Survival analysis of patients with tuberculosis and risk factors for multidrug-resistant tuberculosis in Monrovia, Liberia

Carter, Boye Bobby; Zhang, Yang; Zou, Hangjin; Zhang, Chuhan; Zhang, Xinming; Sheng, Rongtian; Kou, Changgui; Li, Yin

doi:10.1371/journal.pone.0249474

Cited by 10 publications

(8 citation statements)

References 25 publications

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“…Early detection of drug resistance can reduce the incidence of mortality per year. In a 21 month follow-up, the probability of survival was reported 90.2%, 12 which is significantly higher than the 71% reported in the present study.…”

Section: Discussioncontrasting

confidence: 76%

Survival Probability in Multidrug Resistant Pulmonary Tuberculosis Patients in a South Indian Region

Smitha,

Sunitha,

Prabhakar

et al. 2024

Hosp Pharm

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Background: Drug-resistant tuberculosis is a burgeoning threat to public health requiring novel strategies to combat the infection. Although national tuberculosis elimination programs focus on improving health services, challenges in eradicating tuberculosis still exist. Factors attributing to unfavorable outcomes are unknown in Warangal district of Telangana state. Methods: This study included 296 patients diagnosed with multidrug-resistant pulmonary tuberculosis. The study participants followed up for a maximum of 20 months to determine treatment outcomes. Statistical applications of Kaplan-Meier curve and log-rank test used to find the survival probabilities in subgroups. Results: The survival of multidrug-resistant pulmonary tuberculosis patients was ascertained, in male and female patients, aged between 31 and 50 years. Resistance to rifampicin was prominent. The study found a survival rate of 76.68% and a mortality rate of 23.31%. The log-rank test revealed a significant difference in survival in subcategories with and without comorbidities ( P = .03), non-adherence to treatment ( P = .0001), treatment duration ( P = .02), regimens ( P = .01), and grading of radiograph ( P = .0001). Conclusion: This study identified factors that influenced the survival probability of multidrug-resistant pulmonary tuberculosis patients, including comorbidities, weight band, non-adherence to treatment, treatment duration, regimens, and grading of radiograph. These findings emphasize the need for enhanced management strategies to improve treatment outcomes.

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Section: Discussioncontrasting

confidence: 76%

Survival Probability in Multidrug Resistant Pulmonary Tuberculosis Patients in a South Indian Region

Smitha,

Sunitha,

Prabhakar

et al. 2024

Hosp Pharm

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“…Tuberculosis (TB) is one of major causes of death in the world [ 1 ]. In 2019, the World Health Organisation (WHO) estimated 10 million new TB cases with an estimated 15% mortality [ 2 , 3 ].…”

Section: Introductionmentioning

confidence: 99%

Key factors influencing multidrug-resistant tuberculosis in patients under anti-tuberculosis treatment in two centres in Burundi: a mixed effect modelling study

