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河南中医药大学,郑州 450046
东红阳,在读硕士,从事中药学研究,E-mail:donghongyang1998@163.com
苗明三,博士后,教授,从事中药学研究,Tel:0371-65962546,E-mail:miaomingsan@163.com
纸质出版日期:2023-10-20,
网络出版日期:2023-08-04,
收稿日期:2023-03-21,
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东红阳,彭孟凡,安一珂等.基于数据挖掘的近十年中医治疗食管癌用药宏观规律[J].中国实验方剂学杂志,2023,29(20):160-168.
DONG Hongyang,PENG Mengfan,AN Yike,et al.Macroscopic Clinical Medication Pattern of Traditional Chinese Medicine for Esophageal Cancer in Recent Ten Years Based on Data Mining[J].Chinese Journal of Experimental Traditional Medical Formulae,2023,29(20):160-168.
东红阳,彭孟凡,安一珂等.基于数据挖掘的近十年中医治疗食管癌用药宏观规律[J].中国实验方剂学杂志,2023,29(20):160-168. DOI: 10.13422/j.cnki.syfjx.20231011.
DONG Hongyang,PENG Mengfan,AN Yike,et al.Macroscopic Clinical Medication Pattern of Traditional Chinese Medicine for Esophageal Cancer in Recent Ten Years Based on Data Mining[J].Chinese Journal of Experimental Traditional Medical Formulae,2023,29(20):160-168. DOI: 10.13422/j.cnki.syfjx.20231011.
目的
2
探究中医药治疗食管癌(EC)的宏观用药规律,为临床应用中医药治疗食管癌提供用药参考。
方法
2
对中国知网(CNKI)、万方数据库(WanFang)、维普数据库(VIP)三大中文数据库中有关中医药治疗食管癌的文献进行检索,在Excel中录入文献中方药的信息,建立食管癌处方数据库,对其中的数据进行标准化处理,并对其进行归纳总结,对处方中的用药进行频次统计、关联规则和聚类分析。根据中医对食管癌的证型分类,指出各证型对应的临床指征,将高频药物和药对组合与证型对应分析。
结果
2
共筛选得到136首处方,包含240味中药,累计出现频数1 853次,使用频数排名前5位的中药依次为甘草、茯苓、白术、黄芪、半夏;中药类别以补虚药、利水渗湿药、化痰止咳平喘药为主;性味归经的统计分析结果表明,以苦、甘味,温、寒、平性药,归脾、肺、胃经药物居多。关联规则分析得出9个潜在组合药对,高频药物聚类分析得到4类组合。中医对食管癌的4种证型分类对应相应的临床指征及治疗药物和药对。
结论
2
补虚扶正、降逆化痰、活血化瘀是中医治疗食管癌的基本法则,辅以清热散结的同时,注重调畅气机;高频药物及关联分析得到的药对组合为食管癌不同证型治疗提供参考,对临床用药具有一定的参考价值。
Objective
2
To explore the macroscopic medication pattern of traditional Chinese medicine (TCM) in treating esophageal cancer (EC) and provide medication references for the clinical application of TCM in EC treatment.
Method
2
Relevant literature on TCM treatment of EC was retrieved from three major Chinese databases: China National Knowledge Infrastructure (CNKI), Wanfang Data, and VIP. Information about Chinese herbal medicines was entered into Excel to establish a prescription database for EC. The data were standardized, summarized, and subjected to frequency analysis, association rules, and cluster analysis of medication in the prescriptions. Based on the TCM classification of EC syndromes, clinical indications corresponding to each syndrome were identified, and high-frequency drugs and drug pairs were analyzed correspondingly with syndromes.
Result
2
A total of 136 prescriptions containing 240 Chinese herbal medicines were screened, with a cumulative frequency of 1 853 times. The top 5 frequently used Chinese herbal medicines were Glycyrrhizae Radix et Rhizoma, Poria, Atractylodis Macrocephalae Rhizoma, Astragali Radix, and Pinelliae Rhizoma. In terms of functions, the Chinese herbal medicines were mainly deficiency-tonifying, urination-promoting and dampness-draining, deficiency-tonifying, deficiency-tonifying, and phlegm-resolving and cough and dyspnea-relieving ones. The statistical analysis of flavor, property, and meridian tropism showed that Chinese herbal medicines were mainly bitter and sweet, warm, cold, and neutral, and acted on the spleen, lung, and stomach meridians. Association rule analysis yielded nine potential drug combinations, and cluster analysis of high-frequency drugs resulted in four combination categories. The four TCM syndromes for EC corresponded to respective clinical indications, treatment drugs, and drug pairs.
Conclusion
2
Tonifying deficiency, reinforcing healthy Qi, descending adverse Qi, resolving phlegm, activating blood, and resolving stasis are the basic principles of TCM treatment for EC, which are supplemented by clearing heat and dissipating mass while focusing on regulating and smoothing the qi movement. The drug combinations obtained from high-frequency drug and association rule analysis provide references for different TCM syndrome treatments of EC, offering valuable insights for clinical medication.
食管癌中医临床用药规律高频药物聚类分析临床证型
esophageal cancertraditional Chinese medicine clinicalmedication rulehigh-frequency drugscluster analysisclinical syndrome
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