An Observational Study for the Investigation and Classification of Treatable Traits in Patients With Chronic Airway Diseases
Conditions: Asthma (Diagnosis), Chronic Obstructive Pulmonary Disease (COPD), Chronic Airway Diseases
Sponsor: Beijing Chao Yang Hospital

 
                                                                        
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Version: 2.0 
Date: November 20, 2023 
 
 
 
 
Investigation and Classification of Treatable Traits in 
Patients with Chronic Airway Diseases 
 
 
 
 
 
 
Research Unit: Beijing Chao-Yang Hospital, Capital Medical University 
Study Director: Kewu Huang, M.D. 
 
 
 
 
 
 

 
                                                                        
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1. Introduction 
1.1. Background 
Chronic Obstructive Pulmonary Disease (COPD) and bronchial asthma (asthma) are 
common chronic airway diseases that severely impact public health. Globally, 
approximately 600 million people are affected. In 2015, about 3.2 million people died 
from COPD worldwide, and 400,000 died from asthma[1]. In China, chronic airway 
diseases represented by COPD and asthma have become major chronic conditions 
seriously endangering the health of the population. Results from the China Pulmonary 
Health (CPH) study, led by our team, indicate that the prevalence of COPD among 
people aged 20 and above in China is 8.6%[2], and the prevalence of asthma is 4.2%[3]. 
Chronic airway diseases impose a substantial healthcare burden. However, despite 
continuously rising medical costs for these diseases, key clinical outcomes have not 
shown corresponding improvement[4,5]，Personalized treatment tailored to different 
patient subtypes is crucial to addressing this dilemma. 
It has been established that chronic airway diseases exhibit significant heterogeneity. 
Different phenotypes exist among asthma patients, such as allergic asthma, late-onset 
asthma, smoking-related asthma, and obesity-related asthma[6]. Similarly, COPD 
patients present with various phenotypes including mild stable, emphysematous type, 
intermediate type, multiple comorbidities, and multifactorial inflammatory type[7]. 
Applying traditional, uniform treatment regimens to different phenotypic patients falls 
short of meeting the actual needs of disease treatment and management. In clinical 
practice, there is a need to identify more precise treatable traits for patient 
classification and personalized management. Several treatable traits beneficial for the 
individualized management of patients with chronic airway diseases have already 
been identified, for example, blood eosinophil count[8] and serum allergen-specific 
IgE[9]， which have demonstrated clinical utility. There is a pressing need to discover 
and validate more clinically significant traits to provide a basis for the subsequent 
implementation of personalized patient management. 
1.2. Rationale 
Previous research has found that differences in dyspnea perception among 
populations with chronic airway diseases may lead to different disease outcomes. In 
asthma patients, approximately 26% of subjects exhibit low dyspnea perception. 
During follow-up, patients with low perception had higher rates of emergency 
department visits, hospitalizations, near-fatal asthma attacks, and mortality compared 
to groups with normal or high perception, suggesting that reduced dyspnea perception 
may predispose asthma patients to life-threatening acute episodes[10]. In COPD 
patients, it has also been observed that after repeated carbon dioxide breathing, 
patients in the frequent exacerbator group exhibited enhanced dyspnea perception, 
whereas those in the infrequent exacerbator group showed weakened perception. This 
mechanism may contribute to the difference in exacerbation frequency between the 

 
                                                                        
