Analysis on the principles of differentiation and prescription of traditional Chinese medicine in the treatment of cancerous fever
Journal Title: Traditional Medicine Research - Year 2017, Vol 2, Issue 1
Abstract
To investigate the principles of differentiation and prescription of traditional Chinese medicine (TCM) treatment for cancerous fever by logistic stepwise regression and literature investigation, the following databases were searched (from inception to June 30th 2016): CNKI, CSPD, CBM, PubMed, MEDLINE, EMBASE. According to the inclusion and exclusion criteria, literatures about TCM in the treatment of cancerous fever were screened. The frequency about cancerous fever of differential syndrome types, formulas and herbs were analyzed by logistic multiple regression analysis. The model about syndrome types and formula application of cancerous fever was established. The result showed formula prescriptions used most frequently were Qing-Hao-Bie-Jia decoction, Xiao-Chai-Hu decoction, Xue-Fu-Zhu-Yu decoction, Bai-Hu decoction, San-Ren decoction. The main syndrome types of cancerous fever were as follows: Toxic heat flourishing type, Yin deficiency type, Stagnation of damp-heat type, Qi-Yin deficiency type, Liver meridian depressed-heat type, Blood stasis type and Yang deficiency type. Based on regression equation of the syndrome types, the corresponding herbs of this seven syndrome types were Radix Bupleuri, Radix Paeoniae Alba and Scutellaria Baicalensis Georgi; Radix Bupleuri and Cortex Moutan; Radix Paeoniae Rubra and Radix Angelicae Sinensis; Rhizoma Pinelliae, Cortex Lycii Radicis and Radix Paeoniae Alba; Herba Artemisiae Annuae, Gypsum Fibrosum and Poria Cocos; Rhizoma Anemarrhenae, Scutellaria Baicalensis Georgi and Radix Codonopsis; Radix Bupleuri respectively. The results of Logistic regression analysis and frequency of herbs statistics can provide reference for differentiation and treatment of cancerous fever in clinical.
Authors and Affiliations
Xu Wei, Chai Ni, Cheng Yue-Lei, Yang Qiong, Zhu Hui-Rong
Keywords
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- EP ID EP45274
- DOI 10.12032/TMR201705036
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