University of Surrey, Surrey Business School, Guildford, UK
University of Surrey, Surrey Business School, Guildford, UK.
BMJ Open Respir Res. 2021 Oct;8(1). doi: 10.1136/bmjresp-2021-000980.
Chronic obstructive pulmonary disease (COPD) is a heterogeneous group of lung conditions challenging to diagnose and treat. Identification of phenotypes of patients with lung function loss may allow early intervention and improve disease management. We characterised patients with the 'fast decliner' phenotype, determined its reproducibility and predicted lung function decline after COPD diagnosis.
A prospective 4 years observational study that applies machine learning tools to identify COPD phenotypes among 13 260 patients from the UK Royal College of General Practitioners and Surveillance Centre database. The phenotypes were identified prior to diagnosis (training data set), and their reproducibility was assessed after COPD diagnosis (validation data set).
Three COPD phenotypes were identified, the most common of which was the 'fast decliner'-characterised by patients of younger age with the lowest number of COPD exacerbations and better lung function-yet a fast decline in lung function with increasing number of exacerbations. The other two phenotypes were characterised by (a) patients with the highest prevalence of COPD severity and (b) patients of older age, mostly men and the highest prevalence of diabetes, cardiovascular comorbidities and hypertension. These phenotypes were reproduced in the validation data set with 80% accuracy. Gender, COPD severity and exacerbations were the most important risk factors for lung function decline in the most common phenotype.
In this study, three COPD phenotypes were identified prior to patients being diagnosed with COPD. The reproducibility of those phenotypes in a blind data set following COPD diagnosis suggests their generalisability among different populations.
慢性阻塞性肺疾病（COPD）是一组异质性的肺部疾病，诊断和治疗都具有挑战性。识别肺功能丧失患者的表型可能有助于早期干预和改善疾病管理。我们对具有“快速下降”表型的患者进行了特征描述，确定了其可重复性，并预测了 COPD 诊断后的肺功能下降。
这是一项前瞻性的 4 年观察性研究，应用机器学习工具在英国皇家全科医生学院和监测中心数据库中的 13260 名患者中识别 COPD 表型。在诊断前（训练数据集）识别表型，并在 COPD 诊断后（验证数据集）评估其可重复性。
确定了三种 COPD 表型，最常见的是“快速下降型”，其特征是患者年龄较小，COPD 加重次数最少，肺功能较好，但随着加重次数的增加，肺功能下降较快。另外两种表型的特征分别为：（a）COPD 严重程度发生率最高的患者；（b）年龄较大的患者，主要为男性，糖尿病、心血管合并症和高血压的发生率最高。这些表型在验证数据集中的准确性为 80%。在最常见的表型中，性别、COPD 严重程度和加重是肺功能下降的最重要危险因素。
在这项研究中，在患者被诊断为 COPD 之前确定了三种 COPD 表型。这些表型在 COPD 诊断后盲数据集中的可重复性表明它们在不同人群中的普遍性。
