Analysis of prescription regularity of traditional Chinese medicine for colorectal cancer based on data mining / 中国中药杂志

The tumor prescriptions contained in Dictionary of Tumor Formulas, Compendium of Good Tumor Formulas, Chinese Pharmacopoeia, Ministry of Health Drug Standards for Chinese Medicine Formulas and National Compilation of Standards for Proprietary Chinese Medicines were selected and organized to construct a database for tumor prescriptions, and the data mining techniques were applied to investigate the prescription regularity of colorectal cancer prescriptions. The formula data were extracted after screening in strict accordance with the inclusion and exclusion criteria, and were then analyzed with Microsoft Excel 2010 for frequency statistics, Apriori block provided by SPSS Clementine 12.0 software for correlation rule analysis, and arules and arulesViz packages in R 4.0.2 software for correlation rule visualization. In addition, SPSS 18.0 software was used for cluster analysis and factor analysis, in which cluster analysis was performed by Ochiai algorithm with bicategorical variables in systematic clustering method and factor analysis was performed mainly with principal component analysis. A total of 285 prescriptions were included in the statistical analysis, and the frequency statistics showed that 43 herbs had been used more than 16 times. The association rules analysis showed that 26 high-frequency me-dicine pair rules were obtained, and the association rules for those dispelling evil spirits, strengthening the body, resolving stasis, dispelling dampness, etc. were visualized. In the cluster analysis, we generated a dendrogram from which 7 groups of traditional Chinese medicines with homogeneity were extracted. 10 common factors were obtained in the factor analysis. The types of herbal medicines involved in the colorectal cancer prescription included anti-cancer antidotes, strengthening and tonifying medicines, blood-regulating medicines, and expectorant medicines, corresponding to the treatment for eliminating evil spirits, strengthening, resolving stasis, and expectorating dampness. The prescriptions for anti-cancer detoxification were normally based on the pairs composed of Scutellaria barbata-Hedyotis diffusa and Sophora flavescens, Sargentodoxa cuneata, S. barbata, often combined with stasis relieving drug and dampness eliminating drug, reflecting the characteristics of treatment for both toxicity and stasis, dampness and toxicity simultaneously. The prescriptions for strengthening the righteousness and tonifying the deficiency were composed of Astragalus membranaceus and Atractylodes macrocephala mainly, exerting the effect of benefiting Qi, strengthening the spleen and drying dampness, tonifying kidney and essence, tonifying blood and invigorating blood. Meanwhile, anti-cancer detoxification medicines shall be reduced as much as possible. The compatibility of the medicines for the intestinal tract reflected the principle of using the right medicine for the right condition and eliminating evil spirits or strengthening the body, as appropriate.

Famous veteran traditional Chinese medicine doctors' medication rules in treating spermatorrhea / 中国中药杂志

