Abstract
BACKGROUND: In China, the high prevalence and mortality rate of Chronic Obstructive Pulmonary Disease (COPD) and the poor intervention effect makes it into a heavy social burden. The main reason is that the current diagnosis of COPD mainly based on the static lung function, which is difficult for early intervention. Through matching a predictive model for high-risk groups of COPD that rewards FEV(1) rapid decline as the core, we will establish the early warning model and prove its validity and socio-economic value. METHODS: This is a multi-center, prospective, cohort study. A total of 10,000 people aged 40∼75 without lung disease will be recruited and followed for 3 years. Some questionnaires such as St George's Respiratory Questionnaire (SGRQ), income class, educational level, comorbidity, smoking habit, and biomass smoke exposure history will be collected. The baseline level of Interleukin 6 (IL-6), high-sensitivity C-reactive Protein (hs-CRP), microRNAs-23a (miR-23a) in peripheral blood and pH value in exhaled breath condensate (EBC) will be measured, lung spirometry will be tested in the first, second, and fourth years. Primary outcome is the incidence of COPD, multivariate regression analysis will be used to establish the predictive model for COPD in China. DISCUSSION: With the rapid decline of lung function as the core and the baseline inflammatory biomarkers in peripheral blood and pH of the exhaled breath condensate as affecting factors, a predictive model to achieve early detection of high-risk COPD groups will be established and promoted. TRIAL REGISTRATION: This study has been registered at www.ClinicalTrials.gov (registration identifier: NCT03532893) on 21 May 2018, https://register.clinicaltrials.gov.