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目的:利用不同危险因素建立食管癌风险预测模型,为新疆哈萨克族食管癌高危人群监测体系的建立提供循证依据和基础信息.方法:利用前期收集对照和当地人群对照环境、行为危险因素和基因检测数据,采用条件Logistic回归筛选危险因素,利用Logistic判别建立预测模型.结果:以哈萨克族对照,饮酒(OR=2.77)、饮食不规律(OR=3.42)、经常暴饮暴食(OR=4.01)、少吃水果(OR=2.65)、胃病变史(OR=2.66)、进食速度快(OR=1.94)、食管癌家族史(OR=2.06)、HLA-DRB1*0901(OR=2.83)、TAP2379(OR=2.09)、CYP2E1(OR=1.60)10个因素进入模型;以人群对照时,年龄(OR=1.10)、饮酒(OR=6.27)、饮食不规律(OR=118.05)、经常热烫饮食(OR=3.02)、经常暴饮暴食(OR=2.11)、少吃水果(OR=6.80)、吃熏制肉(OR=17.14)、胃病变史(OR=5.31)7个因素进入模型;从判别效果看4个模型的判别正确率分别为74.6%、70.1%、76.1%和96.9%.模型四的判别效果最好.结论:以环境、不良行为因素建立的风险预测模型适合基层应用,风险预测模型可以通过该简单、有效的预测概率模型进行风险自我评估.
Objective: To establish esophageal cancer risk prediction model with different risk factors and provide evidence base and basic information for the establishment of surveillance system of high risk population of esophageal cancer in Xinjiang Kazak.Methods: According to the comparison of environmental and behavioral risk factors and gene (OR = 3.42), regular binge eating (OR = 4.01), alcohol consumption (OR = 2.77), dietary irregularity (OR = 2.66), fasting rate (OR = 1.94), family history of esophageal cancer (OR = 2.06), HLA-DRB1 * 0901 (OR = 2.83), TAP2379 (OR = 2.09) and CYP2E1 (OR = 1.60), respectively. There were 10 factors (OR = 1.60) (OR = 3.02), frequent overeating (OR = 2.11), eating less fruit (OR = 6.80), eating smoked meat (OR = 17.14) and gastric history (OR = 5.31) The results show that the discrimination accuracy of the four models are 74.6%, 70.1%, 76.1% and 96.9%, respectively, and the discriminant effect of Model 4 is the best.Conclusion: Environment, risk prediction model for adverse behavioral factors established for grassroots applications, risk prediction models can be this simple, effective predictive probability model risk self-assessment.