Asthma and chronic obstructive pulmonary disease (COPD) are complex diseases whose definitions overlap.
To investigate clustering of clinical/physiological features and readily available biomarkers in patients with physician-assigned diagnoses of asthma and/or COPD in NOVELTY (NCT02760329).
Two approaches were taken to variable selection, using baseline data: approach A was data119 driven, hypothesis-free, using Pearson’s dissimilarity matrix; approach B used an unsupervised Random Forest guided by clinical input. Cluster analyses were conducted across 100 random resamples using partitioning around medoids, followed by consensus clustering.
Approach A included 3,796 individuals (mean age 59.5 years, 54% female); approach B included 2,934 patients (mean age 60.7 years, 53% female). Each identified six mathematically stable clusters, which had overlapping characteristics. Overall, 67–75% of asthma patients were in three clusters, and ~90% of COPD patients in three clusters.
Although traditional features like allergies and current/ex-smoking (respectively) were higher in these clusters, there were differences between clusters and approaches in features such as sex, ethnicity, breathlessness, frequent productive cough and blood cell counts. The strongest predictors of approach A cluster membership were age, weight, childhood onset, prebronchodilator FEV1, duration of dust/fume exposure and number of daily medications.
Cluster analyses in NOVELTY patients with asthma and/or COPD yielded identifiable clusters, with several discriminatory features that differed from conventional diagnostic characteristics. The overlap between clusters suggests that they do not reflect discrete underlying mechanisms, and points to the need for identification of molecular endotypes and potential treatment targets across asthma and/or COPD.
|Number of pages
|The Journal of Allergy and Clinical Immunology: In Practice
|Early online date
|23 May 2023
|Published - Sept 2023
The NOVELTY study is funded by AstraZeneca.
The authors would like to thank the patients who participated in this study and the NOVELTY Scientific Community and the NOVELTY study investigators who are listed in full in Tables E7 and E8 in the Online Repository. Medical writing support, under the direction of the authors, was provided by Richard Knight, PhD, CMC Connect, a division of IPG Health Medical Communications, funded by AstraZeneca in accordance with Good Publication Practice (GPP 2022) guidelines (Ann Intern Med. 2022;175:1298-1304). J. Vestbo is supported by the NIHR Manchester Biomedical Research Centre and the NIHR Manchester Clinical Research Facility
- Precision medicine
- chronic obstructive pulmonary disease
- cluster analysis