p=0.001). FEV1% pred., cachexia and chronic heart failure in patient history were the major underlying factors determining mortality risk in our cohort. CONCLUSION: Certain phenotypes ("Czech" or "Spanish") of COPD are associated with higher risk of death. Co-presence of multiple phenotypes (emphysematous plus cachectic plus frequent exacerbator) in a single individual was associated with amplified risk of mortality.

Department of Respiratory Diseases University Hospital Brno Brno Czech Republic

Faculty of Medicine in Hradec Kralove Charles University Prague Czech Republic

Faculty of Medicine Masaryk University Brno Czech Republic

Faculty of Medicine Palacky University Olomouc Czech Republic

Faculty of Medicine University of Ostrava Ostrava Czech Republic

Institute of Biostatistics and Analyses Ltd Brno Czech Republic

Pulmonary Department Bulovka Hospital Prague Czech Republic

Pulmonary Department Mlada Boleslav Hospital Mlada Boleslav Czech Republic

Pulmonary Department University Hospital Hradec Kralove Hradec Kralove Czech Republic

Pulmonary Department University Hospital Olomouc Olomouc Czech Republic

Pulmonary Department University Hospital Ostrava Ostrava Czech Republic

Zobrazit více v PubMed

GBD. 2017 causes of death collaborators. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2018;392(10159):1736–1788. PubMed PMC

Miravitlles M, Soler-Cataluña JJ, Calle M, et al. Spanish guidelines for management of chronic obstructive pulmonary disease (GesEPOC) 2017. Pharmacological treatment of stable phase. Arch Bronconeumol. 2017;53(6):324–335. doi:10.1016/j.arbres.2017.03.018 PubMed DOI

Agusti A, Bel E, Thomas M, et al. Treatable traits: toward precision medicine of chronic airway diseases. Eur Respir J. 2016;47(2):410–419. doi:10.1183/13993003.01359-2015 PubMed DOI

McDonald VM, Fingleton J, Agusti A, et al.; Participants of the Treatable Traits Down Under International Workshop; Treatable Traits Down Under International Workshop participants. Treatable traits: a new paradigm for 21st century management of chronic airway diseases: treatable traits down under international workshop report. Eur Respir J. 2019;53(5):1802058. doi:10.1183/13993003.02058-2018 PubMed DOI

Ulrik CS, Vijverberg S, Hanania NA, Diamant Z. Precision medicine and treatable traits in chronic airway diseases - where do we stand? Curr Opin Pulm Med. 2020;26(1):33–39. doi:10.1097/MCP.0000000000000639 PubMed DOI

Zatloukal J, Brat K, Neumannova K, et al. Chronic obstructive pulmonary disease - diagnosis and management of stable disease; a personalized approach to care, using the treatable traits concept based on clinical phenotypes. Position paper of the Czech pneumological and phthisiological society. Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub. 2020;164(4):325–356. doi:10.5507/bp.2020.056 PubMed DOI

Miravitlles M, Vogelmeier C, Roche N, et al. A review of national guidelines for management of COPD in Europe. Eur Respir J. 2016;47(2):625–637. doi:10.1183/13993003.01170-2015 PubMed DOI PMC

Miravitlles M, Soler-Cataluña JJ, Calle M, et al.; Spanish Society of Pulmonology and Thoracic Surgery. Spanish COPD Guidelines (GesEPOC): pharmacological treatment of stable COPD. spanish society of pulmonology and thoracic surgery. Arch Bronconeumol. 2012;48(7):247–257. doi:10.1016/j.arbres.2012.04.001 PubMed DOI

Zatloukal J, Volakova E, Koblizek V, et al. Phenotype-based therapy of COPD: effect on the rate of COPD exacerbations. Eur Respir J. 2018;52(suppl 62):PA3860.

Vukoja M, Kopitovic I, Lazic Z, et al. Diagnosis and management of chronic obstructive pulmonary disease in Serbia: an expert group position statement. Int J Chron Obstruct Pulmon Dis. 2019;14:1993–2002. doi:10.2147/COPD.S214690 PubMed DOI PMC

Zykov KA, Ovcharenko SI. Approaches to drug therapy for COPD in Russia: a proposed therapeutic algorithm. Int J Chron Obstruct Pulmon Dis. 2017;12:1125–1133. doi:10.2147/COPD.S125594 PubMed DOI PMC

Golpe R, Suárez-Valor M, Martín-Robles I, et al. Mortality in COPD patients according to clinical phenotypes. Int J Chron Obstruct Pulmon Dis. 2018;13:1433–1439. doi:10.2147/COPD.S159834 PubMed DOI PMC

Novotna B, Koblizek V, Zatloukal J, et al. Czech multicenter research database of severe COPD. Int J Chron Obstruct Pulmon Dis. 2014;9:1265–1274. doi:10.2147/COPD.S71828 PubMed DOI PMC

Rabe KF, Hurd S, Anzueto A, et al. Global Initiative for chronic obstructive lung disease. Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am J Respir Crit Care Med. 2007;176(6):532–555. doi:10.1164/rccm.200703-456SO PubMed DOI

