Personalized Prediction Strategy for Acute Exacerbation of Chronic Obstructive Pulmonary Disease

Establishment of Individualized Prediction System for Acute Exacerbation of Chronic Obstructive Pulmonary Disease Based on Cloud Platform

This is a 3-year longitudinal study designed to establish a personalized prediction and prevention system for acute exacerbations of chronic obstructive pulmonary disease (AECOPD). Data will be prospectively collected from patients with chronic obstructive pulmonary disease (COPD) and healthy control participants, including clinical characteristics, pathophysiological parameters, etiological factors, and immunological information. These data will be analyzed using data mining approaches combined with Internet-based technologies.

Study Overview

• Status: Active, not recruiting
• Conditions: Pulmonary Disease, Chronic Obstructive

• Study Type: Observational
• Enrollment (Actual): 442

Contacts and Locations

Study Locations

• China
  • Guangdong
    • Guangzhou, Guangdong, China, 510120
      • Guangzhou Institute of Respiratory Health,The First Affiliated Hospital of Guangzhou Medical University

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 40 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No

• Sampling Method: Probability Sample

Study Population

COPD subjects in China

Description

Inclusion Criteria:

• Patients was diagnosed as COPD according to Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines older than 40 years old.

  • A signed and dated written informed consent is obtained prior to participation.
  • Able to comply with the requirements of the protocol and be available for study visits over 3 years.

Exclusion Criteria:

• A COPD subject will not be eligible for inclusion in this study if any of the following criteria apply:

  • Known respiratory disorders, or disorders identified at screening/visit 1 (including identification on the first CT scan), other than COPD (e.g.: lung cancer, sarcoidosis, tuberculosis, lung fibrosis, cystic fibrosis)
  • Known history of significant inflammatory disease, other than COPD (e.g. rheumatoid arthritis and Lupus)
  • Known to be severely alpha-1-antitrypsin deficient
  • Has experienced a moderate or severe exacerbation (requiring oral corticosteroid, antibiotics or hospitalisation) within the last 4 weeks
  • Having undergone lung surgery (e.g. lung reduction, lung transplant)
  • Have cancer or have had cancer in the 5 years prior to study entry
  • Having received a blood transfusion in the 4 weeks prior to study start
  • Inability to walk
  • Taking part in a blinded drug study
  • Having therapy with systemic corticosteroids at inclusion.

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort
COPD subjects; Subjects with GOLD stage I-IV COPD
Healthy control subjects; Ages 40 to 90, with no history of lung disease and no history of acute illness or medication use within the past month.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Establishment of prediction platform for COPD exacerbation	The patients with chronic obstruction pulmonary disease will be followed up at intervals of 3 months for 3 years by the Modified British Medical Research Council (mMRC) score scale,spirometric analysis, sputum smear,questionnaire and so on. An exacerbation of COPD was diagnosed according to GOLD guidelines. Time to the first acute exacerbation and average number of acute exacerbations per year in COPD subjects will be record.Research of AECOPD Risk factors based on complex network analysis.Identification and validation of COPD exacerbations risk stratification and predictive markers based on data mining.	3 years

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Developing new protein chips for AECOPD	Systemic and airway autoantibody profiles and cytokine profiles will be measured using commercial multiplex bead-based assay to screen out a set of ideal AECOPD-related markers.	3 years
Detection of immune repertoire in COPD/AECOPD	Immune status of COPD patients will be investigated by using the immune repertoire technique and its relationship with the pathophysiology of AECOPD will be identified.	3 years
Pathogenic microorganism and drug resistance monitoring for COPD exacerbation	Dynamics of pathogenic microorganism and drug resistance in natural course of COPD will be investigated by using the metagenome technique and the culture technique.	3 years

Collaborators and Investigators

• Sponsor: Guangzhou Institute of Respiratory Disease
• Collaborators: The First Affiliated Hospital of Guangzhou Medical University; Guangzhou Science and Technology Innovation Commission,China
• Investigators: Study Director: Rongchang Chen, MD/Ph.D, Guangzhou Institute of Respiratory Health,The First Affiliated Hospital of Guangzhou Medical University,China

Publications and helpful links

General Publications

• Cass SP, Yang Y, Xiao J, McGrath JJC, Fantauzzi MF, Thayaparan D, Wang F, Liang Z, Long F, Stevenson CS, Chen R, Stampfli MR. Current smoking status is associated with reduced sputum immunoglobulin M and G expression in COPD. Eur Respir J. 2021 Feb 4;57(2):1902338. doi: 10.1183/13993003.02338-2019. Print 2021 Feb. No abstract available.
• Li X, Feng S, Yang Y, Liang Z, Song A, Chen J, Guo Z, Chen Z, Miao C, Yang H, He W, Zhou Z, Drummond MB, Chen R, Wang F. Association Between Airway Mucus Plugs and Risk of Moderate-to-Severe Exacerbations in Patients With COPD: Results From a Chinese Prospective Cohort Study. Chest. 2025 Sep;168(3):627-638. doi: 10.1016/j.chest.2025.03.026. Epub 2025 Apr 8.

Study record dates

Study Major Dates

• Study Start (Actual): August 1, 2016
• Primary Completion (Estimated): September 30, 2026
• Study Completion (Estimated): December 30, 2026

Study Registration Dates

• First Submitted: July 31, 2017
• First Submitted That Met QC Criteria: August 2, 2017
• First Posted (Actual): August 7, 2017

Study Record Updates

• Last Update Posted (Estimated): January 12, 2026
• Last Update Submitted That Met QC Criteria: January 9, 2026
• Last Verified: January 1, 2026

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Pathologic Processes; Chronic Disease; Disease Attributes; Respiratory Tract Diseases; Lung Diseases; Lung Diseases, Obstructive; Pathological Conditions, Signs and Symptoms; Pulmonary Disease, Chronic Obstructive
• Other Study ID Numbers: 201604020012; 2017YFC1310600 (Other Grant/Funding Number: Ministry of Science and Technology of the People's Republic of China)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO