含利奈唑胺方案治疗肺结核患者的预后结局预测模型的构建与评价

Construction of prediction model for treatment outcomes of tuberculosis patients treated with linezolid-containing regimens and its predictive efficiency

  • 摘要: 目的 探索使用利奈唑胺进行抗结核治疗时,患者预后的影响因素。构建针对含利奈唑胺方案治疗肺结核患者的预后结局的预测模型。方法 对2019-2024年在长沙市中心医院收治的382例含利奈唑胺方案治疗的肺结核患者进行回顾性分析。按7∶3比例将患者随机分为训练集(n=267)和验证集(n=115)。训练集进一步根据预后情况分为预后良好组(n=208)和预后不良组(n=59)。采用多变量逻辑回归分析,确定肺结核患者预后情况的影响因素,并构建预测模型。通过受试者工作特征(ROC)曲线、校准曲线和决策曲线分析(DCA)评估模型的诊断价值和临床应用价值。结果 多变量逻辑回归分析显示,耐药(OR=2.594)、冠心病(OR=4.028)、C-反应蛋白(OR=1.010)以及护肝药(OR=0.308)与肺结核患者的预后情况有关(P<0.05)。列线图显示,总评分≥143分时预后不良风险超过90%。基于此构建的预测模型在训练集和验证集中均具有良好区分度,曲线下面积(AUC)分别为0.826、0.750; Hosmer-Lemeshow检验(训练集P=0.156,验证集P=0.520)进一步证实模型具有良好的校准性。DCA曲线表明,在0.05~0.55的阈值概率范围内模型具有临床实用性。结论 耐药、冠心病、C-反应蛋白以及护肝药对肺结核患者的预后情况具有预测价值,预测模型显示出较好的诊断性能。

     

    Abstract: OBJECTIVE To explore the influencing factors for treatment outcomes of the patients with tuberculosis who were treated with linezolid and construct the prediction model for treatment outcomes of the tuberculosis patients who were treated with linezolid-containing regimens. METHODS A total of 382 patients with pulmonary tuberculosis who were treated with linezolid-containing regimens in Changsha Central Hospital from 2019 to 2024 were retrospectively analyzed. The enrolled patients were randomly divided into the training set with 267 cases and the validation set with 115 cases in a 7∶3 ratio. The patients of the training set were divided into the favorable prognosis group with 208 cases and the poor prognosis group with 59 cases according to the treatment outcomes. Influencing factors for the treatment outcomes of the tuberculosis patients were determined by means of multivariate logistic regression analysis, and the prediction model was established. The diagnostic value and clinical application value of the model were evaluated through receiver operating characteristic (ROC) curves, calibration curves and decision curve analysis (DCA). RESULTS The multivariate logistic regression analysis showed that the prognosis of the tuberculosis patients was associated with drug resistance (OR=2.594), coronary heart disease (OR=4.028), C-reactive protein (CRP) (OR=1.010) and hepatoprotective drugs (P<0.05). Nomogram showed that the risk of adverse prognosis exceeded 90% when the total score was no less than 143 points. The prediction model had favorable discrimination degree in both the training set and the validation set, the areas under the curves(AUCs) were 0.826 and 0.750, respectively. Hosmer-Lemeshow test(the training set P=0.156, the validation set P=0.520) further proved that the model had good calibration. The DCA curve indicated that the model has clinical practicability when the threshold value of probability was within the scope of 0.05 to 0.55. CONCLUSIONS The drug resistance, coronary heart disease, CRP and hepatoprotective drugs have the values in prediction of prognosis of the tuberculosis patients. The prediction model shows favorable diagnostic efficiencies.

     

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