Analisis Survival Menggunakan Regresi Eksponensial, Cox Proporsional dan Frailty pada Penderita TBC
Abstract
According to the WHO Global TB Report 2020, Indonesia is among the countries with the highest tuberculosis (TB) burden worldwide, with an estimated 845.000 people affected by TB and 98.000 deaths, which translates to 11 deaths per hour. However, only 67% of these cases have been identified and treated, leaving around 283.000 TB patients undiagnosed and untreated, putting them at risk of spreading the disease to others. This study aims to examine the factors that impact the recovery time of TB patients through Exponential regression and Cox Proportional Hazards (Cox-PH) regression. Additionally, unmeasured factors are incorporated into the model using the frailty model approach. The data used were medical records of 153 TB patients at Soehadi Prijonegoro Regional Public Hospital in Sragen. The study results show that the Cox-PH regression model yields a lower AIC value compared to the Exponential regression and frailty models, indicating that the survival analysis performance using the Cox-PH regression is superior to the other two models. Based on the Cox-PH regression modeling, the factors affecting the recovery duration of TB patients are comorbidities, previous cases, and diagnosis.
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