基于数据挖掘方法分析周郁鸿治疗多发性骨髓瘤中药用药规律
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R273

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浙江省中医药科技计划预目(2024ZF011);浙江省自然科学基金资助项目(LGF22H080005)


Analysis of Medication Rules of Chinese Medicine Used by ZHOU Yuhong in the Treatment of Multiple Myeloma Based on Data Mining Methods
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    摘要:

    目的:基于数据挖掘方法分析国家级名中医周郁鸿教授治疗多发性骨髓瘤(MM) 的中药用药规 律。方法:选取2012年1月1日—2024年5月31日就诊于浙江省中医院血液内科周郁鸿教授门诊并符合纳入标 准及排除标准的MM患者,运用SPSS Modeler 18.0软件进行数据处理,进行药物频次分析;采用SPSS Modeler 18.0中的Apriori算法进行药物关联规则分析;采用SPSS statistics 聚类算法对核心药物进行聚类分析。将数 据挖掘分析结果交由周郁鸿教授审阅并对其进行访谈。结果:共纳入医案491个,处方1 823首,涉及中药 1 798味。药物频次分析结果示,累计总频次30 907次,居前10位的中药依次为茯苓、麦芽、陈皮、白术、太 子参、酸枣仁、党参、鳖甲、黄芪、柴胡。中药功效分类前10位依次为补虚药、理气药、利水渗湿药、安神 药、消食药、解表药、清热药、收涩药、化痰止咳平喘药、活血化瘀药。按药物归经频次从高到低进行排序, 依次为脾、肺、肝、肾、胃、心、胆、大肠、膀胱、小肠、三焦、心包。按药物四气频次从高到低依次排序, 依次为平、温、寒、凉、热。按药物五味频次从高到低依次排序,依次为甘、苦、辛、酸、淡、咸、涩。高频 药物关联规则分析结果获得:核心药物组合有陈皮-茯苓,茯苓-麦芽,鳖甲-太子参,陈皮-太子参,鳖甲-太 子参-茯苓等。将软坚散结药物提取出进行关联规则分析,核心药对有陈皮-甘草-鳖甲、麦芽-黄芪-浙贝母、 半夏-浙贝母;麦芽-茯苓-陈皮-玄参。高频药物系统聚类分析获得6个聚类结果。第1类:山药、枳实、升 麻、白术、柴胡、麦冬、当归、甘草、党参;第2类:太子参、鳖甲、酸枣仁、杜仲;第3类:麦芽、陈皮、 茯苓、半夏、山楂;第4类:黄芪、浙贝母;第5类:天麻、龙骨、甜叶菊、人参。第6类:红景天。结论: 周郁鸿教授治疗MM以补虚药为主,其次为理气药、利水药,药性平和,并辨证施以益气补肾、行气化痰、化 瘀通络诸药。

    Abstract:

    Abstract: Objective: Based on data mining methods, to analyze the Chinese medicine medication rules of Professor ZHOU Yuhong, a famous provincial Chinese medicine practitioner, in the treatment of multiple myeloma (MM). Methods: Selected the MM patients who visited Professor ZHOU Yuhong's outpatient clinic in the Hematology Department of Zhejiang Provincial Hospital of Chinese Medicine from January 1, 2012 to May 31, 2024 and met the inclusion and exclusion criteria. The SPSS Modeler 18.0 software was used for data processing and drug frequency analysis;the Apriori algorithm in SPSS Modeler 18.0 was used for drug association rule analysis;SPSS statistics clustering algorithm was used to perform cluster analysis on core drugs. The data mining analysis results were submitted to Professor ZHOU Yuhong for review and an interview was conducted. Results:A total of 491 medical cases and 1 823 prescriptions were included,involving 1 798 Chinese medicinals. The drug frequency analysis showed that the cumulative total frequency was 30 907 times, and the top 10 Chinese medicinals were Poria, Hordei Fructus Germinatus,Citri Reticulatae Pericarpium,Atractylodis Macrocephalae Rhizoma,Pseudostellariae Radix, Ziziphi Spinosae Semen,Codonopsis Radix,Trionycis Carapax,Astragali Radix,and Bupleuri Radix. The top 10 efficacy categories of Chinese medicinals are, in order, deficiency-supplementing drugs, qirectifying drugs,urination-promoting and dampness-percolating drugs,mind-calming drugs,digestionpromoting drugs, exterior-releasing drugs, heat-clearing drugs, astringent drugs, phlegm-dissolving and cough and panting-relieving drugs, and blood invigorating and stasis-dissolving drugs. According to the frequency of channel entry of drugs,they are ranked from high to low as follows:spleen,lung,liver, kidney, stomach, heart, gallbladder, large intestine, bladder, small intestine, sanjiao, and pericardium. According to the frequency of the four qi of medicine, they are ranked from high to low, namely,neutral,warm,cold,cool,and hot. According to the frequency of the five flavors of medicine, they are ranked from high to low as follows: sweet, bitter, acrid, sour, bland, salty, and astringent. The analysis results of high-frequency drug association rules show that the core drug combinations include Citri Reticulatae Pericarpium-Poria, Poria-Hordei Fructus Germinatus, Trionycis Carapax- Pseudostellariae Radix, Citri Reticulatae Pericarpium-Pseudostellariae Radix, and Trionycis Carapax- Pseudostellariae Radix-Poria. The association rules of hardness-softening and masses-dissipating drugs were extracted and analyzed, and the core medicinal combination include Citri Reticulatae Pericarpium- Glycyrrhizae Radix et Rhizoma- Trionycis Carapax,Hordei Fructus Germinatus- Astragali Radix- Fritillariae Thunbergii Bulbus, Pinelliae Rhizoma-Fritillariae Thunbergii Bulbus, and Hordei Fructus Germinatus- Poria-Citri Reticulatae Pericarpium- Scrophulariae Radix. High frequency drug system clustering analysis obtained six clustering results: Class 1: Dioscoreae Rhizoma, Aurantii Fructus Immaturus, Cimicifugae Rhizoma,Atractylodis Macrocephalae Rhizoma,Bupleuri Radix,Ophiopogonis Radix,Angelicae Sinensis Radix, Glycyrrhizae Radix et Rhizoma, Codonopsis Radix; Class 2: Pseudostellariae Radix, Trionycis Carapax, Ziziphi Spinosae Semen, and Eucommiae Cortex; Class 3: Hordei Fructus Germinatus, Citri Reticulatae Pericarpium, Poria, Pinelliae Rhizoma, and Crataegi Fructus; Class 4: Astragali Radix, and Fritillariae Thunbergii Bulbus; Class 5: Gastrodiae Rhizoma, Fossilia Ossis Mastodi, Sugar Stevia Leaf, and Ginseng Radix et Rhizoma; Class 6: Rhodiolae Crenulatae Radix et Rhizoma. Conclusion: Professor ZHOU Yuhong's treatment for MM mainly focuses on deficiency-supplementing medicinals, followed by qi-rectifying medicinals and urination-promoting medicinals. The medication is mild and nature, and various medicinals such as qi-boosting and kidney-supplementing, qi-moving and phlegm-dissolving, and stasis-dissolving and collateral-unblocking are applied based on syndrome differentiation.

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董南希,叶宝东,国庆,刘淑艳,指导:周郁鸿.基于数据挖掘方法分析周郁鸿治疗多发性骨髓瘤中药用药规律[J].新中医,2024,56(24):134-140

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