Tuberculosis (TB), a disease caused by
Tuberculosis (TB), a disease that killed approximately 2 billion people over the last 200 years, remains a threat to humankind [
Based on the national population survey of Ethiopia conducted in 2010, the prevalence of smear-positive and all forms of TB had estimated 108/100,000 population and 240/100,000 population, respectively [
This study was a retrospective study design. Participants of the study were recruited at the admission point of the MDR-TB and followed up during their stay in the unit, with note-taking of all significant clinical events. The data considered in the study belongs to a patient of tuberculosis who started multidrug treatment at different hospitals before six months of February, 1.2018.
The study was conducted on multidrug-resistant tuberculosis in different hospitals of Amhara region which is located in the north west part of Ethiopia.
The data were obtained from different hospitals of Amhara region that have multidrug resistance tuberculosis patients (Debre Tabor Hospital, Gondar Teaching Hospital, and Debre Markos Hospital). The hospital location or district patients were the random effect for this study
Data was collected by the nurses from patients’ record charts using a pretested standard questionnaire and follow-up data collection form. The data were collected from February to April in 2018.
The collected data was coded to maintain confidentiality, then entered into Epi Info, and analyzed using STATA software version 14.
The response variable in the study was survival time of MDR-TB patients. The survival time of MDR patients was a treatment continued until the date of death or censor occurred. The date of data was obtained from the patient’s history charts. Sociodemographic factors, clinical factors, and districts of hospitals were the independent variable in this study.
In this study, we considered survival models for the multidrug resistance TB dataset which are spatially arranged. Such a spatial arrangement of the strata can be used in geostatistical modeling of the strata. Then, spatial frailty model was applied to analyze multidrug resistance TB. In this study, gamma shared frailty was used with different baseline distributions. Using STATA software, the hazard rate of death and the significance of factors were identified.
Cox proportional hazard model is presented in the form
The joint posterior distribution for the spatial frailty parametric Weibull model is
In this study, 207 multidrug resistance tuberculosis patients were considered to identify the factor of different duration death occurrence. Of these 61 (29.47%) were died and the rest, 146 (70.53%), of the patients were censored at the time of the study. Out of 207 MDR-TB patients, 146 (70.53%) were males, and 61 (29.5%) were females (Table
Summary results of MDR–TB by different demographic characteristics.
Covariates | Category | Death (%) | Censored (%) | Total (%) |
---|---|---|---|---|
Sex | Female | 33(40.74) | 48(59.26) | 81 |
Male | 28(22.22) | 98(77.78) | 126 | |
Age | 18-34 years | 15(14.56) | 88(85.44) | 103 |
35-54 years | 22(39.3) | 34(60.7) | 56 | |
>= 55 years | 24(50) | 24(50) | 48 | |
Marital status of the patient | Single | 16(20.78) | 61(79.22) | 77 |
Married | 36(36) | 64(64) | 100 | |
Separated/Divorced | 6(31.58) | 13(68.42) | 19 | |
Widow/Widowed | 3(30) | 7(70) | 10 | |
Employment status | Employed | 7(30.13) | 16(69.56) | 23 |
Own Business | 8(20) | 32(80) | 40 | |
Merchant | 16(40) | 24(60) | 40 | |
Daily labor | 4(23.53) | 13(76.47) | 17 | |
Unemployed | 26(29.89) | 61(70.11) | 87 | |
The educational level | Illiterate | 16(25.81) | 46(74.19) | 62 |
Read and Write | 23(29.49) | 55(70.51) | 78 | |
Secondary | 14(31.11) | 31(68.88) | 45 | |
Tertiary and above | 8(36.36) | 14(63.64) | 22 | |
Therapeutic delay | >= 1 Month | 31(41.89) | 43(58.11) | 74 |
< 1 Month | 30(22.56) | 103(77.44) | 133 | |
MDR category | Previously Treated for first-line TB | 26(17.11) | 126(82.89) | 152 |
Previously not Treated | 35(64.81) | 19(35.19) | 54 | |
Current Smoking Status | Yes | 23(65.71) | 12(34.29) | 35 |
No | 38(22.09) | 134(77.91) | 172 | |
Current Alcohol use | Yes | 31(60.78) | 20(39.22) | 51 |
No | 30(19.23) | 126(80.77) | 156 | |
City | Debre Tabor | 6(27.27) | 16(72.73) | 22 |
Gondar | 49(33.56) | 97(66.44) | 146 | |
D/Markos | 6(15.38) | 33(84.62) | 39 |
The minimum duration of follow-up was one month whereas the maximum duration was 42 months. Table
Summary results of MDR–TB by clinical characteristics.
