Survival Modelling of Tuberculosis Data-A Case Study of Federal Medical Centre, Bida, Nigeria
Modern Applied Science
The article aimed at fitting Cox-proportional hazards model to Tuberculosis (TB) data. TB data on 259 patients spanning 2010 through 2016 were collected from the Federal Medical Centre, Bida, Nigeria. Covariates involved were gender, age, type of TB and occupation. Fifteen different Cox models, representing all possible combinations of covariates in question were fitted. Parameters were estimated by method of maximum partial likelihood and model selection was based on Akaike information
... information criterion (AIC). Model (G+C), with gender and occupation as covariates produced the least AIC of 618.597 and hence, was adjudged the best. That is, gender and occupation constituted the best subset of covariates that explained survival of TB patients. The model suggested that recovery hazard of a male TB patient was 24.1% lower than that of a female patient possessing same occupation. This implies that male patient had higher survival time than the female having same occupational status. It further suggested that recovery hazard for patient on technical occupation was 27.46% higher than for patient on non-technical job and of same gender. Hence, a patient on technical occupation had reduced survival time compared to one of same gender on non-technical occupation. It was concluded that gender and occupation explained best, survival of TB patients based on AIC.