Cox Proportional Hazards Model Analysis of Survival Among Tuberculosis Patients Under Treatment in Mbuji-Mayi, Democratic Republic of the Congo

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Background: Tuberculosis (TB) remains one of the leading causes of death in Mbuji-Mayi, as in many other cities worldwide. Despite the availability of free treatment, TB continues to spread in the city due to weaknesses in health system performance, socioeconomic conditions, and limited financial resources. This study aimed to contribute to reducing TB-related mortality in Mbuji-Mayi by identifying risk factors affecting the survival of patients undergoing anti-tuberculosis treatment. Methods: A retrospective cohort study was conducted among tuberculosis patients registered and followed up in the TB treatment centers (CDTs) of Mbuji-Mayi between January 1 and December 31, 2024. Data were collected from patient records and treatment registers. A total of 1,633 cases were included in the analysis. Survival probabilities were estimated using the Kaplan–Meier method, and factors associated with survival were identified using the Cox proportional hazards model. Results: Multivariate analysis showed that comorbid conditions such as HIV and diabetes were significantly associated with mortality among TB patients (adjusted Hazard Ratio [aHR] = 4.65; p = 0.003). Drug resistance was strongly associated with reduced survival time (aHR = 12.12; p < 0.001). Male sex was more exposed to mortality compared to females (aHR = 9.94; p = 0.026), and tobacco or alcohol use was also a significant risk factor associated with decreased survival (aHR = 3.31; p = 0.046). Conclusion: The overall survival probability remained high, ranging from 99.7% in the first month to 98.8% in the fifth month of treatment. Most deaths occurred early during therapy. Mortality among TB patients in Mbuji-Mayi is mainly influenced by comorbidity, drug resistance, male sex, and tobacco or alcohol consumption. Strengthening early detection, adherence support, and management of comorbid conditions could improve patient survival. Keywords: survival modeling, tuberculosis, treatment outcomes, cox proportional hazards, mbuji-mayi, Democratic Republic of the Congo

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