Covariates | Category | Death (%) | Censored (%) | Total (%) |
---|---|---|---|---|
Any clinical complication | No complication | 35(20.35) | 137(79.65) | 172 |
Pneumonia | 7(87.5) | 1(12.5) | 8 | |
Pneumothorax | 6(85.71) | 1(14.29) | 7 | |
Hemoptysis | 7(63.64) | 4(36.36) | 11 | |
Cor pulmonal | 4(100) | 0(0) | 4 | |
Other | 2(40) | 3(60) | 5 | |
HIV Co-infection | Positive | 21(61.76) | 13(38.24) | 34 |
Negative | 40(23.12) | 133(76.88) | 173 | |
Acid-fast bacilli Smear (AFB) | positive | 43(28.28) | 109(71.71) | 152 |
Negative | 12(30) | 28(70) | 40 | |
Antibiotic Susceptibility | INH | 6(72.86) | 8(57.14) | 14 |
RMP | 24(30.38) | 55(69.62) | 79 | |
MDR | 26(30.95) | 58(69.05) | 84 | |
INH+RMP | 5(16.67) | 25(83.33) | 30 | |
Presence of any chronic disease | No chronic disease | 42(24.14) | 132(75.86) | 174 |
Diabetes Mellitus | 8(50) | 8(50) | 16 | |
Myocardial infarction | 4(100) | 0(0) | 4 | |
Asthma | 4(66.66) | 2(33.33) | 6 | |
other | 1(33.33) | 2(66.67) | 3 | |
Radiological findings | unilateral cavity | 9(26.47) | 25(73.53) | 34 |
unilateral infiltration | 3(33.33) | 6(66.67) | 9 | |
Bilateral cavity | 4(18.18) | 18(81.82) | 22 | |
Bilateral inflation | 7(38.89) | 11(61.12) | 18 | |
Non cavity | 14(27.45) | 37(72.55) | 51 | |
Effusion | 12(37.5) | 20(62.5) | 32 | |
Smear positivity | Positive | 46(31.94) | 98(68.06) | 144 |
Negative | 14(26.42) | 39(73.58) | 53 | |
Clinical Presentation | Pulmonary | 51(30) | 119(70) | 170 |
Extra pulmonary | 8(28.57) | 20(71.43) | 28 |
INH: isoniazid; RMP: rifampicin; MDR: multidrug-resistant.
The mean duration of death for MDR TB patients.
Mean | 95% confidence interval | ||
Estimate | Std. Error | Lower Bound | Upper Bound |
31.907 | 1.098 | 29.755 | 34.059 |
To identify sets of covariates that have the potential influence to be included in the linear components of a multivariable model, univariate analysis was done. Covariates that were found to be significant in the univariable analysis were included in the multivariable analysis. We performed multivariable survival analysis by assuming exponential, Weibull, Gompertz, and Log logistic distributions for baseline hazard functions and the frailty distributions.
The AIC and BIC values of Weibull baseline distribution with frailty model are found to be minimum among all other considered models. The results indicated that Weibull baseline distribution with gamma frailty model is the most efficient model to describe the multidrug resistance tuberculosis (Table
AIC and BIC values of shared frailty models.
Baseline Distributions | AIC | BIC |
---|---|---|
Exponential | 251.7942 | 311.696 |
Gompertz | 238.0642 | 301.2938 |
Log logistic | 241.6048 | 304.8344 |
Weibull | 234.4422 | 297.6718 |
Lognormal | 249.4659 | 312.6955 |
Model with shared frailty for multidrug resistance tuberculosis patients.
