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

. 2023 ; 18 () : 2661-2672. [epub] 20231117

Jazyk angličtina Země Nový Zéland Médium electronic-ecollection

Typ dokumentu multicentrická studie, časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/pmid38022829

PURPOSE: The Phenotypes of COPD in Central and Eastern Europe (POPE) study assessed the prevalence and clinical characteristics of four clinical COPD phenotypes, but not mortality. This retrospective analysis of the POPE study (RETRO-POPE) investigated the relationship between all-cause mortality and patient characteristics using two grouping methods: clinical phenotyping (as in POPE) and Burgel clustering, to better identify high-risk patients. PATIENTS AND METHODS: The two largest POPE study patient cohorts (Czech Republic and Serbia) were categorized into one of four clinical phenotypes (acute exacerbators [with/without chronic bronchitis], non-exacerbators, asthma-COPD overlap), and one of five Burgel clusters based on comorbidities, lung function, age, body mass index (BMI) and dyspnea (very severe comorbid, very severe respiratory, moderate-to-severe respiratory, moderate-to-severe comorbid/obese, and mild respiratory). Patients were followed-up for approximately 7 years for survival status. RESULTS: Overall, 801 of 1,003 screened patients had sufficient data for analysis. Of these, 440 patients (54.9%) were alive and 361 (45.1%) had died at the end of follow-up. Analysis of survival by clinical phenotype showed no significant differences between the phenotypes (P=0.211). However, Burgel clustering demonstrated significant differences in survival between clusters (P<0.001), with patients in the "very severe comorbid" and "very severe respiratory" clusters most likely to die. Overall survival was not significantly different between Serbia and the Czech Republic after adjustment for age, BMI, comorbidities and forced expiratory volume in 1 second (hazard ratio [HR] 0.80, 95% confidence interval [CI] 0.65-0.99; P=0.036 [unadjusted]; HR 0.88, 95% CI 0.7-1.1; P=0.257 [adjusted]). The most common causes of death were respiratory-related (36.8%), followed by cardiovascular (25.2%) then neoplasm (15.2%). CONCLUSION: Patient clusters based on comorbidities, lung function, age, BMI and dyspnea were more likely to show differences in COPD mortality risk than phenotypes defined by exacerbation history and presence/absence of chronic bronchitis and/or asthmatic features.

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World Health Organization. WHO global report on trends in prevalence of tobacco use 2000–2025, third edition; 2019. Available from: https://www.who.int/publications/i/item/who-global-report-on-trends-in-prevalence-of-tobacco-use-2000-2025-third-edition. Accessed April 2023.

Yang IA, Jenkins CR, Salvi SS. Chronic obstructive pulmonary disease in never-smokers: risk factors, pathogenesis, and implications for prevention and treatment. Lancet Respir Med. 2022;10(5):497–511. doi:10.1016/S2213-2600(21)00506-3 PubMed DOI

Zbozinkova Z, Barczyk A, Tkacova R, et al. POPE study: rationale and methodology of a study to phenotype patients with COPD in Central and Eastern Europe. Int J Chron Obstruct Pulmon Dis. 2016;11:611–622. doi:10.2147/COPD.S88846 PubMed DOI PMC

Koblizek V, Milenkovic B, Barczyk A, et al. Phenotypes of COPD patients with a smoking history in Central and Eastern Europe: the POPE study. Eur Respir J. 2017;49(5):1601446. doi:10.1183/13993003.01446-2016 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

Brat K, Svoboda M, Zatloukal J, et al. The relation between clinical phenotypes, GOLD groups/stages and mortality in COPD patients–a prospective multicenter study. Int J Chron Obstruct Pulmon Dis. 2021;16:1171–1182. doi:10.2147/COPD.S297087 PubMed DOI PMC

