摘要目的:分析常规检验项目作为肺结核治疗预后关键预测因子并构建早期预测模型的临床意义。方法:回顾性分析2012年1月—2020年12月苏州市第五人民医院的结核科163例肺结核患者（男144例、女19例，年龄41~70岁、平均年龄56岁）及体检科118名健康体检者（男101名、女17名，年龄46~64岁、平均年龄54岁）的基本信息、生化指标和血常规项目，根据肺结核患者治疗6个月后结核分枝杆菌检测结果分为治愈组（96例）和治疗失败组（67例），通过分析组间检验指标基线水平差异筛选出关键预测因子，并采用SPSS statistics 软件中的二元logistic回归方法联合关键因子构建预测模型。结果:治愈组和治疗失败组比较，总蛋白、白蛋白、前白蛋白、丙氨酸转氨酶、红细胞、血红蛋白及淋巴细胞的基线水平差异均有统计学意义（均 P<0.05）。治疗6个月后，总蛋白、白蛋白、前白蛋白在治愈组显著升高，而在治疗失败组仍处于较低水平。受试者工作特征曲线（ROC）分析显示，总蛋白、白蛋白、前白蛋白作为独立预测因子判断肺结核治疗预后的预测准确度最高，均具有一定的预测效率。logistic回归数据显示，联合这3项关键预测因子能够构建最佳早期预测模型用于肺结核治疗的预后评估，联合模型的预测准确度达到0.924（0.886~0.961），敏感度为75.0%，特异度为94.0%，具有较高的预测准确率。 结论:总蛋白、白蛋白、前白蛋白在构建肺结核治疗预后评估的早期预测模型中具有很好的应用价值，联合总蛋白、白蛋白及前白蛋白构建的早期预测模型有望为临床上结核病精准治疗和预后评估提供理论依据和参考方案。

abstractsObjective:To analyze the clinical significance of laboratory examination indicators as the key prognostic factors and to construct an early prediction model for prognosis assessment of pulmonary tuberculosis patients.Methods:The basic information, biochemical indexes and blood routine items of 163 tuberculosis patients (144 males and 19 females, aged 41-70 years, with an average age of 56 years) and 118 healthy persons who underwent physical examination (101 males and 17 females, aged 46-64 years, with an average age of 54 years) in Suzhou Fifth People′s Hospital from January 2012 to December 2020 were retrospectively collected. According to the presence of Mycobacterium tuberculosis after six months of treatment, the enrolled patients were divided into a cured group (96 cases) and a treatment failure group (67 cases). To analyze the baseline levels of laboratory examination indicators between these two groups, we screened the key predictors and the binary logistic regression method in SPSS statistics software was used to construct the prediction model. Results:The baseline levels of total protein, albumin, prealbumin, glutamic-pyruvic transaminase, erythrocyte, hemoglobin and lymphocyte were significantly higher in the cured group than in the treatment failure group. After 6 months of treatment, the indexes of total protein, albumin and prealbumin increased significantly in the cured group, but remained at the low levels in the treatment failure group. Receiver operating characteristic (ROC) curve analysis showed that total protein, albumin and prealbumin as independent predictors for forecasting the prognosis of pulmonary tuberculosis patients had the highest prediction accuracy. Logistic regression analysis showed that the combination of these three key predictors could construct the best early prediction model for assessing the prognosis of pulmonary tuberculosis patients, with a prediction accuracy of 0.924 (0.886-0.961), sensitivity of 75.0%, specificity of 94%, showing an ideal prediction accuracy.Conclusions:The routine test indexes of total protein, albumin and prealbumin show good application value in the construction of early prediction model for prognosis evaluation of pulmonary tuberculosis treatment. The combined prediction model consisting of total protein, albumin and prealbumin is expected to provide a theoretical basis and reference model for precision treatment and prognosis assessment of tuberculosis patients.