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Chinese Journal of Antituberculosis ›› 2026, Vol. 48 ›› Issue (2): 197-205.doi: 10.19982/j.issn.1000-6621.20250366

• Original Articles • Previous Articles     Next Articles

Survival status and influencing factors analysis of patients with rifampicin-resistant pulmonary tuberculosis in Kashgar Prefecture, Xinjiang Uygur Autonomous Region, 2013—2022

Su Wei1, Bai Xinyu2, Maiwulajiang Yimamu3, Keyoumu Wubulikasimu2, Diermulati Tusun3, Lai Fuli2, Mirenisha Abudurexiti2, Xirizhati Mamuti2, Zhou Linjun2(), Huang Fei1()   

  1. 1 National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention (Chinese Academy of Preventive Medicine), Beijing 102206, China
    2 Kashgar Prefectural Institute for Tuberculosis Control and Prevention, Xinjiang Uygur Autonomous Region, Kashgar 844099, China
    3 Kashgar Prefectural Center for Disease Control and Prevention, Xinjiang Uygur Autonomous Region, Kashgar 844100, China
  • Received:2025-09-09 Online:2026-02-10 Published:2026-02-03
  • Contact: Zhou Linjun, Email:1149306215@qq.com;Huang Fei, Email: huangfei@chinacdc.cn
  • Supported by:
    Disease Contro-Tuberculosis Prevention and Control;Science and Technology Bureau of Kashgar Prefecture, Xinjiang Uygur Autonomous Region(KS2022047)

Abstract:

Objective: To analyze the survival status and influencing factors of patients with rifampicin-resistant pulmonary tuberculosis (RR-PTB) in Kashgar Prefecture, Xinjiang Uygur Autonomous Region, and to provide a scientific basis for optimizing the prevention and control strategies of drug-resistant tuberculosis. Methods: A retrospective analysis was performed on the survival status of RR-PTB patients diagnosed in Kashgar Prefecture since the initiation of standardized diagnosis and treatment for drug-resistant tuberculosis in 2013, up to the end of 2022. The life table method was used to analyze the death probability, survival probability and cumulative survival rate of the patients; the Kaplan-Meier method was used to calculate the median survival time and draw the survival curve, and the Log-rank test was performed; univariate and multivariate Cox proportional hazards regression models were applied to analyze the risk factors affecting the survival of RR-PTB patients. Results: A total of 782 RR-PTB patients were included in the analysis, with a maximum follow-up duration of 9.9 years. During the follow-up period, 40.0% (313/782) of the patients died, with deaths predominantly concentrated in the first year after diagnosis (121 cases), particularly within 2 months after diagnosis (31 cases, accounting for 25.6%). The overall mortality density was 4.4/100 person-years, showing a decreasing trend. The median survival time of the patients was 80.9 (95%CI: 61.3-100.5) months, and cumulative survival rates at the 12th, 36th, and 60th months were 74.2%, 61.5%, and 52.2%, respectively. The average survival times of patients who presented with the three adverse treatment outcomes of treatment failure, loss to follow-up, and unevaluated were (67.9±7.9), (67.4±3.8), and (71.1±3.6) months, respectively, and the difference in survival times between the groups was statistically significant by the Log-rank test (χ2=27.631, P<0.001). Multifactorial Cox proportional risk model analysis revealed that non-treatment (compared to the treated patients, HR=2.642,95%CI: 2.018-3.458), retreatment (compared to the new patients, HR=1.779, 95%CI: 1.359-2.329) and low education(compared to the primary school or below group, the junior high school group: HR=0.652, 95%CI: 0.443-0.959)were factors affecting the survival time of patients. Conclusion: RR-PTB patients in Kashgar Prefecture have a notably high mortality rate and bear a heavy disease burden. Non-treatment, retreatment and low education level are risk factors affecting the survival of patients, and patients with adverse treatment outcomes such as treatment failure have a prolonged infectious period. It is recommended to promote rapid drug susceptibility testing technology and short-course treatment regimens, ensure that all eligible patients receive treatment, provide appropriate health education, and strengthen patient care and support, so as to reduce the risk of death and alleviate the disease burden.

Key words: Tuberculosis, pulmonary, Rifampin, Drug resistance, Survival analysis, Risk factors

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