Derivation and validation of clinical phenotypes for COPD: a systematic review.
BACKGROUND
The traditional classification of COPD, which relies solely on spirometry, fails to account for the complexity and heterogeneity of the disease. Phenotyping is a method that attempts to derive a single or combination of disease attributes that are associated with clinically meaningful outcomes. Deriving phenotypes entails the use of cluster analyses, and helps individualize patient management by identifying groups of individuals with similar characteristics. We aimed to systematically review the literature for studies that had derived such phenotypes using unsupervised methods.


METHODS
Two independent reviewers systematically searched multiple databases for studies that performed validated statistical analyses, free of definitive pre-determined hypotheses, to derive phenotypes among patients with COPD. Data were extracted independently.


RESULTS
9156 citations were retrieved, of which, 8 studies were included. The number of subjects ranged from 213 to 1543. Most studies appeared to be biased: patients were more likely males, with severe disease, and recruited in tertiary care settings. Statistical methods used to derive phenotypes varied by study. The number of phenotypes identified ranged from 2 to 5. Two phenotypes, with poor longitudinal health outcomes, were common across multiple studies: young patients with severe respiratory disease, few cardiovascular co-morbidities, poor nutritional status and poor health status, and a phenotype of older patients with moderate respiratory disease, obesity, cardiovascular and metabolic co-morbidities.


CONCLUSIONS
The recognition that two phenotypes of COPD were often reported may have clinical implications for altering the course of the disease. This review also provided important information on limitations of phenotype studies in COPD and the need for improvement in future studies.
Respiratory Division, McGill University Health Centre, Montreal, Quebec, Canada. lancelot.pinto@mail.mcgill.ca.|Respiratory Epidemiology and Clinical Research Unit, Montreal Chest Institute, McGill University Health Centre, Montreal, Quebec, Canada. lancelot.pinto@mail.mcgill.ca.
Lancelot M
LM
Pinto
Respiratory Division, McGill University Health Centre, Montreal, Quebec, Canada. majed.rabia@gmail.com.|Respiratory Epidemiology and Clinical Research Unit, Montreal Chest Institute, McGill University Health Centre, Montreal, Quebec, Canada. majed.rabia@gmail.com.
Majed
M
Alghamdi
Respiratory Epidemiology and Clinical Research Unit, Montreal Chest Institute, McGill University Health Centre, Montreal, Quebec, Canada. andrea.benedetti@mcgill.ca.|Department of Epidemiology, Biostatistics & Occupational Health, Montreal, Quebec, Canada. andrea.benedetti@mcgill.ca.
Andrea
A
Benedetti
School of PH & OT, Faculty of Medicine, McGill University, Quebec, Canada. tasneem.zaihra@mail.mcgill.ca.|Division of Clinical Epidemiology, McGill University Health Centre, Montreal, Quebec, Canada. tasneem.zaihra@mail.mcgill.ca.
Tasneem
T
Zaihra
Medical Library, Montreal General Hospital, McGill University Health Centre, Montreal, Quebec, Canada. tara.landry@mail.mcgill.ca.
Tara
T
Landry
Respiratory Division, McGill University Health Centre, Montreal, Quebec, Canada. jean.bourbeau@mcgill.ca.|Respiratory Epidemiology and Clinical Research Unit, Montreal Chest Institute, McGill University Health Centre, Montreal, Quebec, Canada. jean.bourbeau@mcgill.ca.|Montreal Chest Institute, McGill University Health Centre, 3650 St.Urbain, Room K1.32, H2X 2P4, Montréal (Québec), Canada. jean.bourbeau@mcgill.ca.
Jean
J
Bourbeau
D006304:Health Status; D006801:Humans; D010641:Phenotype; D029424:Pulmonary Disease, Chronic Obstructive / Q000175:diagnosis* / Q000453:epidemiology*