Weibull (No frailty) | Weibull (Gamma) | Weibull (Inverse Gaussian) | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Variable | Category | HR | SE | P>z | 95%CI | HR | SE | P>z | 95%CI | HR | SE | P>z | 95%CI |
Age | 18-34 | ||||||||||||
35-54 years | 1.823 | 0.841 | 0.193 | | 1.833 | .841 | 0.193 | | 1.824 | .843 | 0.194 | | |
>= 55 years | 3.940 | 1.768 | 0.002 | | 3.939 | 1.77 | 0.002 | | 3.943 | 1.77 | 0.002 | | |
Therapeutic delay | < 1 Month | 0.309 | .0982 | 0.000 | | .3092 | .098 | 0.000 | | .3095 | .098 | 0.000 | |
Alcohol use | No | 0.347 | .1247 | 0.003 | | .3466 | .125 | 0.003 | | .3479 | .125 | 0.003 | |
Any clinical complication | No complication | ||||||||||||
Pneumonia | 2.033 | .9656 | 0.135 | | 2.033 | .965 | 0.135 | | 2.037 | .969 | 0.135 | | |
Pneumothorax | 1.876 | 1.057 | 0.264 | | 1.876 | 1.066 | 0.264 | | 1.874 | 1.06 | 0.266 | | |
Hemoptysis | 1.524 | 1.008 | 0.524 | | 1.524 | 1.007 | 0.524 | | 1.525 | 1.01 | 0.524 | | |
Cor pulmonale | 2.816 | 1.180 | 0.013 | | 2.816 | 1.180 | 0.013 | | 2.822 | 1.18 | 0.013 | | |
Other | 4.11e-06 | .0037 | 0.989 | 0 | 9.46e-11 | .0001 | 1.000 | 0. | 2.76e-08 | .001 | 0.999 | 0 | |
MDR category | Previously not Treated | 2.329 | .7306 | 0.007 | | 2.329 | .7305 | 0.007 | | 2.329 | .732 | 0.007 | |
HIV | Negative | 0.202 | .0668 | 0.000 | | .2024 | .0668 | 0.000 | | .2023 | .067 | 0.000 | |
chronic disease | No chronic disease | ||||||||||||
Diabetes Mellitus | 3.292 | 1.523 | 0.010 | | 3.292 | 1.523 | 0.010 | | 3.294 | 1.53 | 0.010 | | |
Myocardial infarction | 7.774 | 3.906 | 0.000 | | 7.773 | 3.905 | 0.000 | | 7.774 | 3.913 | 0.000 | | |
Asthma | 3.085 | 1.326 | 0.009 | | 3.085 | 1.325 | 0.009 | | 3.086 | 1.328 | 0.009 | | |
DM and HTN | 2.483 | 2.980 | 0.449 | | 2.483 | 2.980 | 0.449 | | 2.498 | 2.999 | 0.446 | | |
Other | 1.950 | 2.162 | 0.547 | | 1.949 | 2.162 | 0.547 | | 1.956 | 2.171 | 0.545 | | |
| |||||||||||||
_cons | 0.0045 | .0032 | 0.000 | | .0045 | .0032 | 0.000 | | .0044 | .0032 | 0.000 | | |
/ln_p | 0.5228 | .1066 | 0.000 | | .5228 | .1066 | 0.000 | | .5231 | .1072 | 0.000 | | |
/ln _the | -16.82 | 849.2 | 0.984 | | -9.87 | 26.49 | 0.709 | | |||||
P | 1.687 | 0.1799 | | 1.687 | 0.1798 | | 1.687 | .1809 | | ||||
1/p | 0.5929 | .0633 | | 0.5928 | .0632 | | .5927 | .0636 | | ||||
Theta | 0.0000697 | .002 | | 0.0000516 | 0.0014 | |
Age of MDR patient, therapeutic delay, alcohol user, any clinical complication, MDR category, HIV results, and chronic diseases were significant at 5 percent level of significance by using Weibull-gamma shared frailty model (Table
Multidrug resistance tuberculosis patients with age difference was a significant factor for the death time of MDR. The hazard rate of death of MDR-TB patients who had age group of 55 and above year was 3.940 times higher than that of MDR-TB patients who had age group of 18-34 years (95% CI: 1.63, 9.549). Here, the confidence interval did not include one at 5% level of significance; they had the duration of death difference between ages group of MDR-TB. The age of MDR patients of 35-55 years was compared to 18-34 years and the accelerated factor was
The therapeutic delay was a significant association with mortality of MDR-TB patients. The hazard ratio of death therapeutic delay before one month was 0.309 at 5% level of significance. The acceleration factor and 95% confidence interval for multidrug resistance tuberculosis were 0.309 and (0.166, 0.576), respectively. The estimated coefficient hazard ratio of death MDR-TB patient who starts treatment before one month was reduced by 61.0% compared to MDR-TB patient who starts treatment after one month.