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two groups[11]. Consequently, abnormal dyspnea perception may be one of the risk 
factors leading to refractory chronic airway diseases, and patients with such abnormal 
perception might represent a novel subtype of chronic airway disease. 
However, the influencing factors of dyspnea perception remain unclear. Some 
studies suggest potential associations with age [12]、gender[13]、airway inflammation[14]、
psychological 
and 
emotional 
factors[15,16]among 
others. 
Nevertheless, 
a 
comprehensive description of this trait in patients with chronic airway diseases is still 
lacking, and we do not fully understand the distribution of dyspnea perception and its 
determinants in this population. This study aims to investigate the distribution and 
risk factors of abnormal dyspnea perception in patients with chronic airway diseases. 
By collecting and analyzing other relevant clinical data from these patients, we intend 
to construct a clinical classification of chronic airway diseases based on dyspnea 
perception and further identify more treatable traits. The goal is to enable more 
precise personalized management of patients in clinical practice[17], addressing the 
urgent need to reduce the frequency of disease exacerbations, disability, and 
mortality. 
1.3. Study Objectives 
This project aims to investigate the distribution of dyspnea perception within 
established chronic airway disease cohorts from community screenings and 
hospital-based populations, identify novel subtypes classified by dyspnea perception, 
analyze their relationships with known biomarkers and other treatable traits, and 
explore new treatable traits contributing to refractory chronic airway diseases. The 
findings will provide a foundation for subsequent implementation of personalized 
management strategies for patients. 
2. Study Objectives 
2.1. Primary and Quantitative Objectives 
Primary Objectives 
Quantitative Targets 

 
                                                                        
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⚫ To clarify the distribution of dyspnea 
perception in chronic airway diseases. 
⚫ To construct novel subtypes of chronic 
airway diseases based on the degree of 
dyspnea perception and analyze their 
relationship with known biomarkers 
and other treatable traits. 
⚫ 
To observe the changes in dyspnea 
perception 
during 
follow-up 
and 
explore its relationship with outcome 
measures such as acute exacerbations, 
occurrence 
of 
comorbidities, 
hospitalizations, and mortality. 
⚫ Complete dyspnea perception measurements 
in 800 chronic airway disease subjects. 
⚫ Complete repeat dyspnea perception 
measurements one year after baseline in 200 
subjects. 
⚫ Complete measurements of biomarkers and 
other treatable traits (e.g., head MRI) in 300 
patients. 
⚫ Apply for 1-2 patents or software copyrights. 
⚫ Publish 2-4 Chinese and English articles; 
train 4 postgraduate students. 
3. Methods 
3.1. Source of Funding 
This study is supported by the municipal fiscal science and technology funds, 
specifically from the Respiratory Institute's Reform and Development Project 
"Phenotype-based Prognosis and Individualized Diagnosis and Treatment Research 
for Chronic Airway Diseases." 
3.2. Study Design 
This is a 3-year observational study. It will involve dyspnea perception 
measurement, pulmonary function tests, blood sample testing, quality of life 
assessment, recording of acute exacerbations and comorbidities, and collection of 
other clinical information in 800 participants with chronic airway diseases. 
Additionally, 150 normal control subjects will undergo dyspnea perception 
measurement, pulmonary function tests, blood sample testing, and clinical 
information collection. Participants with good compliance will undergo regular 
follow-up, including brain functional magnetic resonance imaging (fMRI) 
examinations alongside repeated dyspnea perception measurements. The study will 
analyze the relationship between dyspnea perception and known biomarkers as well 

 
                                                                        
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as other treatable traits, aiming to identify new treatable traits underlying refractory 
chronic airway diseases. 
3.3. Study Population: 
This study will recruit approximately 800 participants with COPD or asthma 
and 150 normal control subjects from hospitals and the community. Participants with 
COPD or asthma will be aged 20-75 years, must meet the diagnostic criteria for 
COPD according to the 2022 GOLD guidelines or the diagnostic criteria for asthma 
according to the 2022 GINA guidelines, must be able to participate in the study per 
protocol, and must provide written informed consent before participating. 
1.1.1.1. Inclusion Criteria: 
Participants with COPD or asthma must meet all the following criteria: 
• Age 20-75 years. 
• Meet the diagnostic criteria for COPD according to the 2022 GOLD guidelines 
OR meet the diagnostic criteria for asthma according to the 2022 GINA 
guidelines. 
• Agree to participate in the study and provide written informed consent. 
Normal control subjects must meet all the following criteria: Age ≥20 years; no 
asthma symptoms and no previous diagnosis of chronic respiratory diseases such as 
asthma or chronic obstructive pulmonary disease; must provide written informed 
consent before participation and be able to participate in the study and follow-up per 
protocol. 
1.1.1.2. Exclusion Criteria: 
Study participants must not meet any of the following criteria: 
• Respiratory tract infection, acute exacerbation of COPD, or acute asthma attack 
within the past 3 months. 
• Presence of other diseases causing substantial lung tissue destruction, such as 
severe bronchiectasis or tuberculosis. 