Vogelmeier CF, Criner GJ, Martinez FJ, et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive lung disease 2017 Report. GOLD executive summary. Am J Respir Crit Care Med. 2017;195(5):557–582. doi:10.1164/rccm.201701-0218PP PubMed DOI

Singh D, Agusti A, Anzueto A, et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive lung disease: the GOLD science committee report 2019. Eur Respir J. 2019;53(5):1900164. doi:10.1183/13993003.00164-2019 PubMed DOI

Vestbo J, Hurd SS, Agustí AG, et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am J Respir Crit Care Med. 2013;187(4):347–365. doi:10.1164/rccm.201204-0596PP PubMed DOI

Hernández Vázquez J, Ali García I, Jiménez-García R, et al. COPD phenotypes: differences in survival. Int J Chron Obstruct Pulmon Dis. 2018;13:2245–2251. doi:10.2147/COPD.S166163 PubMed DOI PMC

Calle Rubio M, Casamor R, Miravitlles M. Identification and distribution of COPD phenotypes in clinical practice according to Spanish COPD guidelines: the FENEPOC study. Int J Chron Obstruct Pulmon Dis. 2017;12:2373–2383. doi:10.2147/COPD.S137872 PubMed DOI PMC

Cabrera López C, Casanova Macario C, Marín Trigo JM, et al. Comparison of the 2017 and 2015 global initiative for chronic obstructive lung disease reports. Impact on grouping and outcomes. Am J Respir Crit Care Med. 2018;197(4):463–469. doi:10.1164/rccm.201707-1363OC PubMed DOI

Brat K, Plutinsky M, Koblizek V, et al. Cluster phenotyping as an approach to identify COPD patients at risk of poor prognosis. Eur Respir J. 2018;52(suppl 62):PA3853.

Young KA, Regan EA, Han MK, et al. COPDGene® Investigators. Subtypes of COPD have unique distributions and differential risk of mortality. Chronic Obstr Pulm Dis. 2019;6(5):400–413. doi:10.15326/jcopdf.6.5.2019.0150 PubMed DOI PMC

Sarkar M, Niranjan N, Banyal PK. Mechanisms of hypoxemia. Lung India. 2017;34(1):47–60. doi:10.4103/0970-2113.197116 PubMed DOI PMC

Schols AM, Slangen J, Volovics L, Wouters EF. Weight loss is a reversible factor in the prognosis of chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 1998;157(6 Pt 1):1791–1797. doi:10.1164/ajrccm.157.6.9705017 PubMed DOI

Landbo C, Prescott E, Lange P, Vestbo J, Almdal TP. Prognostic value of nutritional status in chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 1999;160(6):1856–1861. doi:10.1164/ajrccm.160.6.9902115 PubMed DOI

McDonald MN, Wouters EFM, Rutten E, et al. It’s more than low BMI: prevalence of cachexia and associated mortality in COPD. Respir Res. 2019;20(1):100. doi:10.1186/s12931-019-1073-3 PubMed DOI PMC

Celli BR, Cote CG, Marin JM, et al. The body-mass index, airflow obstruction, dyspnea, and exercise capacity index in chronic obstructive pulmonary disease. N Engl J Med. 2004;350(10):1005–1012. doi:10.1056/NEJMoa021322 PubMed DOI

Suissa S, Dell’Aniello S, Ernst P. Long-term natural history of chronic obstructive pulmonary disease: severe exacerbations and mortality. Thorax. 2012;67(11):957–963. doi:10.1136/thoraxjnl-2011-201518 PubMed DOI PMC

Hillas G, Perlikos F, Tzanakis N. Acute exacerbation of COPD: is it the “stroke of the lungs”? Int J Chron Obstruct Pulmon Dis. 2016;11:1579–1586. doi:10.2147/COPD.S106160 PubMed DOI PMC

Franssen FM, Alter P, Bar N, et al. Personalized medicine for patients with COPD: where are we? Int J Chron Obstruct Pulmon Dis. 2019;14:1465–1484. doi:10.2147/COPD.S175706 PubMed DOI PMC

Pikoula M, Quint JK, Nissen F, Hemingway H, Smeeth L, Denaxas S. Identifying clinically important COPD sub-types using data-driven approaches in primary care population based electronic health records. BMC Med Inform Decis Mak. 2019;19(1):86. doi:10.1186/s12911-019-0805-0 PubMed DOI PMC

Burgel PR, Paillasseur JL, Janssens W, et al. Initiatives BPCO, EABPCO, Leuven and 3CIA study groups. A simple algorithm for the identification of clinical COPD phenotypes. Eur Respir J. 2017;50(5):1701034. doi:10.1183/13993003.01034-2017 PubMed DOI

Aramburu A, Arostegui I, Moraza J, et al. COPD classification models and mortality prediction capacity. Int J Chron Obstruct Pulmon Dis. 2019;14:605–613. doi:10.2147/COPD.S184695 PubMed DOI PMC

Brat K, Svoboda M, Hejduk K, et al. Introducing a new prognostic instrument for long-term mortality prediction in COPD patients: the CADOT index. Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub. 2020. doi:10.5507/bp.2020.035 PubMed DOI

RETRO-POPE: A Retrospective, Multicenter, Real-World Study of All-Cause Mortality in COPD