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Identification and analysis of clinical phenotypes in COPD patients: PALOMB Cohort

dc.rights.licenseopenen_US
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorOUAALAYA, El-Hassane
dc.contributor.authorZYSMAN, Maéva
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorBERTEAUD, Emilie
dc.contributor.authorFALQUE, Laurent
dc.contributor.authorMONGE, Emmanuel
dc.contributor.authorNGUYEN, Laurent
dc.contributor.authorOZIER, Annaig
dc.contributor.authorDUPIS, Jean Michel
dc.contributor.authorSABATINI, Marielle
dc.contributor.authorNOCENT-EJNAINI, Cécilia
dc.contributor.authorPETROV, Laura
dc.contributor.authorBERNADY, Alain
dc.contributor.authorROY, Christophe
dc.contributor.authorLE GUILLOU, Frédéric
dc.contributor.authorALIATI, Mohammed
dc.contributor.authorPRUDHOMME, Anne
dc.contributor.authorQUINQUENEL, Marie Line
dc.contributor.authorSTAALI, Mohammed
dc.contributor.authorPILARD, Frederic
dc.contributor.authorIGLESIAS, Esther
dc.contributor.authorSAPÈNE, Marc
dc.contributor.authorCASTEIGT, Julien
dc.contributor.authorMOINARD, Jean
dc.contributor.authorDAOUDI, Yannick
dc.contributor.authorBLANCHARD, Élodie
dc.contributor.authorMACEY, Julie
dc.contributor.authorVEILLON, Rémi
dc.contributor.authorDEMANT, Xavier
dc.contributor.authorBON, Claire
dc.contributor.authorGRASSION, Leo
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorMOLIMARD, Mathieu
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorRAHERISON-SEMJEN, Chantal
dc.date.accessioned2024-05-28T13:16:41Z
dc.date.available2024-05-28T13:16:41Z
dc.date.issued2021-09-05
dc.date.conference2021-09-05
dc.identifier.issn1044-3983en_US
dc.identifier.urioai:crossref.org:10.1183/13993003.congress-2021.pa3502
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/200098
dc.description.abstractEnIn recent years, several researchers have attempted to identify COPD phenotypes using different cluster analysis. This study aimed to determine the most optimal cluster analysis (supervised vs unsupervised) to robustly identify clinical phenotypes. 2,968 COPD patients have been included from January 2014 until February 2020. General information (age, BMI, smoking, comorbidities), lung function, exacerbations and symptoms were collected. After 5 years of follow-up, vital status was recorded. A hierarchical classification on the principal components (HCPC) was performed, followed by two unsupervised classification algorithms: k-means and PAM (Partition Around Medoids). Robustness was defined according to three different indices of validation (Connectivity, Dunn and silhouette). The mean age was 70 years, 63.7% of males, current smokers: 38.7%, mean FEV1: 61.3% predicted, ≥2 exacerbations: 43.6%, mMRC dyspnea grade≥2: 56.3%, chronic cough: 58%. The 5-year mortality rate was 11.3%. Based on our hypothesis, four phenotypes were described, using the PAM method. The phenotype A (24.2%) consisted of elderly patients with severe airflow limitation, low symptoms, cardiovascular comorbidities, diabetes and a higher mortality. The phenotype B (23.9%) contained more female patients, young patients with moderate airflow limitation and a high rate of current smokers. The phenotype C (25.5%) contained patients with very severe airflow limitation, more symptoms and low BMI. The Phenotype D (26.2%) was composed of patients with mild airflow limitation and low dyspnoea. These results showed the superiority of PAM classification compared with two other algorithms (k-means and HCPC) in terms of the robustness.
dc.language.isoENen_US
dc.publisherEuropean Respiratory Societyen_US
dc.sourcecrossref
dc.title.enIdentification and analysis of clinical phenotypes in COPD patients: PALOMB Cohort
dc.typeCommunication dans un congrèsen_US
dc.identifier.doi10.1183/13993003.congress-2021.pa3502en_US
dc.subject.halSciences du Vivant [q-bio]/Santé publique et épidémiologieen_US
bordeaux.pagePA3502en_US
bordeaux.volume58en_US
bordeaux.hal.laboratoriesBordeaux Population Health Research Center (BPH) - UMR 1219en_US
bordeaux.issuesuppl. 65en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionINSERMen_US
bordeaux.conference.title2021 ERS International Congressen_US
bordeaux.title.proceedingEuropean Respiratory Journalen_US
bordeaux.teamEPICENE_BPHen_US
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hal.proceedingsouien_US
hal.conference.organizerEuropean Respiratory Society (ERS)en_US
hal.conference.end2021-09-08
hal.popularnonen_US
hal.audienceInternationaleen_US
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dc.rights.ccPas de Licence CCen_US
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