基于真实世界数据分析中医药非介入治疗肺恶性肿瘤的辨治规律. - 卢思玮; 程淼 (Chinese Journal of Cancer Biotherapy, 2024)
Objective: To analyze the discriminative patterns of traditional Chinese medicine (TCM) in the non-interventional treatment of lung malignancies from a real-world perspective using data mining methods based on a clinical medical record information system. Methods: The medical history, symptoms at diagnosis, and medication information of patients with malignant lung cancer diagnosed in Dongzhimen Hospital of Beijing University of Chinese Medicine from January 1, 2015 to December 31, 2021 were collected from the medical record system, and a database was established after excluding the cases using interventional therapy. Microsoft Office Excel 2019 software was used to conduct descriptive statistics on the frequency, four basic properties and five tastes, meridian tropism, and efficacy of frequently used drugs. Microsoft Office Excel 2019 software was also used to data-mine the medical history and symptoms. Apriori algorithm in SPSS Modeler 18.0 software was applied to perform association rule analysis on the core data of high-frequency drugs and symptom information obtained from statistics, and an association network graph was constructed using web nodes. Cluster analysis was conducted using SPSS Statistics 23.0. Results: A total of 119 patients with malignant lung tumors who did not undergo interventional treatment were included. The common TCM symptoms included cough, white phlegm, wheezing, poor appetite, poor sleep, sticky phlegm, constipation, fatigue, chest tightness, and shortness of breath; Warm is the most common type among the four properties of the medicine; sweetness is the most common type in the five flavors of the medicine; and the highest frequency of meridian tropism is lung meridian. The association rule results showed that the combinations with the highest support for binomial association were Pinellia ternata → Chaihu, Pinellia ternata → Gualou, and Almond → Ephedra. The combinations with the highest support for trinomial association were Pinellia ternata → (Poria cocos, Bupleurum chinense), Almonds → (Ephedra, Pinellia ternate), Pinellia ternata → (Almonds, Radix Bupleuri), and Pinellia ternata → (Gualou, Fritillaria). The clustering results revealed three clusters, namely phlegm heat obstructing lung syndrome, lung yin deficiency syndrome, and lung qi deficiency syndrome in succession. Conclusion: The discriminative patterns of TCM in the non-interventional treatment of malignant lung tumors were lung yin deficiency syndrome, phlegm heat obstructing lung syndrome and lung qi deficiency syndrome in the syndrome clusters. The treatment is mainly based on harmonizing Shaoyang, moving qi to relieve cough and asthma, and clearing deficiency heat and resolving phlegm-rheum. The commonly used drugs include Pinellia ternata, Glycyrrhiza, Scutellaria, Poria cocos, and Radix Bupleuri.