The Targeted Maximum Likelihood estimation to estimate the causal effects of the previous tuberculosis treatment in Multidrug-resistant tuberculosis in Sudan

Adel Hussein Elduma, Kourosh Holakouie-Naieni, Amir Almasi-Hashiani, Abbas Rahimi Foroushani, Hamdan Mustafa Hamdan Ali, Muatsim Ahmed Mohammed Adam, Asma Elsony and Mohammad Ali Mansournia

PLOS ONE, 2023, vol. 18, issue 1, 1-12

Abstract: Introduction: This study used Targeted Maximum Likelihood Estimation (TMLE) as a double robust method to estimate the causal effect of previous tuberculosis treatment history on the occurrence of multidrug-resistant tuberculosis (MDR-TB). TMLE is a method to estimate the marginal statistical parameters in case-control study design. The aim of this study was to estimate the causal effect of the previous tuberculosis treatment on the occurrence of MDR-TB using TMLE in Sudan. Method: A case-control study design combined with TMLE was used to estimate parameters. Cases were MDR-TB patients and controls were and patients who cured from tuberculosis. The history of previous TB treatment was considered the main exposure, and MDR-TB as an outcome. A designed questionnaire was used to collect a set of covariates including age, time to reach a health facility, number of times stopping treatment, gender, education level, and contact with MDR-TB cases. TMLE method was used to estimate the causal association of parameters. Statistical analysis was carried out with ltmle package in R-software. Result presented in graph and tables. Results: A total number of 430 cases and 860 controls were included in this study. The estimated risk difference of the previous tuberculosis treatment was (0.189, 95% CI; 0.161, 0.218) with SE 0.014, and p-value (

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0279976

DOI: 10.1371/journal.pone.0279976

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