To explore famous veteran traditional Chinese medicine( TCM) doctors' medication rules in treating spermatorrhea based on the medical cases about spermatorrhea collected from Hundred TCM Clinical Doctors of Hundred Years in China and Proven Cases and National Medical Master Test Case. Researchers extracted such data as medicinal and therapies from these cases according to the inclusion and exclusion criteria. Then,Excle 2010,SPSS Clementine 12. 0 and SPSS 22. 0 were adopted respectively for frequency analysis,association rules analysis,cluster analysis and factor analysis. Cluster analysis was carried out by Ochiai algorithm of binary variable data,one of the systematic clustering methods. And principal component analysis was used for factor analysis. Finally,27 medical cases and 41 prescriptions were included in total. The frequency analysis showed that the most common therapy was the astringent therapy( n = 28),which was followed by the tonifying method,tranquilizing method,heat-clearing method,damp-dispelling method and Qiregulating method. The top three kinds of high-frequency traditional Chinese medicines were Poria,Ostreae Concha and Dioscoreae Rhizoma. The association rules analysis found out 11 association rules of medicine pairs,23 association rules of medicine combinations of the three kinds of herbs and 6 association rules of medicine combinations of five kinds of herbs. Among them,the representatives were Rubi Fructus→Fossilia Ossis Mastodi,Rehmanniae Radix Praeparata + Corni Fructus→Dioscoreae Rhizoma,and Pinelliae Rhizoma→Citri Reticulatae Pericarpium,which showed the therapeutic characteristics of astringing,tonifying the kidney and replenishing essence,fortifying the spleen and dispelling dampness. Moreover,7 medicine groups with relevance were extracted from the tree map generated by cluster analysis,including " Phellodendri Chinensis Cortex and Anemarrhenae Rhizoma" and " Angelicae Sinensis Radix,Rehmanniae Radix,Bupleuri Radix and Glycyrrhizae Radix et Rhizoma",which demonstrated the effects of nourishing Yin and purging fire,tonifying and soothing the liver. Besides,totally 12 common factors were obtained according to factor analysis,including 14 drug combinations,like " Amomi Fructus,Anemarrhenae Rhizoma and Phellodendri Chinensis Cortex" and " Nelumbinis Stamen,Moutan Cortex,Poria and Scrophulariae Radix",which indicated the compatibility characteristics of tonifying the spleen and purging fire,dispelling dampness and clearing heat. In conclusion,data mining techniques( including frequency analysis,association rules analysis,cluster analysis and factor analysis) were used to comprehensively analyze the famous veteran TCM doctors' medication rules in treating spermatorrhea,which was helpful for guiding the clinical practice of treating spermatorrhea in TCM.

Research rules of famous veteran traditional Chinese medicine practitioners in treating infertility / 中国中药杂志

To explore the medication rules of famous veteran traditional Chinese medicine practitioners in treating infertility based on medical cases of infertility collected from book series of Hundred Traditional Chinese Medicine Clinicians of Hundred Years in China and Prescription Proven by Traditional Chinese Medicine Masters. Researchers extracted the information of prescriptions from these cases according to the inclusion and exclusion criteria. Then, Excel 2010, SPSS Clementine(ver.12.0) and SPSS(ver. 22.0) were adopted respectively for frequency analysis, association rules analysis, cluster analysis and factor analysis. Cluster analysis was carried out by Ochiai algorithm of binary variable data, which was a systematic clustering method. And principal component analysis was used for factor analysis. Besides, KMO test and Bartlett spherical test were used for factor adaptation test. Finally, 151 medical cases and 396 prescriptions were included in total. A total of 60 kinds of frequently used herbs were identified according to the results of frequency analysis for medication, they were mainly used for activating blood and resolving stasis, tonifying and clearing heat respectively. The association rules analysis found out 25 drug pair association rules and 14 3-drug combination association rules. A total of 15 medicine groups were extracted by cluster analysis. KMO test and Bartlett spherical test indicated that the method was suitable for factor analysis, and 21 common factors were respectively extracted by factor analysis. Association rules indicated the characteristics of the therapeutic methods, like tonifying Qi and replenishing blood. The famous veteran traditional Chinese medicine practitioners utilized modified Siwu Decoction for tonifying blood and preferred Atractylodis Macrocephalae Rhizoma(Baizhu) for tonifying Qi. The results of both cluster analysis and factor analysis demonstrated the characteristics of the therapies for tonifying kidney, activating blood, tonifying spleen and dispelling dampness. In addition, factor analysis could reflect the therapies for nourishing Yin, tonifying kidney, warming the meridian, dissipating cold, nourishing blood and dispelling blood stasis. These results of analysis comprehensively showed out the medication characteristics of famous veteran traditional Chinese medicine practitioners of strictly following the pathogenesis, making good use of classical formulas and providing proper compatibility. In conclusion, data mining techniques(including frequency analysis, association rules analysis, cluster analysis and factor analysis) were used to comprehensively analyze the medication rules of famous veteran traditional Chinese medicine practitioners in treating infertility, which is helpful for guiding the clinical practice of treating infertility with traditional Chinese medicine.