摘要
目的:探讨中医药治疗肺癌核心处方的数据挖掘方法,对核心处方进行有效性评价。方法:收集300例非小细胞肺癌患者,利用遗传算法发现核心中药处方,通过建立C57BL/6近交系小鼠Lewis肺癌动物模型进行核心处方的有效性评价。结果:挖掘出核心有效处方4张(P<0.05),动物实验表明核心处方可抑制Lewis肺癌皮下移植瘤的瘤体生长,瘤重较对照组减轻(P<0.05),同时联合组对小鼠肿瘤负荷抑制最明显,瘤重最轻。结论:遗传算法是中医药治疗肺癌核心处方数据挖掘的有效方法,挖掘出的核心处方经初步验证有明确疗效。
Objective: To investigate the data mining method applicable for exploring the core prescription in treating lung cancer with traditional Chinese medicine(TCM) and test the curative effect of the core prescription. Methods: After collecting 300 cases of patients with non-small cell lung cancer, we discovered the core prescription through the genetic algorithm, and then we tested the curative effect of the core prescription by establishing the Lewis lung cancer animal model of C57 BL/6 inbred mice. Results: We discovered four core effective prescription(P<0.05). Animal experiments shown core prescriptions were proved to inhibit the growth of the subcutaneous transplantation tumor of Lewis lung cancer, tumor weight was lighter than that of the control group(P<0.05), at the same time, the combined group had the most obvious inhibition on tumor load in mice, and the tumor weight was the lightest. Conclusion: Genetic algorithm, a kind of the data mining method, has proved effective to discover the core prescription in treating lung cancer with TCM. Meanwhile, the core prescription we discovered has proved clearly effective by preliminary verification.
引文
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