基于数据挖掘探析陈焕朝教授治疗乳腺癌 用药经验.

Objective To analyze the experience of Professor Chen Huanchao, a famous TCM doctor in Hubei Province, in treating breast cancer by data mining technology. Methods The medical records of Professor Chen Huanchao’s treatment of breast cancer were collected, and the first prescription of each patient was recorded after screening and sorting. MS Excel 2019 was used to analyze drug frequency, efficacy frequency, and the meridian distribution, and SPSS Modeler 18.0 software was adopted for association rule analysis and network display of drugs. SPSS 27.0 was employed for clustering analysis of high-frequency drugs to summarize medication patterns. Results A total of 185 prescriptions involving 180 traditional Chinese medicines were included, and 29 high-frequency drugs were screened. The medicinal properties were mainly neutral, cold, and warm, and the medicinal flavors were mainly sweet, bitter, and pungent. The meridians were liver, lung, spleen, and kidney meridians. The medicinal effects primarily included tonifying deficiency, clearing heat, and promoting diuresis and dampness. The association rule analysis showed 20 groups of drug pairs, and the cluster analysis mainly revealed two categories. Conclusion Professor Chen Huanchao believes that breast cancer involves root deficiency and excessive symptoms and should be treated from the perspective of “deficiency, blood stasis, phlegm, and toxin.” Genuine-Qi should be strengthened, and Evil-Qi should be eliminated. The symptoms and root causes of this disease should be treated simultaneously while soothing the liver and qi, tonifying the spleen and kidney, promoting blood circulation, removing phlegm and preventing its accumulation, and clearing heat and detoxify. This work provides ideas for the treatment of breast cancer with traditional Chinese medicine. [ABSTRACT FROM AUTHOR]