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Archivos de Bronconeumología
Article . 2022 . Peer-reviewed
License: Elsevier TDM
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Deconstruyendo los fenotipos en la EPOC: un análisis de la cohorte TRACE

Authors: Carrasco Hernández, Laura; Caballero-Eraso, Candela; Ruiz-Duque, Borja; Abad Arranz, María; Márquez-Martín, Eduardo; Calero-Acuña, Carmen; López-Campos, J. L.;

Deconstruyendo los fenotipos en la EPOC: un análisis de la cohorte TRACE

Abstract

[EN] Objetivos: En una estrategia de manejo de la enfermedad pulmonar obstructiva crónica (EPOC) basada en fenotipos clínicos sería deseable que todos los pacientes pudieran adscribirse al menos a un fenotipo sin adscribirse a otro. El objetivo de este trabajo fue evaluar si todos los pacientes tienen un fenotipo y sólo uno asignado según la actual guía española de la EPOC (GesEPOC 2017) y evaluar los criterios que los definen. Método: El estudio Time-based Register and Analysis of COPD Endpoints (TRACE; clinicaltrials.gov NCT03485690) es una cohorte prospectiva de pacientes con EPOC en visitas anuales desde 2012 que recoge los fenotipos GesEPOC. A pesar de que GesEPOC recomienda no fenotipar a los pacientes considerados de bajo riesgo, se realizó un análisis de los criterios de identifican los fenotipos en alto y bajo riesgo, comparando la distribución de los fenotipos y sus criterios en estos dos grupos. Resultados: La cohorte incluye 970 pacientes con diagnóstico confirmado de EPOC, divididos en 427 (44,02%) pacientes de bajo riesgo y 543 (55,9%) de alto riesgo. El fenotipo más frecuente fue el no agudizador (44,9% de los pacientes de alto riesgo). Un 20,6% de los pacientes de bajo riesgo cumplían criterios de solapamiento entre EPOC y asma. Un 9,2% de la cohorte no cumplía los criterios diagnósticos de ningún fenotipo y el 19,1% cumplía los criterios de dos fenotipos, sin diferencias entre grupos de riesgo. Conclusiones: Nuestros datos ponen de manifiesto algunas de las debilidades de la actual estrategia basada en fenotipos clínicos, existiendo solapamiento en algunos casos y pacientes sin fenotipos. [EN] Objectives: In a clinical phenotype-based management strategy for COPD, it would be preferable to at least assign all patients to a phenotype, but to a single phenotype only. The aim of this study was to evaluate whether all patients are assigned to one and only one phenotype using the Spanish COPD guidelines (GesEPOC) and to evaluate the criteria that define these categories. Method: The Time-based Register and Analysis of COPD Endpoints study (TRACE; clinicaltrials.gov NCT03485690) is a prospective cohort of COPD patients attending annual visits since 2012, which collects GesEPOC phenotypes. Although the GesEPOC recommends that patients considered to be at low risk are not phenotyped, an analysis of the criteria for identifying high- and low-risk phenotypes was performed, comparing the distribution of phenotypes and the criteria applied between these 2 groups. Results: The cohort included 970 patients with a confirmed diagnosis of COPD, divided into 427 (44.02%) low-risk and 543 (55.9%) high-risk patients. The most frequent phenotype was the non-exacerbator (44.9% of high-risk patients). Overall, 20.6% of low-risk patients met criteria for asthma-COPD overlap syndrome, while 9.2% of the cohort did not meet the diagnostic criteria for any phenotype, and 19.1% met the criteria for 2 phenotypes, with no differences between risk groups. Conclusions: Our data highlight some of the weaknesses of the current clinical phenotype strategy, revealing overlapping categories in some cases, and patients to whom no phenotype was assigned. El proyecto TRACE (clinicaltrials.gov NCT03485690) ha sido financiado con una beca no condicionada de Laboratorios Gebro Phama (Barcelona, España).

Keywords

Control, COPD, EPOC, Medicina personalizada, Clinical phenotypes, Fenotipos clínicos, Personalized medicine

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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