Rationale and design of the Early Chronic Obstructive Pulmonary Disease (ECOPD) study in Guangdong, China: a prospective observational cohort study

Fan Wu; Yumin Zhou; Jieqi Peng; Zhishan Deng; Xiang Wen; Zihui Wang; Youlan Zheng; Heshen Tian; Huajing Yang; Peiyu Huang; Ningning Zhao; Ruiting Sun; Rongchang Chen; Pixin Ran

doi:10.21037/jtd-21-1379

Rationale and design of the Early Chronic Obstructive Pulmonary Disease (ECOPD) study in Guangdong, China: a prospective observational cohort study

J Thorac Dis. 2021 Dec;13(12):6924-6935. doi: 10.21037/jtd-21-1379.

Authors

Fan Wu^#^{1

2}, Yumin Zhou^#^{1

2}, Jieqi Peng¹, Zhishan Deng¹, Xiang Wen¹, Zihui Wang¹, Youlan Zheng¹, Heshen Tian¹, Huajing Yang¹, Peiyu Huang¹, Ningning Zhao¹, Ruiting Sun¹, Rongchang Chen³, Pixin Ran^{1

2}

Affiliations

¹ National Center for Respiratory Medicine, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
² Guangzhou Laboratory, Bio-Island, Guangzhou, China.
³ Shenzhen Institute of Respiratory Disease, Shenzhen People's Hospital, Shenzhen, China.

^# Contributed equally.

Abstract

Background: Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease and its clinically relevant subtypes are not well understood. Which clinical characteristics are more likely to be present among individuals who develop COPD remains to be studied in depth. Therefore, we designed a prospective observational cohort study, entitled the Early Chronic Obstructive Pulmonary Disease (ECOPD) study, to fill this evidence gap. The ECOPD study has four specific aims: (I) identification of characteristics, parameters, and biomarkers that may predict the development of airflow obstruction and annual decline in lung function with normal spirometry; (II) identification of clinically relevant early COPD subtypes; (III) identification of characteristics, parameters, and biomarkers that may predict disease progression in these early COPD subtypes; (IV) development and validation of machine learning models to predict development of airflow obstruction and disease progression.

Methods: We will recruit approximately 2,000 participants aged 40-80 years, including approximately 1,000 with COPD [post-bronchodilator forced expiratory volume in 1 second (FEV1)/forced vital capacity (FVC) <0.7] and approximately 1,000 without COPD, using a population-based survey for COPD. We will assess all participants using standard respiratory epidemiological questionnaires, pulmonary function tests [pre-bronchodilator and post-bronchodilator spirometry, and impulse oscillometry (IOS)], health outcomes [modified British Medical Research Council (mMRC) dyspnea scale, COPD assessment test (CAT), COPD clinical questionnaire (CCQ)], inspiratory and expiratory chest computed tomography (CT), and biomarker measurements (blood and urine), as well as satellite remote sensing pollutant exposure measures. Subgroup will additionally complete induced sputum, exercise capacity tests [6-minute walk test (6MWT) and cardiopulmonary exercise testing (CPET)] and home monitoring/personal sampling as pollutant exposure measures. Study procedures will be performed at baseline and every 1 year thereafter.

Discussion: The ECOPD study will provide insight into many aspects of early COPD and improve our understanding of COPD development, which may facilitate therapeutic interventions with the potential to modify the course of disease.

Trial registration: Chinese Clinical Trial Registry, ChiCTR1900024643. Registered on 19 July, 2019.

Keywords: Chronic obstructive pulmonary disease (COPD); cohort study; early chronic obstructive pulmonary disease; pre-chronic obstructive pulmonary disease; subtype.