Clinical Study on Treatment of Advanced Non-Small Cell Lung Cancer by Combination of Consolidating Root,Removing Toxin and Dispelling Blood Stasis Method and Chemotherapy
Objective To study the clinical study of the treatment of advanced non-small cell lung cancer with the combina-tion of consolidating root,removing toxin and dispelling blood stasis method and chemotherapy.Methods A total of 102 patients diagnosed as advanced non-small cell lung cancer were divided into two groups according to the random number table.Fifty-one patients in the control group were treated with chemotherapy,and the other 51 patients in the study group were treated with consolidating root,removing toxin and dispelling blood stasis method and chemotherapy.The clinical efficacy of the two groups was observed and compared.Results Compared with that of the control group,the objective remission rate of the study group was 96.08％(49/51),higher than that of the control group(74.51％,38/51),and the difference was statistically significant(P＜0.05).After treatment,the values of carcinoembryonic antigen(CEA),cancer antigen 125(CA125)and cytokeratin 19 fragment(CYFRA21-1)in the study group were lower than those in the control group,while the levels of CD3+,CD4+and CD8+in the study group were higher than those in the control group,and the level of CD8+was lower than that in the control group with statisti-cal significance(P＜0.05).The degree of gastrointestinal tract damage,liver function damage and blood cell toxicity in the study group was lower than that in the control group,and the difference was statistically significant(P＜0.05).Conclusion The pa-tients diagnosed as obsessive-compulsive disorder were treated with clomipramine and Wendan Decoction(温胆汤)in combina-tion,and the clinical effect was significant,which could effectively improve the clinical symptoms of patients with high safety and clinical application value.
advanced non-small cell lung cancerconsolidating root,removing toxin and dispelling blood stasis methodchemotherapyimmune function
万方数据
维普
