TCM Constitution, Pattern Types, and Disease Factors in Primary Lung Cancer.

Risk Factors Clinical Trial

Official title:

A Study on the Correlation Between TCM Constitution, Pattern Types, and Disease Factors in Primary Lung Cancer.

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT06143436
• Other study ID #: CMUH112-REC3-157
• Status: Recruiting
• Start date: December 20, 2023
• Est. completion date: May 19, 2025

Study information

• Verified date: December 2023
• Source: China Medical University Hospital
• Contact: Su-Tso Yang, M.D.
• Phone: 886-4-22052121
• Email: 002794[@]tool.caaumed.org.tw
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Recently, TCM has played an important role in adjuvant therapy for lung cancer. TCM treatment is based on pattern identification, and constitution theory is also used as a tool for TCM to predict the disease progression. Although there have been many researchs related to the pattern identification and constitution of lung cancer, in view of the problems and limitations, further research on lung cancer patients in Taiwan is needed. This study aims to explore the correlation between TCM constitution, pattern identification, and other related factors in patients with primary lung cancer in Taiwan, hoping to reveal the disease characteristics of lung cancer in TCM theory. This study intends to interview subjects through attending physicians in the thoracic ward and outpatient clinic of the CMUH from November 20th, 2023 to May 19th , 2025, and the subjects will be included in this study after the researchers ask the subjects for consent. This study will collect the demographic data of the subjects (sex, age, BMI, smoking history) and disease-related clinical data (tumor stage, pathological type, gene mutation, tumor markers, other comorbidities), and the investigator will ask about the subjects' signs according to the Constitution in Chinese Medicine Questionnaire (CCMQ) , ask the subjects' symptoms according to the pattern identification table, obtain the data to analyze their distribution by descriptive statistics, and then analyze the correlation between them by analysis of variance and Chi-square test.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 250
• Est. completion date: May 19, 2025
• Est. primary completion date: May 19, 2025
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years to 100 Years

Eligibility

Inclusion Criteria:

• Patients diagnosed with primary lung cancer.
• Age greater than 18 years and less than 100 years.
• After explanation, they agree to join this study and voluntarily sign the subject consent form, and can understand the content of the questionnaire.

Exclusion Criteria:

• Pregnant women.
• Severe mental illness that affects the response to the questionnaire.
• Has been treated (e.g., surgery, chemotherapy, targeted therapy, immunotherapy, radiation therapy, etc.).
• Concomitant with other uncured primary malignancies.
• Patients with other serious primary diseases (such as: liver and kidney dysfunction, hematolymphatic system diseases, etc.).
• Severe respiratory diseases that are not lung cancer (e.g. primary emphysema, interstitial fibrosis, etc.) .

Related Conditions & MeSH terms

• Body Constitution
• Medicine, Chinese Traditional
• Risk Factors
• Syndrome

Intervention

Diagnostic Test:
• Constitution in Chinese Medicine Questionnaire
Using questionnaire to collect data from new lung cancer patients.

Locations

Country	Name	City	State
Taiwan	China Medical University Hospital	Taichung City

Sponsors (1)

Lead Sponsor	Collaborator
China Medical University Hospital

Country where clinical trial is conducted

Taiwan, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	TCM body constitution	Ask about the subjects' signs according to the Constitution in Chinese Medicine Questionnaire (CCMQ)	20-30 minuts
Primary	TCM pattern types	Ask about the subjects' symptoms according to the pattern identification table	20-30 minuts
Secondary	demographic data	sex, age, BMI, smoking history	1 day
Secondary	disease-related clinical data	tumor stage, pathological type, gene mutation, tumor markers, other comorbidities	1 day