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

Rennard SI, Locantore N, Delafont B, et al. Identification of five chronic obstructive pulmonary disease subgroups with different prognoses in the ECLIPSE cohort using cluster analysis. Ann Am Thorac Soc. 2015;12(3):303–312. doi:10.1513/AnnalsATS.201403-125OC PubMed DOI

Tiew PY, San Ko FW, Narayana JK, et al. “High-risk” clinical and inflammatory clusters in COPD of Chinese descent. Chest. 2020;158(1):145–156. doi:10.1016/j.chest.2020.01.043 PubMed DOI PMC

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

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 P-R, Paillasseur J-L, Janssens W, et al. 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

Miravitlles M, Soler-Cataluna JJ, Calle M, Soriano JB. Treatment of COPD by clinical phenotypes: putting old evidence into clinical practice. Eur Respir J. 2013;41(6):1252–1256. doi:10.1183/09031936.00118912 PubMed DOI

Gagatek S, Wijnant SRA, Stallberg B, et al. Validation of clinical COPD phenotypes for prognosis of long-term mortality in Swedish and Dutch cohorts. COPD. 2022;19(1):330–338. doi:10.1080/15412555.2022.2039608 PubMed DOI

Kaur M, Chandel J, Malik J, Naura AS. Particulate matter in COPD pathogenesis: an overview. Inflam Res. 2022;71(7–8):797–815. doi:10.1007/s00011-022-01594-y PubMed DOI

Lamprecht B, McBurnie MA, Vollmer WM, et al. COPD in never smokers: results from the population-based burden of obstructive lung disease study. Chest. 2011;139(4):752–763. doi:10.1378/chest.10-1253 PubMed DOI PMC

Salvi SS, Barnes PJ. Chronic obstructive pulmonary disease in non-smokers. Lancet. 2009;374(9691):733–743. doi:10.1016/S0140-6736(09)61303-9 PubMed DOI

Agusti A, Vogelmeier C, Faner R. COPD 2020: changes and challenges. Am J Physiol Lung Cell Mol Physiol. 2020;319(5):L879–L883. doi:10.1152/ajplung.00429.2020 PubMed DOI

Valipour A, Aisanov Z, Avdeev S, et al. Recommendations for COPD management in Central and Eastern Europe. Expert Rev Respir Med. 2022;16(2):221–234. PubMed

Chai C-S, Liam C-K, Pang Y-K, et al. Clinical phenotypes of COPD and health-related quality of life: a cross-sectional study. Int J Chron Obstruct Pulmon Dis. 2019;14:565–573. doi:10.2147/COPD.S196109 PubMed DOI PMC

Miravitlles M, Roman-Rodriguez M, Ribera X, Ritz J, Izquierdo JL; Opti Investigator's Group. Inhaled corticosteroid use among COPD patients in primary care in Spain. Int J Chron Obstruct Pulmon Dis. 2022;17:245–258. doi:10.2147/COPD.S342220 PubMed DOI PMC

Han MK, Agusti A, Calverley PM, et al. Chronic obstructive pulmonary disease phenotypes: the future of COPD. Am J Respir Crit Care Med. 2010;182(5):598–604. doi:10.1164/rccm.200912-1843CC PubMed DOI PMC

Lange P, Halpin DM, O’Donnell DE, MacNee W. Diagnosis, assessment, and phenotyping of COPD: beyond FEV1. Int J Chron Obstruct Pulmon Dis. 2016;11(Spec Iss):3–12. doi:10.2147/COPD.S85976 PubMed DOI PMC

Dal Negro RW, Carone M, Cuttitta G, et al. Prevalence and clinical features of most frequent phenotypes in the Italian COPD population: the CLIMA Study. Multidiscip Respir Med. 2021;16(1):790. doi:10.4081/mrm.2021.790 PubMed DOI PMC

Marques A, Souto-Miranda S, Machado A, et al. COPD profiles and treatable traits using minimal resources: identification, decision tree and stability over time. RespirRes. 2022;23(1):30. PubMed PMC

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