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原发性肝癌的中医体质类型分布及其预后因素分析 被引量:28

Distribution of Traditional Chinese Medicine Constitution and Prognostic Analysis of Primary Liver Cancer
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摘要 目的:探讨原发性肝癌的中医体质类型分布及其预后因素。方法:采用标准化的中医体质分类量表,对151例原发性肝癌患者进行中医体质辨识并分析中医体质类型等因素对肝癌预后的影响结果:患者的体质类型分布为:平和质37例(24.5%),气虚质36例(23.8%),阳虚质25例(16.6%),湿热质21例(13.9%),气郁质14例(9.3%),瘀血质10例(6.6%),特禀质4例(2.6%),阴虚质2例(1.3%),痰湿质2例(1.3%)单因素及多因素分析结果提示体质类型为气虚质、临床分期、AFP水平和CLIP评分均是生存期的独立影响因素、其中气虚质是值得进一步研究的可能影响患者预后的独立危险因素。结论:肝癌患者的偏颇体质主要以气虚质、阳虚质和湿热质三种体质为主。 Objective: To investigate the distribution of Chinese medicine constitution and analyze the prognostic factors among cases with the primary liver cancer ( PLC ). Methods: The standardized classification measurement questionnaire of nine constitutions in Chinese medicine was used to investigate the Chinese medicine constitution of 151 PLC patients. The impacts of this Chinese medi- cine constitution and other factors for prognosis of PLC were analyzed. Results: The types of Chinese medicine constitutions were as follows: gentleness, qi-deficiency, yang-deficiency, wet-heat, qi-depression, blood-stasis, special diathesis, yin-deficiency, and phlegm-wetness. The number of corresponding patients per constitution were as follows: 37 ( 24.5% ), 36 ( 23.8% ), 25 ( 16.6% ), 21 ( 13.9% ), 14 ( 9.3% ), 10 ( 6.6% ), 4 (2.6%), 2 ( 1.3% ), and 2 ( 1.3% ), respectively. Univariate and multivariate analyses indicated that qi-deficiency type, TNM stating, AFP level, and CLIP score were independent prognostic factors for survival time, and that qi-deficiency type was an important independent factor that might be worth further investigation for predicting prognosis. Conclusion: The constitutions of Chinese medicine in patients with PLC were predominantly gentleness, qi-deficiency, yang-deficiency, and wet-heat types. Qi-deficiency type was a strong independent prognostic factor for survival of PLC patients.
出处 《中国肿瘤临床》 CAS CSCD 北大核心 2012年第2期101-104,共4页 Chinese Journal of Clinical Oncology
关键词 中医体质类型 原发性肝癌 COX回归分析 Chinese medicine constitution patterns Primary liver cancer COX regression
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