Analysis of medication rule of Traditional Chinese Medicine in treating depression based on data mining

Depression is a mental disorder characterized by persistent feelings of sadness, decreased interest or pleasure in activities and reduced energy. As a highly prevalent disorder, it seriously endangers the psychosocial functioning of patients. Many scholars have conducted clinical studies on the trea...

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Veröffentlicht in:Heliyon 2024-10, Vol.10 (20), p.e39245, Article e39245
Hauptverfasser: Yang, Jin, Wang, Shuai, Zhang, Zhen, Huang, Junjie, Chen, Weihai, Xu, Zhan
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Sprache:eng
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Zusammenfassung:Depression is a mental disorder characterized by persistent feelings of sadness, decreased interest or pleasure in activities and reduced energy. As a highly prevalent disorder, it seriously endangers the psychosocial functioning of patients. Many scholars have conducted clinical studies on the treatment of depression using different herbal remedies, but there are no studies that integrate these remedies to explore the general medication rule. This study aims to explore the medication pattern of Traditional Chinese Medicine (TCM) treatment for depression through data mining methods, so as to provide scientific theoretical basis and reference for clinical treatment and new prescription development. Based on the PRISMA principle, 121 articles involving 10810 patients with depression of TCM treatment were collected. We then performed frequency, association rule, and hierarchical clustering analysis of Chinese herbs using Microsoft Excel 2016, SPSS Modeler 18.0 and IBM SPSS Statistics 23. Among the 270 herbs collected, the three most frequently occurring herbs are Gancao, Chaihu, and Shaoyao. The categories of high-frequency herbs are mainly deficiency-tonifying, Qi-regulating and blood-activating and stasis-eliminating herbs. Through the Apriori algorithm, we mined 21 herbal groups of association rules, and among which the combination of Chaihu-Shaoyao-Gancao has the highest level of support. Furthermore, five novel clustering combinations were identified, predominantly derived from Xiaoyao-San, Chaihu-Shugan-San, Sini powder, Kaixin-San and Chaihu-Jia-Longgu-Muli Decoction. The current study not only concluded the frequent combinations but also developed five new drug cluster combinations for depression, which can provide evidence-based references for the future clinical treatment and is helpful to understand the potential pharmaceutical mechanism from the properties, tastes, meridian tropisms and categories. The clinical effectiveness of these combinations needs to be verified by future study. [Display omitted] •The main selection of articles highlighting the therapeutic efficacy of TCM for depression compared to western medicines.•Five core clustered herbal combinations derived from data mining were considered worthy of further study.•This data mining method similar to meta-analysis may help to more scientifically identify drug candidates based on TCM for depression.•This study provides an evidence-based basis for future clinical treatment research.
ISSN:2405-8440
2405-8440
DOI:10.1016/j.heliyon.2024.e39245