Hsing-Yu Chen1, Yi-Hsuan Lin2, Jen-Wu Huang3, Yu-Chun Chen4. 1. Division of Chinese Internal Medicine, Center for Traditional Chinese Medicine, Chang Gung Memorial Hospital, Taoyuan, Taiwan; Graduate Institute of Clinical Medical Sciences, Chang Gung University, Taoyuan, Taiwan; School of Traditional Chinese Medicine, College of Medicine, Chang Gung University, Taoyuan, Taiwan. 2. Division of Chinese Internal Medicine, Center for Traditional Chinese Medicine, Chang Gung Memorial Hospital, Taoyuan, Taiwan; Graduate Institute of Clinical Medical Sciences, Chang Gung University, Taoyuan, Taiwan; School of Traditional Chinese Medicine, College of Medicine, Chang Gung University, Taoyuan, Taiwan; Department of Cosmetic Science, Chang Gung University of Science and Technology, Taoyuan, Taiwan. 3. Department of Surgery, National Yang-Ming University Hospital, I-Lan, Taiwan. 4. Department of Medical Research and Education, National Yang-Ming University Hospital, I-Lan, Taiwan; Faculty of Medicine, School of Medicine, National Yang-Ming University, Taipei, Taiwan; Institute of Hospital and Health Care Administration, School of Medicine, National Yang-Ming University, Taipei, Taiwan. Electronic address: yuchn.chen@googlemail.com.
Abstract
ETHNO-PHARMACOLOGICAL RELEVANCE: Chinese herbal medicine (CHM) is commonly used to treat skin diseases, but CHM prescription patterns are difficult to understand due to their complexity and inter-connections. This study aimed to demonstrate CHM core treatments and network for treatment of allergic skin diseases by analyzing a nationwide prescription database. MATERIALS AND METHODS: All CHM prescriptions made for atopic dermatitis (with age limitation ≤ 12 years) and urticaria for the entire year of 2011 were included. Association rule mining (ARM) combined with social network analysis (SNA) were used to analyze CHM prescriptions and explore the CHM prescription pattern and network. RESULTS: A total of 27,350 and 97,188 prescriptions for atopic dermatitis and urticaria, respectively, were analyzed. Xiao-Feng-San (XFS) was the most commonly used CHM (32% of prescriptions for atopic dermatitis and 47.4% for urticaria) and was the core treatment for both diseases. Moreover, 42 and 82 important CHM-CHM combinations were identified to establish the CHM network, and XFS with Dictamnus dasycarpus Turcz was the most prevalent (6.4% for atopic dermatitis and 9.1% for urticaria). Traditional Chinese Medicine heat syndrome was most prevalent cause. Extensive anti-inflammation, anti-allergy, anti-oxidation, and anti-bacterial effects were also found among the CHMs. CONCLUSIONS: Network analysis on CHM prescriptions provides graphic and comprehensive illustrations regarding CHM treatment for atopic dermatitis and urticaria. The CHM network analysis of prescriptions is essential to realize the CHM treatments and to select suitable candidates for clinical use or further studies.
ETHNO-PHARMACOLOGICAL RELEVANCE: Chinese herbal medicine (CHM) is commonly used to treat skin diseases, but CHM prescription patterns are difficult to understand due to their complexity and inter-connections. This study aimed to demonstrate CHM core treatments and network for treatment of allergic skin diseases by analyzing a nationwide prescription database. MATERIALS AND METHODS: All CHM prescriptions made for atopic dermatitis (with age limitation ≤ 12 years) and urticaria for the entire year of 2011 were included. Association rule mining (ARM) combined with social network analysis (SNA) were used to analyze CHM prescriptions and explore the CHM prescription pattern and network. RESULTS: A total of 27,350 and 97,188 prescriptions for atopic dermatitis and urticaria, respectively, were analyzed. Xiao-Feng-San (XFS) was the most commonly used CHM (32% of prescriptions for atopic dermatitis and 47.4% for urticaria) and was the core treatment for both diseases. Moreover, 42 and 82 important CHM-CHM combinations were identified to establish the CHM network, and XFS with Dictamnus dasycarpus Turcz was the most prevalent (6.4% for atopic dermatitis and 9.1% for urticaria). Traditional Chinese Medicine heat syndrome was most prevalent cause. Extensive anti-inflammation, anti-allergy, anti-oxidation, and anti-bacterial effects were also found among the CHMs. CONCLUSIONS: Network analysis on CHM prescriptions provides graphic and comprehensive illustrations regarding CHM treatment for atopic dermatitis and urticaria. The CHM network analysis of prescriptions is essential to realize the CHM treatments and to select suitable candidates for clinical use or further studies.
Keywords:
Association rule mining; Atopic dermatitis; Chinese herbal medicine; Social network analysis; The national health insurance research database; Urticaria