Factors associated with time to successful treatment in Thai patients with newly diagnosed pulmonary TB in upper southern Thailand
DOI:
https://doi.org/10.14456/dcj.2021.82Keywords:
new PTB, time to successful treatment, survival analysisAbstract
This study aims to explore factors associated with time to successful treatment in new Thai pulmonary tuberculosis (PTB) patients. The secondary data of new PTB registered cases derived from NTIP online program provided by the Office of Disease Prevention and Control, Region 11 Nakhon Si Thammarat, comprised 14,963 cases from 2014 to 2017. Kaplan-Meier functions are used to estimate survival probabilities and time to successful treatment about interesting factors. Cox proportional hazards model provide estimates of survival probabilities and cumulative hazard than those provided by the Kaplan-Meier function for adjusted confounding. R program is used for data analysis. Descriptive results presented 81.87% of the treatment success rate and 18.13% of otherwise. Kaplan-Meier show overall median time to successful treatment 189 days (95%CI 189-190). Cox proportional hazards model found gender, residential province, year, initial AFB, HIV, and NCD comorbidity are significantly associated with time to successful treatment (p-value < 0.05). Males had time to successful treatment more than females 8%. Krabi had the shortest time to successful treatment followed by Chumphon, Phang-Nga, Nakhon Si Thammarat, Surat Thani, Ranong, and Phuket, respectively. Initial positive AFB had time to successful treatment more than negative smear AFB 7%. HIV positive and NCD comorbidity affected for time to successful treatment more than HIV negative and no-NCD comorbidity of 40% and 22%, respectively. Therefore, health staff should be focusing on male patients, patients with initial positive AFB, patients with HIV positive, and patients with NCD comorbidity due to delay time to successful treatment. Estimated hazard ratio may be inaccurate due to some survival curves' shape violated the assumptions of Cox proportional hazard model.
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