Analysis of successful treatment factors and establishment of predictive models for multidrug-resistant tuberculosis patients

doi:10.19871/j.cnki.xfcrbzz.2023.04.007

Abstract

Abstract: Objective To analyze the factors related to treatment success in patients with MDR-TB, and establish a nomogram model to predict the probability of treatment success. Method 263 MDR-TB patients admitted to the tuberculosis Department of Chengdu Public Health Clinical Medical Center from November 2019 to May 2022 were retrospectively analyzed. The patients were divided into model group (184 cases) and verification group (79 cases) by 7:3. According to the efficacy results, the model group was divided into successful treatment group and adverse outcome group, and the clinical parameters, CT examination results and laboratory indicators of the two groups were compared. After the potential factors were screened by LASSO regression method, multivariate Logistic regression analysis was performed, and a nomogram model was established and verified according to the results of multiple factors. Result Among the 184 patients in the model group, 103 (55.98%) cases were successfully treated, and 81 (44.02%) cases had adverse outcomes. The results of ascending Logistic regression analysis on the basis of LASSO regression showed that age, history of second-line anti-TB drug use, sputum turning negative after 6 months of treatment, lesion scope, multiple cavity, erythrocyte sedimentation rate and urinary protein were independent factors influencing the treatment success of MDR-TB patients. The AUC for successful treatment of MDR-TB patients was 0.894 (95%CI: 0.847-0.941). The AUC of the verification group was 0.865 (95%CI: 0.810-0.919). The prediction curves of the model group and the verification group were basically fitted with the standard curves. When this column chart model predicts that the probability threshold of treatment success for MDR-TB patients is 0.10-0.95, the net benefit rate for patients is greater than 0. Conclusion The success of treatment of MDR-TB patients is affected by age, history of second-line anti-TB drugs, sputum turning negative after 6 months of treatment and other factors. The nomogram model has high accuracy and differentiation in predicting the success of treatment of MDR-TB patients.

Key words: Multidrug-resistant tuberculosis, Multi factor analysis, Nomogram, Predictive models

CLC Number:

Wu Xueqing, Cheng Yao, Yang Ming, Yuan Ping, Li Jiao, Sun Qiuping. Analysis of successful treatment factors and establishment of predictive models for multidrug-resistant tuberculosis patients[J]. Electronic Journal of Emerging Infectious Diseases, 2023, 8(4): 30-35.

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