Abstract

While asthma presentation is heterogeneous, current asthma management guidelines in primary care are quite homogeneous. In this study we aim to cluster patients together into different phenotypes, that may aid the general practitioner in individualised asthma management. We analysed data from the ACCURATE trial, containing 611 adult asthmatics, 18–50 year-old, treated in primary care, with one year follow-up. Variables obtained at baseline (n = 14), were assessed by cluster analysis. Subsequently, established phenotypes were assessed separately on important asthma outcomes after one year follow-up: asthma control (Asthma Control Questionnaire (ACQ)), quality of life (Asthma Quality of Life Questionnaire (AQLQ)), exacerbation-rate and medication-usage. Five distinct phenotypes were identified. The first phenotype was predominantly defined by their early onset atopic form of asthma. The second phenotype mainly consisted of female patients with a late onset asthma. The third phenotype were patients with high reversibility rates after bronchodilator usage. The fourth phenotype were smokers and the final phenotype were frequent exacerbators. The exacerbators phenotype had the worst outcomes for asthma control and quality of life and experienced the highest exacerbation-rate, despite using the most medication. The early onset phenotype patients were relatively well controlled and their medication dosage was low.

Highlights

  • Over 300 million people suffer from asthma globally, which makes it one of the most common chronic diseases in the world.[1]

  • The results described here were generated in a five step process, which is described in detail in our methods section

  • Important long-term asthma outcomes, such as asthma control, quality of life, exacerbation rate and medication usage differed between these phenotypes after 12-month followup

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Summary

Introduction

Over 300 million people suffer from asthma globally, which makes it one of the most common chronic diseases in the world.[1]. The majority of the current hospital care-based phenotypes require certain measurements not available in primary care. This hampers implementation and it would be preferable if primary care phenotypes consist of measurements obtainable to the general practitioner (GP) or practice nurse (PN). As the first part of our study we aimed to cluster primary care asthma patients into distinct phenotypes based on obtainable patient characteristics using a clustering strategy

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