 
                                                                        
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• History of thoracic or abdominal surgery within the past 3 months. 
• Heart rate >120 beats per minute. 
• Currently undergoing anti-tuberculosis treatment. 
• Presence of other severe, uncontrolled systemic diseases. 
• Pregnant or lactating women. 
1.1.1.3. 变量及人口学数据Variables and Demographic Data 
1.1.1.4. 暴露Exposure 
The patient's treatment regimen will be determined by their treating physician. 
No investigational drugs will be administered as part of this study. The study will 
collect information on the patient's current respiratory medication and specific 
concomitant medications. 
1.1.1.5. Variables 
• Demographic Data: Includes sex, date of birth, height, weight, living 
environment, education level/years of formal education; smoking 
history/secondhand smoke exposure history; occupational exposure history; 
biofuel exposure history. 
• Clinical Information: Duration since diagnosis of COPD/chronic 
bronchitis/emphysema/asthma and age at onset; current respiratory symptoms 
such as shortness of breath, chest tightness, cough, wheezing, sputum 
production; past family history; allergy history/atopy. 
• Previous Exacerbation History: Exacerbations within the 12 months prior to 
baseline: number of exacerbations, exacerbation severity (use of systemic 
corticosteroids/antibiotics/emergency department visit/hospitalization), and 
length of hospital stay or number of emergency department visit days. 
• Comorbidities: Comorbidities present prior to the baseline visit. 
• Treatments: Current medications for COPD/asthma/chronic respiratory 
symptoms (type/duration of use/dosage/frequency), and non-pharmacological 
treatments; specific concomitant medications (e.g., corticosteroids). 
• Pulmonary Function Tests: Spirometry with bronchodilator test; lung volume 
measurements; diffusing capacity test; fractional exhaled nitric oxide (FeNO) 
measurement; dyspnea perception measurement. 
• Blood Tests: Complete blood count, inhalant allergen screen, total IgE. 
• Imaging: Chest HRCT scan (high-resolution computed tomography in 
inspiratory and expiratory phases). 

 
                                                                        
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• Health-Related Quality of Life: Assessed using the COPD Assessment Test 
(CAT), the Modified British Medical Research Council (mMRC) dyspnea scale, 
the Asthma Quality of Life Questionnaire (AQLQ), and the St. George's 
Respiratory Questionnaire (SGRQ). 
• Dyspnea Perception Measurement. 
• Brain Functional Magnetic Resonance Imaging (fMRI). 
4. Data Processing  
All statistical analyses will be performed using the Full Analysis Set (FAS), 
which includes all patients who were enrolled and met the inclusion/exclusion criteria. 
Missing data will be analyzed as is, without imputation. 
The epidemiology and statistics working group at the Chinese Academy of 
Medical Sciences will perform the statistical analyses using SAS and SUDAAN 
software. 
The analysis methods will primarily be descriptive. For continuous variables, 
summary statistics will include number of observations, mean, median, standard 
deviation, minimum, and maximum values. For categorical variables, frequencies and 
percentages will be calculated for each category. 
Linear regression or logistic regression and multivariate analysis will be used to 
explore the relationship between dyspnea perception and disease outcomes. 
4.1. Interim Analysis 
An interim analysis will be conducted when the number of enrolled subjects 
reaches 400. The date when the 400th patient is enrolled will be considered the 
interim analysis date. 
4.2. Data Management 
This study will utilize an Electronic Data Capture (EDC) system for data entry 
via a password-protected web-based platform. Spirometry data from pulmonary 
function tests will be transmitted daily to the web-based data entry platform. Within a 
48-hour interval, researchers will grade the quality of the pulmonary function tests 
(FEV1, FVC, and diffusing capacity) according to an academic grading system (A, B, 
C, D, or E). 
The completeness and accuracy of questionnaire variables will be checked. 
Before data upload, the questionnaire administrator must identify and clarify any 
obvious errors or omissions in the questionnaires. Prior to statistical analysis, the 
consistency of dual-entered data will be checked, and paper questionnaires will be 
scanned and stored securely. 

