Are there specific clinical characteristics associated with physician's treatment choices in COPD?


Journal

Respiratory research
ISSN: 1465-993X
Titre abrégé: Respir Res
Pays: England
ID NLM: 101090633

Informations de publication

Date de publication:
20 Aug 2019
Historique:
received: 06 04 2019
accepted: 05 08 2019
entrez: 21 8 2019
pubmed: 21 8 2019
medline: 8 2 2020
Statut: epublish

Résumé

The number of pharmacological agents and guidelines available for COPD has increased markedly but guidelines remain poorly followed. Understanding underlying clinical reasoning is challenging and could be informed by clinical characteristics associated with treatment prescriptions. To determine whether COPD treatment choices by respiratory physicians correspond to specific patients' features, this study was performed in 1171 patients who had complete treatment and clinical characterisation data. Multiple statistical models were applied to explain five treatment categories: A: no COPD treatment or short-acting bronchodilator(s) only; B: one long-acting bronchodilator (beta2 agonist, LABA or anticholinergic agent, LAMA); C: LABA+LAMA; D: a LABA or LAMA + inhaled corticosteroid (ICS); E: triple therapy (LABA+LAMA+ICS). Mean FEV1 was 60% predicted. Triple therapy was prescribed to 32.9% (treatment category E) of patients and 29.8% received a combination of two treatments (treatment categories C or D); ICS-containing regimen were present for 44% of patients altogether. Single or dual bronchodilation were less frequently used (treatment categories B and C: 19% each). While lung function was associated with all treatment decisions, exacerbation history, scores of clinical impact and gender were associated with the prescription of > 1 maintenance treatment. Statistical models could predict treatment decisions with a < 35% error rate. In COPD, contrary to what has been previously reported in some studies, treatment choices by respiratory physicians appear rather rational since they can be largely explained by the patients' characteristics proposed to guide them in most recommendations.

Sections du résumé

BACKGROUND BACKGROUND
The number of pharmacological agents and guidelines available for COPD has increased markedly but guidelines remain poorly followed. Understanding underlying clinical reasoning is challenging and could be informed by clinical characteristics associated with treatment prescriptions.
METHODS METHODS
To determine whether COPD treatment choices by respiratory physicians correspond to specific patients' features, this study was performed in 1171 patients who had complete treatment and clinical characterisation data. Multiple statistical models were applied to explain five treatment categories: A: no COPD treatment or short-acting bronchodilator(s) only; B: one long-acting bronchodilator (beta2 agonist, LABA or anticholinergic agent, LAMA); C: LABA+LAMA; D: a LABA or LAMA + inhaled corticosteroid (ICS); E: triple therapy (LABA+LAMA+ICS).
RESULTS RESULTS
Mean FEV1 was 60% predicted. Triple therapy was prescribed to 32.9% (treatment category E) of patients and 29.8% received a combination of two treatments (treatment categories C or D); ICS-containing regimen were present for 44% of patients altogether. Single or dual bronchodilation were less frequently used (treatment categories B and C: 19% each). While lung function was associated with all treatment decisions, exacerbation history, scores of clinical impact and gender were associated with the prescription of > 1 maintenance treatment. Statistical models could predict treatment decisions with a < 35% error rate.
CONCLUSION CONCLUSIONS
In COPD, contrary to what has been previously reported in some studies, treatment choices by respiratory physicians appear rather rational since they can be largely explained by the patients' characteristics proposed to guide them in most recommendations.

Identifiants

pubmed: 31429756
doi: 10.1186/s12931-019-1156-1
pii: 10.1186/s12931-019-1156-1
pmc: PMC6701115
doi:

Substances chimiques

Adrenal Cortex Hormones 0
Adrenergic beta-Agonists 0
Bronchodilator Agents 0
Muscarinic Antagonists 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

189

Subventions

Organisme : Agir à Dom
ID : -
Organisme : AstraZeneca
ID : -
Organisme : Boehringer Ingelheim France
ID : -
Organisme : Chiesi
ID : -
Organisme : GSK
ID : -
Organisme : Novartis
ID : -
Organisme : PneumRX
ID : -

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Auteurs

Nicolas Roche (N)

Service de Pneumologie, Hôpitaux Universitaires Paris Centre, Hôpital Cochin, AP-HP and Université Paris Descartes, Sorbonne Paris Cité, 75014, Paris, France. nicolas.roche@aphp.fr.
Pneumologie et Soins Intensifs Respiratoires, Hôpital Cochin, 27, rue du Fbg St Jacques, 75014, Paris, France. nicolas.roche@aphp.fr.

Anestis Antoniadis (A)

Laboratoire LJK, Département de statistiques, Université Grenoble Alpes, Grenoble, France.

David Hess (D)

Programme Colibri-Pneumo, ACCPP (Association pour la Complémentarité des Connaissances et des Pratiques de la Pneumologie), Grenoble, France.

Pei Zhi Li (PZ)

Respiratory Epidemiology and Clinical Research Unit, Montreal Chest Institute, McGill University, Montreal, Canada.

Eric Kelkel (E)

Service de pneumologie, Pôle médecines spécialisées et cancérologie, Centre hospitalier général, Chambéry, France.

Sylvie Leroy (S)

Department of Pulmonary Medicine and Oncology, CHU de Nice, University Hospital Federation OncoAge, Nice, France.
CNRS UMR 7275 - Institut de Pharmacologie Moléculaire et Cellulaire, Université de Nice Sophia Antipolis, Nice, France.

Christophe Pison (C)

Service Hospitalier Universitaire Pneumologie Physiologie, Pôle Thorax et Vaisseaux, Centre Hospitalier Universitaire Grenoble Alpes, Inserm 1055, Université Grenoble Alpes, Grenoble, France.

Pierre-Régis Burgel (PR)

Service de Pneumologie, Hôpitaux Universitaires Paris Centre, Hôpital Cochin, AP-HP and Université Paris Descartes, Sorbonne Paris Cité, 75014, Paris, France.

Bernard Aguilaniu (B)

Université Grenoble Alpes and Programme Colibri-Pneumo (aCCPP), Grenoble, France.

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Classifications MeSH