| Objective1.Retrospective statistics were conducted on the case data of prostate cancer patients in the Urology Department of Guang'anmen Hospital of Chinese Academic of Traditional Chinese Medicine Science from January 1,2015 to March 31,2020,to summarize the TCM syndrome distribution of clinical prostate cancer patients and observe the safety of TCM for prostate cancer treatment.2.On January 1,2011 to December 31,2019,Guang'anmen Hospital of Chinese Academic of Traditional Chinese Medicine Science gate prescription of traditional Chinese medicine professor Jianxin Lu outpatient cases of data in data mining,summarizes professor Jianxin Lu drugs' feature for the treatment of prostate cancer,mining high frequency using a combination of drugs and try to categorize all prescription,summarize its quality.MethodsStudy 1 To study the syndrome analysis of 231 patients with prostate cancer1.General information Research methods:Microsoft Excel 2019 was used to include the case information,and a basic database was established,including the patient's name,file number,hospital admission time,diagnosis of Chinese and western medicine,etchings,Gleason score and auxiliary examination at diagnosis.2.Text mining method:SPSS Modeler 18 was used to conduct text mining for all 231 cases of TCM diagnosis and syndrome.SPSS Modeler18.0 was used to conduct text mining and then cluster analysis on TCM syndromes of 231 cases,so as to explore the common rules among cases diagnosed as standard clustering.At the same time,the syndrome elements of all standard syndromes were statistically analyzed to explore the differences between clustering groups and the common rules within the groups.3.Data analysis:using SPSS Statistics for all 22 cases of complete blood for statistical analysis and biochemical examination project,curative effect analysis objects including indicators and TCM syndrome score and security index.Baseline data analysis conducted by using descriptive Statistics,data comparison before and after conducted by adopting independent samples nonparametric tests.4.Data sorting methods:Data of 231 cases were entered into Excel data sheet to establish a case data database.Baseline conditions were established at the time of diagnosis,including Gleason score of pathological diagnosis,prostate specific antigen level at the first admission,and TCM symptoms at the first admission.Study 2 Summary of prescription and formula of Professor Jianxin Lu in the treatment of prostate cancer1.Establishment of database:The original data were obtained from the prescription system of Guang'anmen Hospital of Chinese Academic of Traditional Chinese Medicine Science.The prescription data of Professor Jianxin Lu from January 1,2011 to December 31,2019 were retrieved based on the patient's personal information,diagnosis of Traditional Chinese medicine,diagnosis of Western medicine and establishment of inquiry of prescription drugs.The original data were entered into Excel,the original database was established,and 2443 Chinese medicine prescriptions were sorted out through Python 3.7 scripting language with prescription number as the key value.A prescription containing more than 4 flavors is used for internal administration.After preliminary data cleansing,2413 valid prescription data were used for Statistics and data mining using SPSS Statistics and SPSS Modeler.Through text mining of 2,413 prescription drugs,103 terms of traditional Chinese medicine were obtained,and 89 names of traditional Chinese medicine drugs were finally obtained after correction of multiple names of one drug caused by processing,genuine medicinal materials or common names in the Pharmacopoeia of The People's Republic of China.2.Drawing prescription data matrix diagram:Using 89 traditional Chinese medicine names as matrix head,using Python 3.7 to extract and escape 2413 prescription information.Draws an 89x2413 L-shaped matrix with only "0" or "1" as the value.3.Descriptive Statistic method:For the valid prescription database,SPSS Statistic was used for descriptive analysis.4.Correlation analysis of drug flavors:For the matrix table,SPSS Modeler was used for data mining,and Apriori algorithm was used to find frequent item sets for all the escaped prescriptions.5.Prescription clustering analysis:Try to find the model of prescription classification.ResultsStudy 1 To study the syndrome analysis of 231 patients with prostate cancer1.Baseline of cases:Descriptive