An Apriori Algorithm-Based Association Analysis of Analgesic Drugs in Chinese Medicine Prescriptions Recorded From Patients With Rheumatoid Arthritis Pain - Lai, Wei-dong; Li, Dian-ming; Yu, Jie; Huang, Lin; Zheng, Ming-zhi; Jiang, Yue-peng; Wang, Song; Wen, Jun-jun; Chen, Si-jia; Wen, Cheng-ping; Jin, Yan (Frontiers in Pain Research, 2022)
Chronic pain, a common symptom of people with rheumatoid arthritis, usually behaves as persistent polyarthralgia pain and causes serious damage to patients' physical and mental health. Opioid analgesics can lead to a series of side effects like drug tolerance and addiction. Thus, seeking an alternative therapy and screening out the corresponding analgesic drugs is the key to solving the current dilemma. Traditional Chinese Medicine (TCM) therapy has been recognized internationally for its unique guiding theory and definite curative effect. In this study, we used the Apriori Algorithm to screen out potential analgesics from 311 cases that were treated with compounded medication prescription and collected from “Second Affiliated Hospital of Zhejiang Chinese Medical University” in Hangzhou, China. Data on 18 kinds of clinical symptoms and 16 kinds of Chinese herbs were extracted based on this data mining. We also found 17 association rules and screened out four potential analgesic drugs—“Jinyinhua,” “Wugong,” “Yiyiren,” and “Qingfengteng,” which were promised to help in the clinical treatment. Besides, combined with System Cluster Analysis, we provided several different herbal combinations for clinical references.