A time-to-event modelling of sputum conversion within two months after antituberculosis initiation among drug-susceptible smear positive pulmonary tuberculosis patients: Implementation of internal and external validation

Abstract

Delayed sputum conversion has been associated with a higher risk of treatment failure or relapse among drug susceptible smear-positive pulmonary tuberculosis patients. Several contributing factors have been identified in many studies, but the results varied across regions and countries. Therefore, the current study aimed to develop a predictive model that explained the factors affecting time to sputum conversion within two months after initiating antituberculosis agents among Malaysian with drug-susceptible smear-positive pulmonary tuberculosis patients. Retrospective data of pulmonary tuberculosis patients followed up at a tertiary hospital in the Northern region of Malaysia from 2013 until 2018 were collected and analysed. Nonlinear mixed-effect modelling software (NONMEM 7.3.0) was used to develop parametric survival models. The final model was further validated using Kaplan-Meier-visual predictive check (KM-VPC) approach, kernel-based hazard rate estimation method and sampling-importance resampling (SIR) method. A total of 224 patients were included in the study, with 34.4 % (77/224) of the patients remained positive at the end of 2 months of the intensive phase. Gompertz hazard function best described the data. The hazard of sputum conversion decreased by 39 % and 33 % for moderate and advanced lesions as compared to minimal baseline of chest X-ray severity, respectively (adjusted hazard ratio (aHR), 0.61; 95 % confidence intervals (95 % CI), (0.44–0.84) and 0.67, 95 % CI (0.53–0.84)). Meanwhile, the hazard also decreased by 59 % (aHR, 0.41; 95 % CI, (0.23–0.73)) and 48 % (aHR, 0.52; 95 % CI, (0.35–0.79)) between active and former drug abusers as compared to non-drug abuser, respectively. The successful development of the internally and externally validated final model allows a better estimation of the time to sputum conversion and provides a better understanding of the relationship with its predictors.