MODELS FOR PREDICTING TIME TO SPUTUM CONVERSION AMONG MULTI-DRUG RESISTANT TUBERCULOSIS PATIENTS IN LAGOS, NIGERIA

Abstract

Multi-drug resistant tuberculosis (MDR-TB) develops due to problems such as irregular drug supply, poor drug quality, inappropriate prescription and poor adherence to treatment. These factors allow the development and subsequent transmission of resistant strains of the pathogen. With the advancements in statistics, mixture cure models provide the insight to the covariates that are related with the treatment outcomes. However, potential modifiable factors such as demographic and clinical characteristics are not clearly known in poor resource settings such as Nigeria. Therefore, this study was designed to determine the factors that can predict time to sputum conversion among MDR-TB patients using cure model. A retrospective clinic-based cohort study was conducted on 413 patients who were diagnosed of multi-drug resistant tuberculosis and met inclusion criteria from April 2012 to October 2016 at the Infectious Disease Hospital, Lagos. The main outcome measure (sputum conversion time) was the time from the date of commencement or MDR-TB treatment to the date of specimen collection for the first of two-consecutive negative smear and culture taken 30 days apart. The predictor variables of interest include: demographic (age, gender and marital status) and clinical characteristics (registration group, number of drugs resistant to during treatment initiation, HIV status, diabetes status and adherence with medication). Mixture Cox cure models were fitted to the main outcome variable using Log-normal, Log-logistic and Weibull distributions as alternatives to the violation of Proportional Hazards (PH) assumption. Akaike Information Criterion (AIC) was used for models comparison based on different distributions, while the effect of predictors of time to sputum conversion was reported as Hazard Ratio (HR) at a0.05. Age was 36.8±12.7 years, 60.8% were male and 67.6% were married. Majority of the patients (58.4%) converted to .sputum negative. Patients who were resistant to two drugs at treatment initiation had 39.0% rate of conversion than those resistant to at least three drugs [HR: 1.39 (CI:0.98, 1.98)]. The likelihood of sputum conversion time was shorter among non-diabetic patients compared to diabetics [HR: 0.55: (CI: 0.24, 0.85)]. The overall median time for sputum conversion was 5.5 (IQR: 1.5-11.5) months. In the cure model, resistance to more drugs at the time of initiation was significantly related with a longer sputum conversion time for Log normal Cox mixture [HR: 2.06 (CI: 1.36-3.47)]; Log-logistic Cox mixture cure [HR: 2.56 (CI: 1.85- 4.09)] and Weibull Cox mixture [HR: 2.81 (CI: 1.94-4.19)]. Diabetic patients had a significantly higher sputum conversion rate compared to non-diabetics; Log-normal Cox mixture [HR: 2.03 (CI: 1.17-3.58)); Log-logistic Cox mixture cure I I-IR: 2.11 (CI: 1.25-3.82)) and Weibull Cox mixture [HR: 2.02 (CI: 1.17-3.34)). However, Log-normal PH model gave the best fit and provided the fitness statistics [(-2LogL: 519.84); (AIC: 1053.68)). The best fitting Log-normal PH model was Y=1.00X1+2.06X2+0.98X3+2.03X1 I-E where Y is time to sputum conversion and X5 are age, number of drugs, adherence and diabetes status. The models confirmed the presence of some factors related with sputum conversion time in Nigeria. The quantum of drugs resistant at treatment initiation and diabetes status would aid the clinicians in predicting the rate of sputum conversion of patients.