大数据背景下的中医药临床研究——基于数据挖掘分析欧阳郴生名中医治疗肺癌的用药规律

When Big Data Comes Into TCM Clinic Research—Analysis of Professor Ouyang Chensheng’s Experience in Treating Lung Cancer Based on Data Mining

目的:本研究运用数据挖掘技术,总结欧阳郴生名中医治疗肺癌的用药规律,探讨数据挖掘技术在中医用药传承规律研究中的应用,为研究中医药治疗肺癌的方法提供新思路。方法:收集整理2009年11月~2019年7月深圳市中医院信息中心记录的欧阳郴生诊治的肺癌患者的门诊病案,建立处方用药数据库,分别运用Python和R语言对数据进行整理及关联分析,并采用Cytoscape 3.7.1软件对结果可视化,分析欧阳郴生名中医辨治肺癌用药经验规律及特点。结果:本文共分析处方2852首,中药45,519次。大数据分析欧阳郴生名中医近10年临证诊治肺癌的处方用药,我们发现其遣方用药以平为期,辨证以扶正祛邪为主,兼顾化痰祛瘀、滋阴润肺、健脾补肾为法。选方多以六君子、三子养亲汤合二陈汤、千金苇茎汤、血府逐瘀汤、小青龙汤、沙参麦门冬汤等加减。选药常用黄芪、党参、茯苓、白术、山萸肉等补益脾肾,配以化痰祛湿、活血养血之品,用药多寒温并用、宣肺祛痰。结论:通过数据挖掘整理欧阳郴生诊治原发性肺癌的临证用药,谨守病机,重视辨证论治,配以调补脾肾之法,扶正与祛邪并施是欧阳郴生教授治疗肺癌的基本治法。

Objective: To summarize the academic experience of Professor Ouyang Chensheng in the pat-tern-differentiation based prescriptions for treating malignant lung cancer through the data mining technology;to explore the application of data mining technology in the traditional Chinese medicine (TCM) inheritance study, and to provide new insights to evaluate the adjunctive effect of TCM for patients with malignant cancers. Methods: We collected clinical records of out-patients in Shenzhen Hospital of TCM, who were diagnosed with malignant lung cancers, between December 2009 and July 2019. Chinese medicines in the prescriptions and the corresponding differentiated-patterns were extracted from the records and entered into the database, and further analyzed by Python and R respectively. The results were visualized by Cytoscape 3.7.1. The rules of TCM prescription and Chinese medicines commonly used for malignant lung cancers were summarized. Results: In the study, 2852 prescriptions were extracted consisting of 45,519 Chinese medicines. Through apriori algorithm based correlation analysis and frequency analysis, we found that Professor Ouyang Chensheng followed TCM principles of maintaining Zheng Qi, tonifying the spleen and kidney, resolving phlegm and removing blood stasis, and nourishing Yin and moistening lung in treating lung cancer. Liu Jun Zi decoction, Sanziyangqin, Erchen decoction, Qianjinweijing decoction, Xuefuzhuyu decoction, Xiaoqinglong decoction, and Shashenmaidong decoction were the commonest prescriptions in his treatments. In those prescriptions, Astragalus, Radix codonopsis, Poria cocos, Rhizoma atractylodes and Cornus officinalis were often added to tonify the spleen and kidney, as well as promote lung expectoration and nourish blood and Qi. Conclusion: Through data analysis, we find out Professor Ouyang Chensheng treated primary lung cancer on the principles of syndrome differentiation, tonifying Zheng Qi and removing pathogenic factors. These are important for treating malignant lung cancer by traditional Chinese Medicine. The data mining technology could be a useful tool to summarize the clinical experience of famous TCM practitioners.