 
                                                                        
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5. Study Oversight 
The Project Leader will be responsible for overseeing the entire research process. 
Two working groups will be established, responsible for project implementation 
supervision and data cleaning/analysis, respectively. The leaders of these working 
groups will report study progress monthly to the Project Leader. 
6. Collection and Reporting of Adverse Events / Adverse Drug 
Reactions 
6.1. Definition of Adverse Events (AE) 
An Adverse Event (AE) is any unfavorable medical occurrence in a patient or 
clinical trial subject administered a pharmaceutical product, which does not 
necessarily have a causal relationship with the treatment. Therefore, an adverse event 
can be any unfavorable sign (e.g., an abnormal laboratory finding), symptom, or 
disease temporally associated with the use of an investigational product, whether or 
not considered related to the product. 
The term "adverse event" encompasses both serious and non-serious adverse 
events. 
6.2. Definition of Serious Adverse Events (SAE) 
A Serious Adverse Event (SAE) is any adverse event occurring at any stage of 
the study (i.e., run-in period, treatment period, washout period, follow-up period) that 
meets one or more of the following criteria: 
• Results in death 
• Is life-threatening (in this context, "life-threatening" refers to the patient being at 
risk of death at the time of the event; it does not refer to an event which 
hypothetically might have caused death if it were more severe) 
• Requires inpatient hospitalization or prolongation of existing hospitalization 
• Results in persistent or significant disability/incapacity 
• Is a congenital anomaly/birth defect 
• Is an important medical event that may jeopardize the subject or may require 
medical or surgical intervention to prevent one of the outcomes listed above. 
• Medical judgment should be exercised in deciding whether other situations 
should be considered serious adverse events. 

 
                                                                        
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• Any suspected transmission of a pathogenic agent via a medicinal product is 
considered an SAE, and some countries require prompt reporting of such events. 
Any biological, viral, or infectious agent (e.g., a prion transmitting infectious 
spongiform encephalopathies), whether pathogenic or non-pathogenic, is 
considered a transmissible agent. 
1.1.1.6. Definition of Adverse Drug Reactions，ADR 
An Adverse Drug Reaction (ADR) is an adverse event for which a causal 
relationship with the drug use is suspected. 
An ADR is a harmful and unintended response to a drug. Adverse reactions may 
arise from use within or outside the terms of the marketing authorization, including 
those resulting from occupational exposure. 
The term "adverse drug reaction" includes both serious and non-serious adverse 
drug reactions. 
1.1.1.7. Reporting of Adverse Events 
As this is a non-interventional study, and the drugs used by participants are 
prescribed by the investigator according to clinical practice, adverse events will not be 
actively collected. 
The investigator is responsible for ensuring that all personnel involved in the 
study are familiar with the content of this section. 
7. Study Timfline 
This study is anticipated to commence in the first quarter of 2023 and be 
completed by the fourth quarter of 2027. The study endpoint is defined as 
"completion of all analyses related to the study." 
Study Milestone 
Estimated Date 
Protocol Approval 
March 2023 
Enrollment of First Participant 
March 2023 
Enrollment of Last Participant 
December 2025 
Last Visit of Last Participant 
December 2027 
Database Lock 
December 2027 
Final Study Report Completion 
December 2027 
Publication of Final Study Report 
December 2027 
 

 
                                                                        
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