et al. 2021

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Background Despite the World Health Organization efforts to expand access to the tuberculosis treatment, multidrug resistant tuberculosis (MDR-TB) remains a major threat. MDR-TB represents a challenge for clinicians and staff operating in national tuberculosis (TB) programmes/centres. In sub-Saharan African countries including Burundi, MDR-TB coexists with high burden of other communicable and non-communicable diseases, creating a complex public health situation which is difficult to address. Tackling this will require targeted public health intervention based on evidence which well defines the at-risk population. In this study, using data from two referral anti-tuberculosis in Burundi, we model the key factors associated with MDR-TB in Burundi. Methods A case-control study was conducted from 1stAugust 2019 to 15th January 2020 in Kibumbu Sanatorium and Bujumbura anti-tuberculosis centres for cases and controls respectively. In all, 180 TB patients were selected, comprising of 60 cases and 120 controls using incidence density selection method. The associated factors were carried out by mixed effect logistic regression. Model performance was assessed by the Area under Curve (AUC). Model was internally validated via bootstrapping with 2000 replications. All analysis were done using R Statistical 3.5.0. Results MDR-TB was more identified among patients who lived in rural areas (51.3%), in patients’ residence (69.2%) and among those with a household size of six or more family members (59.5%). Most of the MDR-TB cases had already been under TB treatment (86.4%), had previous contact with an MDR-TR case (85.0%), consumed tobacco (55.5%) and were diabetic (66.6 %). HIV prevalence was 32.3 % in controls and 67.7 % among cases. After modelling using mixed effects, Residence of patients (aOR= 1.31, 95%C: 1.12-1.80), living in houses with more than 6 family members (aOR= 4.15, 95% C: 3.06-5.39), previous close contact with MDR-TB (aOR= 6.03, 95% C: 4.01-8.12), history of TB treatment (aOR= 2.16, 95% C: 1.06-3.42), tobacco consumption (aOR = 3.17 ,95% C: 2.06-5.45) and underlying diabetes’ ( aOR= 4.09,95% CI = 2.01-16.79) were significantly associated with MDR-TB. With 2000 stratified bootstrap replicates, the model had an excellent predictive performance, accurately predicting 88.15% (95% C: 82.06%-92.8%) of all observations. The coexistence of risk factors to the same patients increases the risk of MDR-TB occurrence. TB patients with no any risk factors had 17.6% of risk to become MDR-TB. That probability was respectively three times and five times higher among diabetic and close contact MDR-TB patients. Conclusion The relatively high TB’s prevalence and MDR-TB occurrence in Burundi raises a cause for concern especially in this context where there exist an equally high burden of chronic diseases including malnutrition. Targeting interventions based on these identified risk factors will allow judicious channel of resources and effective public health planning.

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“…In contrast to the previous studies that recruited volunteers in the hospital population or program groups to observe the survival time and its associated factors, our study considered all direct deaths caused by PTB in Zhejiang Province through the accurate matching of two available surveillance systems. 20–22 The strength of our study, which has comprehensive sample and precise outcome, could clarify associations and provide more robust results.…”

Section: Discussionmentioning

confidence: 90%

Survival Analysis and Associated Factors for Pulmonary Tuberculosis Death: Evidence from the Information System of Tuberculosis Disease and Mortality Surveillance in China

Liu¹,

Ai²,

Jin³

et al. 2022

RMHP

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Background Pulmonary tuberculosis (PTB) is a severe infection, and its factors that influence survival have not been explored in some developed regions. Therefore, this study aimed to identify the factors that influence TB survival in China. Methods We acquired data of PTB deaths through matching two manage systems of PTB and mortality surveillance. The Kaplan–Meier method and Cox regression model were used to identify the significant factors under various survival times. Results A total of 283 deaths were caused by PTB, in which 53.4% occurred during the first year. In the Cox regression model, regular sputum smear test could reduce the risk of PTB death from the result of one-, three-, and five-year survival; and history of PTB treatment could decline the risk of PTB death in the first year. Additionally, age of “75–90 years” and positive result of sputum smear test significantly increased the risk of PTB death for the findings of three- and five-year survival, while age of “60–75 years” could increase the probability of PTB death for five-year survival. Conclusion To reduce PTB deaths, more attention should be paid to the older group especially in the first year. Regular sputum smear test could effectively reduce the mortality of PTB cases. More evidence-based interventions should be implemented to enhance the survival of patients with PTB.

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Survival analysis of patients with tuberculosis and risk factors for multidrug-resistant tuberculosis in Monrovia, Liberia

Cited by 10 publications

References 25 publications

Survival Probability in Multidrug Resistant Pulmonary Tuberculosis Patients in a South Indian Region

Survival Probability in Multidrug Resistant Pulmonary Tuberculosis Patients in a South Indian Region

Key factors influencing multidrug-resistant tuberculosis in patients under anti-tuberculosis treatment in two centres in Burundi: a mixed effect modelling study

Survival Analysis and Associated Factors for Pulmonary Tuberculosis Death: Evidence from the Information System of Tuberculosis Disease and Mortality Surveillance in China

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