李苑, 钱琳, 杨义. 中药治疗乳腺癌用药规律研究—基于真实世界的数据挖掘. 2025. biomedRxiv.202506.00022
中药治疗乳腺癌用药规律研究—基于真实世界的数据挖掘
通讯作者: 杨义, thehanyang@163.com
DOI:10.12201/bmr.202506.00022
Analysis the Medication Regularity of TCM in the Treatment of Breast Cancer in the Real World Based on Data Mining Method
Corresponding author: yangyi, thehanyang@163.com
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							    摘要:目的:基于真实世界数据挖掘分析中药治疗乳腺癌用药规律,为中药治疗乳腺癌提供依据。方法:收集2017年1月至2021年12月成都中医药大学附属医院住院且使用中药治疗乳腺癌的患者临床诊疗信息。采用Python 3.10软件对收集的中药处方实现数据挖掘,建立数据库;运用SPSS进行描述性分析,并对高频药物系统聚类分析。结果:共收集3020诊次乳腺癌住院患者诊疗数据,中医主要证候诊断“肝郁气滞为主”排在第1位(占累计诊次61.1%),治疗使用240味中药,累计频次35462次,其中当归、茯苓、白术、柴胡等29中药每味累计使用频次均超过300次。药物四气以寒性(43.5%)、温性(30.0%)、平性(23.3%)药物为主;五味以甘味(46.1%) 、苦味(30.9%)、辛味(20.0%)为主。用药频次最多的为补虚药(32.8%),其次为清热药(16.0%)、化痰药(14.7%)。系统聚类分析共获得7组药物组合。结论:真实世界中药临床用药以补虚药为主,体现中医治疗肿瘤扶正培本的原则,药物四气五味遵循辨证施用、寒热并用。聚类组合药物治疗功效广泛,乳腺癌各治疗期临床证型均涉及,对乳腺癌患者中医用药规律分析能为临床合理用药提供参考。 Abstract: Objective: Based on data mining, the medication rules of traditional Chinese medicine (TCM) in the treatment of breast cancer in the real world were analyzed to provide a basis for the treatment of breast cancer with TCM. Methods: The diagnosis and treatment information of patients who were hospitalized in the Affiliated Hospital of Chengdu University of traditional Chinese medicine and treated with TCM for breast cancer from January 2017 to December 2021 was collected. Python 3.10 software was used to realize data mining of the collected Chinese medicine prescriptions. Each Chinese medicine was listed as a variable. The Chinese medicine was recorded as “1” and the unused record was “0”. Analyze the basic situation of patients, TCM syndromes, frequency of Chinese medicine use, four qi and five flavors of drugs, and drug efficacy, and cluster analysis of high-frequency drug systems to summarize the medication rules of real-world Chinese medicine in the treatment of breast cancer. Results: A total of 3020 clinical data of hospitalized patients with breast cancer treated with TCM were collected. The main syndrome diagnosis of traditional Chinese medicine liver depression and qi stagnation ranked first ( accounting for 61.1 % of the cumulative diagnosis ).A total of 240 kinds of TCM were involved, and the cumulative frequency of use was 35462. Among them, 29 kinds of TCM such as angelica, poria cocos, atractylodes macrocephala and bupleurum were used more than 300 times. The four properties of drugs were mainly cold ( 43.5 % ), warm ( 30.0 % ) and flat ( 23.3 % ). The main flavors were sweet ( 46.1 % ), bitter ( 30.9 % ) and pungent ( 20.0 % ). The most frequently used drugs were tonics ( 32.8 % ), followed by heat-clearing drugs ( 16.0 % ) and phlegm-resolving drugs ( 14.7 % ). A total of 7 drug combinations were obtained by systematic cluster analysis. Conclusion: In the real world, the clinical medication of traditional Chinese medicine is mainly tonic medicine, which reflects the principle of traditional Chinese medicine in the treatment of tumors. The four qi and five flavors of the drug follow the dialectical application and the combination of cold and heat. Cluster combination drugs have a wide range of therapeutic effects, and all clinical syndromes of breast cancer are involved. The analysis of TCM medication rules for breast cancer patients can provide reference for clinical rational drug use. Key words: Data mining; Medication Regularity; Breast cancer; Herbal Medicine; Cluster analysis提交时间:2025-06-10 版权声明:作者本人独立拥有该论文的版权,预印本系统仅拥有论文的永久保存权利。任何人未经允许不得重复使用。
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								序号 提交日期 编号 操作 1 2025-03-22 10.12201/bmr.202506.00022V1 下载 
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