statistics were conducted on the ages of 231 Prostate cancer patients,whose ages were 71.16±9.872 years.Gleason Group grade 1 to 5 accounted for 23.1%,5.8%,19.2%,21.2%and 30.8%,respectively,in biopsy pathological reports of all Prostate cancer patients observed in the study.According to risk stratification,the high risk accounted for 76.9 of the observed cases.3.Prostate specific antigen level at first diagnosis:Prostate specific antigen level at first diagnosis(n=231)was 68.756ng/mL on average and 55.830ng/mL on median.4.Overall prostate specific antigen level:All hospitalization records(n=891)of 231 patients with prostate cancer were analyzed,and the overall prostate specific antigen level was 78.17ng/mL.5.Comparison of safety indicators before and after:After independent sample non-parametric test,there was no difference in each indicator before and after.6.The distribution of TCM syndromes and syndrome elements of prostate cancer:syndrome types of "Ben deficiency" and "Biao excessive" account for almost the same proportion(53.7%vs 46.3%).Meanwhile,the percentage of those who has "Ben deficiency" and "Biao excessive" at the same time accounts for 69%.The results of spleen and kidney diseases were 33.29%and 20.57%respectively.32%of tongue color information suggested Yang deficiency,33%suggested Yin deficiency or blood stasis;42%of tongue material information suggested Yang deficiency;tongue coating information showed Yin deficiency and Yang deficiency were almost the same proportion;48%of tongue color information indicated that the functions of viscera were not free of gasification.Chordal vein,synovial vein and veinlets account for 34.73%,26.33%and 18.77%,respectively,and 79.83%of the total pulse information.Study 2 Summary of prescription and formula of Professor Jianxin Lu in the treatment of prostate cancer1.Basic descriptive characteristics of prescriptions:the average number of prescriptions is 11;A total of 89 traditional Chinese medicines were used.Use frequency more than 10%of the drugs were dried tangerine or orange peel(90.05%),Fried atractylodes(83.46%),codonopsis pilosula(77.83%),poria cocos(71.86%),vinegar rhizoma zedoariae(58.52%),barbed skullcap herb(48.98%),mountain(39.99%),arrowhead,fresh mushroom raw semen coicis(37.5%),radix bupleuri,astragalus(35.72%),honey(32.86%),bran Fried divine comedy(32.45%),focal hawthorn(31.74%),and dandelion(28.72%),angelica(26.73%),radix paeoniae alba(24.08%),caulis dendrobii(22.21%),Radix pseudostellariae(18.32%),licorice(17.70%),cassia twigs(16.87%),stir-fried Raphani seed(16.87%),stir-fried Fructus Raphani(15.62%),stir-fried Atractylodes rhizome(14.50%),stir-fried almonds(14.30%),dates(12.06%),ginger(11.56%)and Shiwei(11.27%).2.Frequent combinations of high frequency drugs:all results were integrated,and it was found that "orange peel-poria cocos-sauteed rhizoma atractylosum-jujube","orange peel-poria cocos-ginger-vinegar zedoary curcuma-jujube" and "orange peel-poria cocos-ginger-raw semen coicis-jujube" were the most commonly used drug combinations.3.The clustering results of 2413 prescriptions showed that there were 4 groups of copolymerization,and cluster 1 was "Poria Cocos-Cidodes edodes-Vinegar Zedoary Curcumascutellaria-dried tangerine peel-radix Atractylodis-Codonopsis".Cluster 2 was "AngelicaHoney Astragalus-Bupleurum-raspberry-Sauteed atractylodes-Dried tangerine peel".Cluster 3 was "Fried Rhizoma atractylodes Rhizoma Codonopsis-Tangerine peel-Sinifera siniferaVinegar Zedoary Turmeric-Poria cocos".Cluster 4 was "jujube-ginger-poria cocos-raw semen coicis-radix codonopsis-sauteed rhizoma atractylodis-tangerine peel-sinifera sinifera-vinegar zedoary turmeric".Conclusion1.231 cases had 14 syndromes,mainly distributed as damp-heat syndrome(27%),qi deficiency and blood stasis(26%),spleen and kidney Yang deficiency(22%)and phlegm-blood stasis(12%).2.There was no statistical difference between the observation and comparison of the safety indexes of 231 cases before and after observation,indicating that reasonable and compliant TCM treatment would not bring burden to Prostate cancer patients.3.Professor Jianxin Lu takes strengthening the body and removing pathogenic factors as the clinical principle of Prostate cancer,takes strengthening the spleen and supplementing qi as the general method,and takes "Six Junzi Decoction" and "Buzhong Yiqi Decoction" as the basic prescription. |
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