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目的:通过检测HR-HPV感染、hTERC、c-myc基因扩增和MCM5蛋白在宫颈鳞状细胞癌及不同级别宫颈上皮内瘤变中的水平,筛选宫颈癌相关指标,建立回归模型用以预测宫颈鳞状细胞癌,并评估模型效果。方法:筛选初诊病理确诊宫颈鳞状细胞癌和CIN I、II、III级患者共200例作为研究对象,分别检测HR-HPV感染、hTERC、c-myc基因扩增及MCM5蛋白表达,用Logistic向后逐步回归的方法,筛选宫颈癌相关指标,建立回归模型预测宫颈鳞状细胞癌,并评估模型效果。结果:将HR-HPV负荷量及感染状况、hTERC、c-myc基因扩增和MCM5蛋白表达的检测数据绘制直方图,并进行Logistic向后逐步回归分析,得出hTERC、HR-HPV负荷量、MCM5回归系数分别为0.042、0.061和0.052,P值分别是0.024、0.005、0.005(P<0.05),HR-HPV感染状态和c-myc基因P值是0.856和0.682(P>0.05),被回归方程排除,提示hTERC(X_1)、HR-HPV负荷量(X_2)、MCM5(X_5)与回归方程存在线性关系,即与宫颈鳞状细胞癌发生有关,由此建立回归模型Logit(P)=-66.283+0.042X_1+0.061X_2+0.052X_5。评估模型拟合优度和预测准确度,H-L检验P值=1(P>0.05),模型拟合效果好,Cox-Snell R~2=0.643,Nagelkerke R~2=0.958,模型预测准确度98.5%,模型预测准确性高。结论:由hTERC、HR-HPV负荷量和MCM5蛋白建立的回归模型拟合效果较好,对宫颈鳞状细胞癌的预测准确度较高,hTERC、HR-HPV负荷量和MCM5蛋白联合检测能够用于宫颈鳞状细胞癌的预测评估,对CIN患者的分流管理和预后评估、宫颈鳞癌患者的早期诊断均有较高临床价值。
OBJECTIVE: To screen cervical cancer-related markers by detecting HR-HPV infection, hTERC, c-myc gene amplification and MCM5 protein in cervical squamous cell carcinoma and different levels of cervical intraepithelial neoplasia, and to establish a regression model to predict Cervical squamous cell carcinoma and evaluate the model effect. Methods: A total of 200 cases of cervical squamous cell carcinoma and CIN I, II and III patients with newly diagnosed cervical squamous cell carcinoma were screened for HR-HPV infection, hTERC, c-myc gene amplification and MCM5 protein expression. After gradual regression method, screening of cervical cancer related indicators, the establishment of a regression model to predict cervical squamous cell carcinoma, and evaluate the model effect. Results: The histogram of HR-HPV load, infection status, hTERC, c-myc gene amplification and MCM5 protein expression were plotted and logistic backward stepwise regression analysis was performed to get the hTERC, HR-HPV load, The regression coefficients of MCM5 were 0.042,0.061 and 0.052, P values were 0.024,0.005,0.005 (P <0.05) respectively. The HR-HPV infection status and c-myc gene P values were 0.856 and 0.682 (P> 0.05) The results suggested that there was a linear relationship between hTERC (X_1), HR-HPV load (X_2) and MCM5 (X_5) and regression equation, which was related to the occurrence of cervical squamous cell carcinoma. Logit (P) 66.283 + 0.042X_1 + 0.061X_2 + 0.052X_5. The goodness of fit and the prediction accuracy of the model were evaluated. The P value of HL test was 1 (P> 0.05). The model fitting effect was good. The Cox-Snell R ~ 2 = 0.643 and Nagelkerke R ~ 2 = 0.958, %, Model prediction accuracy. Conclusion: The regression model established by hTERC, HR-HPV load and MCM5 protein has good fitting effect and high accuracy in predicting cervical squamous cell carcinoma. Combined detection of hTERC, HR-HPV load and MCM5 protein can be used In cervical squamous cell carcinoma of the predictive assessment of CIN patients with shunt management and prognosis, cervical squamous cell carcinoma in patients with early diagnosis of high clinical value.