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赵磊,唐蔚,宋程,孔贤.基于数据挖掘的蒋益兰教授治疗肝癌的方药规律研究[J].湖南中医药大学学报,2022,42(3):436-440[点击复制] |
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| 基于数据挖掘的蒋益兰教授治疗肝癌的方药规律研究 |
| 赵磊,唐蔚,宋程,孔贤 |
| (湖南中医药大学研究生院, 湖南 长沙 410208;湖南省中医药研究院附属医院, 湖南 长沙 410006;湖南省肿瘤医院, 湖南 长沙 410013) |
| 摘要: |
| 目的 探讨国家级名医蒋益兰治疗肝癌的用药规律，指导临床实践和新药开发。方法 通过对临床病例的前瞻性研究和设计，采用结构化病例模块“中医传承计算平台V3.0”，采集2018 年 2 月至 2019 年 3 月蒋益兰教授门诊的210例肝癌患者病历，305 次就诊记录，采用软件集成的数据挖掘方法，对数据库进行症状、证型、治法、方剂、中药药性分布及频次统计，挖掘组方规律。结果 肝癌患者常见肋痛、腹胀、口干等症状，其证型有肝瘀脾虚证、湿热毒结证、肝虚脾困证、肝肾阴虚证，常用治法为健脾益气、软坚散结、疏肝行气，常用方剂为肝复方、健脾消癌方等，常用中药有甘草、人参、白术、茯苓、柴胡等，药性以平、温、寒为主，药味以甘、苦、辛为主，主归脾、肝、肺经。治疗肝癌的核心处方为人参、白芍、柴胡、郁金、香附、白花蛇舌草、茯苓、白术、法半夏、石见穿、枳壳、甘草。结论 蒋益兰教授认为肝癌病性虚实夹杂，且多以虚为主，辨证须重视五脏，尤以肝脾为主，治疗多用健脾益气之品，擅用肝复方为基础方随症加减，体现其临证辨治“扶正祛邪，标本同治，兼顾脾胃”的学术思想。 |
| 关键词: 肝癌 辨证论治 蒋益兰 名医经验 中医传承计算平台 数据挖掘 |
| DOI：10.3969/j.issn.1674-070X.2022.03.016 |
| 投稿时间：2021-05-16 |
| 基金项目:长沙市科技局一般项目（kq1901068,kq1907124）。 |
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| Research on the prescription rules of professor Jiang Yilan in the treatment of liver cancer based on data mining |
| ZHAO Lei,TANG Wei,SONG Cheng,KONG Xian |
| (Graduate School of Hunan University of Chinese Medicine, Changsha, Hunan 410208, China;The Affiliated Hospital of Hunan Academy of Chinese Medicine, Changsha, Hunan 410006, China;Hunan Cancer Hospital, Changsha, Hunan 410013, China) |
| Abstract: |
| Objective To explore the medication rule of Jiang Yilan, a national famous doctor, in the treatment of liver cancer, to guide clinical practice and new drug development. Methods Through prospective research and design of clinical cases, the structured case module "TCM inheritance calculation platform V3.0" was used, the medical records and 305 medical records of 210 liver cancer patients from the outpatient department of professor Jiang Yilan from February 2018 to March 2019 were selected. The data mining method of software integration was used to analyze the distribution and frequency of symptoms, syndrome type, treatment, prescription and traditional Chinese medicine in the database, and to explore the rule of prescription. Results Liver cancer patients always had rib pain, abdominal distension, dry mouth and other symptoms. The syndrome types included liver stasis and spleen deficiency, damp-heat toxic syndrome, liver deficiency and spleen trapped syndrome, liver and kidney Yin deficiency syndrome. The commonly used treatment methods were invigorating the spleen and supplementing Qi, softening and strengthening the knot, soothing the liver and regulating Qi, and the commonly used prescriptions were liver compound, Jianpi Xiaoai Prescription, etc. Commonly used Chinese medicines included Gancao (Glycyrrhizae Radix Et Rhizoma), Renshen (Ginseng Radix Et Rhizoma), Baizhu (Atractylodis Macrocephalae Rhizoma), Fuling (Poria), Chaihu (Bupleuri Radix), etc. Medicinal properties were mainly flat, warm, cold, the taste was mainly sweet, bitter and spicy, mainly belonged to the spleen, liver and lung meridian. The core drugs to treat liver cancer were Renshen (Ginseng Radix Et Rhizoma), Baishao (Paeoniae Radix Alba), Chaihu (Bupleuri Radix), Yujin (Curcumae Radix), Xiangfu (Cyperi Rhizoma), Baihuasheshecao (Hedyotis Diffusa), Fuling (Poria), Baizhu (Atractylodis Macrocephalae Rhizoma), Fabanxia (Pinelliae Rhizoma Praeparatum), Shijianchuan (Salvia Chinensis), Zhiqiao (Aurantii Fructus), Gancao (Glycyrrhizae Radix Et Rhizoma). Conclusion Professor Jiang Yilan believes that liver cancer is characterized by deficiency and excess, and mostly excess, and the five viscera organs, especially the liver and spleen should be paid attention to in syndrome differentiation. Spleen enhancing and Qi enhancing drugs should be used in the treatment, and is good at using the liver compound as the basic prescription add or decrease along with disease, which embodies his academic thought of "strengthening the body and eliminating pathogenic factors, simultaneous treatment of principal and subordinate symptoms, giving consideration to the spleen and stomach" in syndrome differentiation and treatment. |
| Key words: liver cancer syndrome differentiation and treatment Jiang Yilan famous doctor's experience TCM inheritance calculation platform data mining |
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