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Factors associated with survival of tuberculosis patients in Southeast Iran

Comparison of stepwise cox regression, survival tree, and random survival forest

Bibliographic Data

ID15364173
AuthorsMehdi Sharafi (0000-0002-6505-9463, Gerash University of Medical Sciences), Sakineh Narouee (0000-0003-2908-3965, Kerman University of Medical Sciences), Feizorrahman Rasoulizadeh (Iranshahr University), Maryam TalebiMoghaddam (Kerman University of Medical Sciences, corresponding author), Jamileh Dadgar (Iranshahr University), Mohsen Khaleghi (0000-0002-5395-4460, Islamic Azad University, Fasa Branch), Abdoljabbar Zakeri (0000-0001-5701-0259, Hormozgan University of Medical Sciences), Najibullah Baeradeh (0000-0002-2215-3791, Birjand University of Medical Sciences)
Year2025
Volume25
Issue1
Pages3504-3504
Publication date2025-10-15
Open AccessYes
TypeARTICLE
VenueBMC Public Health (JOURNAL)
Journal identifiersISSN: 1471-2458 • E-ISSN: 1471-2458
PublisherBioMed Central (PUBLISHER • GB)
DOI10.1186/s12889-025-24603-1
PMID41094468
OpenAlexW4415192025
LanguageEN
References cited40

Understanding the factors associated with survival of tuberculosis (TB) patients is crucial for effective control and prevention efforts. This study aimed to identify the survival factors of TB patients in Iran. A historical cohort study was conducted using data from the Iranshahr (Southeast Iran) Tuberculosis Control Program. Stepwise Cox regression, survival tree analysis, and Random Survival Forest (RSF) models were employed to identify survival predictors. The C-index was used for model comparison. Of the 3429 TB patients (2016-2021), 292 (8.5%) died. Stepwise Cox regression revealed that positive smears after 2 and 3 months of treatment significantly increased mortality risk [HR: 15.44 and HR: 38.28, respectively]. Other factors contributing to a higher risk of death included being a prisoner [HR: 3.8], chest pain [HR: 1.35], and older age [HR: 1.01] (P < 0.05). In contrast, having extrapulmonary TB [HR: 0.16], nationality (Afghan or Pakistani) [HR: 0.36], and increased weight [HR: 0.98] reduced the risk of death (P < 0.05). RSF analysis identified a positive smear after two months as the most critical variable, followed by age, smear results after three months, weight, and TB type. The stepwise Cox model demonstrated a higher C-index than the RSF model. This study highlights key factors associated with the TB patient survival in the region, urging health policymakers to focus on early diagnosis and treatment optimization, especially for high-risk groups

Biostatistics · Cohort · Cohort study · Proportional hazards model · Stepwise regression · Survival analysis · Tuberculosis · Diagnosis and treatment of tuberculosis · Pneumonia and Respiratory Infections · Tuberculosis Research and Epidemiology · Epidemiology

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