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.
Study Type
OBSERVATIONAL
Enrollment
250
Using questionnaire to collect data from new lung cancer patients.
China Medical University Hospital
Taichung, Taiwan
RECRUITINGTCM body constitution
Ask about the subjects' signs according to the Constitution in Chinese Medicine Questionnaire (CCMQ)
Time frame: 20-30 minuts
TCM pattern types
Ask about the subjects' symptoms according to the pattern identification table
Time frame: 20-30 minuts
demographic data
sex, age, BMI, smoking history
Time frame: 1 day
disease-related clinical data
tumor stage, pathological type, gene mutation, tumor markers, other comorbidities
Time frame: 1 day
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