The alcohol use was another prognostic factor that predicts the mortality of MDR-TB patients. The result of this study indicates that the hazard ratio of death of non-alcohol takers was 0.347 times that of alcohol user (HR = 0.347, 95% CI: 0.171, 0.702). This indicates that, in multidrug resistance tuberculosis patients, survivability of TB of alcohol users was shortened compared with non-alcohol users. The clinical complication was a determinant factor of multidrug resistance tuberculosis for time of death of patients. But Pneumonia, Pneumothorax complication, Hemoptysis, and other clinical complications were not statistically significant (Table
The estimated relative risk (hazard ratio) of death for MDR-TB patients who developed chronic disease varied. The hazard of death of MDR-TB patients who developed diabetes mellitus compared to those who did not develop chronic disease was 3.292 higher (95% CI: 1.329, 8.151). The duration of the death of MDR-TB patients who developed diabetes mellitus was higher than those with non-chronic disease. The hazard of death of MDR-TB patients with Myocardial infarction was 7.774 times higher than that of MDR-TB patients who did not develop chronic disease (95% CI: 2.904,20.812). This result revealed that the risk of death of MDR-TB patients with Asthma was 3.086 higher than that of MDR-TB patients with no chronic disease (95% CI 1.329, 17.162). Thus, the coinfected chronic disease was the risk factor for the death of MDR-TB patients. This indicated that the duration of death for MDR-TB patients who had coinfected chronic disease was shorter compared to MDR-TB patients free from any chronic disease.
The hazard of death of MDR-TB patients that were previously not treated as compared to those previously treated was higher. The hazard of death of those previously not treated was 2.329 (95% CI: 1.260, 4.307). This indicates that the hazard of death was higher for MDR-TB patients who are previously not treated relative to previously treated ones. The risk of death for MDR-TB patients infected by HIV could be higher than those non-infected by HIV (HR= 0.2021 (95% CI: 0.116, 0.387)). The value of the shape parameter in the Weibull-gamma frailty model was
The main aim of the study was to determine survival time and predictors of mortality among patients under multidrug-resistant tuberculosis treatment. The study accounted for the correlation between MDR-TB among districts of hospitals. The comparison of models was selected by using the AIC and BIC criteria, where a model with minimum AIC and BIC was accepted to be the best. According to AIC and BIC, the Weibull-gamma shared frailty model was the most appropriate model to describe the multidrug resistance tuberculosis dataset.
Based on clustered district of multidrug resistance tuberculosis patients, no heterogeneity death occurred in patients. Hence, our study showed that there was no cluster (frailty) effect based on grouped district of the hospitals. The survival time of multidrug resistance tuberculosis variation was not due to the heterogeneity (among patients of the district). The district of hospitals did not effect the death of patients.
This study revealed that as the age of the patient’s increases, the survival probability of the MDR-TB patient declines. Similar findings have been observed in [
Multidrug resistance tuberculosis patients having coinfected by HIV had shorter duration of death in treatment periods than that of HIV negative MDR-TB patients. This finding was consistent with a study in America and southern Africa [
Based on AIC and BIC values, the most appropriate model for our dataset was Weibull, which well described the survival of tuberculosis. In this study, there was no frailty (district) effect on the survival of multidrug-resistant tuberculosis. The death of tuberculosis patients attending multidrug resistance was 61 (29.5%) and the rest, 146 (70.53%), of patients were censored. The mean duration of death attending tuberculosis in multidrug resistance was 31.07 months (95%, CI: 29.75, 34.056). The Weibull non-frailty model shows that the old age, delays treatment, alcohol use, any clinical complication previously not treated, positive HIV/AIDS, and any chronic disease of patients under multidrug resistance tuberculosis were significant variables.
Acid-fast bacilli smear
Akaike information criterion
Bayesian information criterion
Confidence interval
Hazard ratio
Multidrug resistance
Tuberculosis
Human immunodeficiency virus
World Health Organization.
In consultation with the Bahir Dar University Ethics Committee that approved this study, the data of the study cannot be publicly available due to the privacy protection of patients. Therefore, sharing the dataset is not possible.
Multiple drug resistance (MDR) is antimicrobial resistance shown by a species of a microorganism to multiple antimicrobial drugs [
The study protocol was approved by the Ethics Committee of the College of Science, BDU.
Ashenafi Abate Woya is a Principal Investigator.
The authors declare that they have no conflicts of interest.
Ashenafi Abate Woya, Abay Kassa Tekile, and Garoma Wakjira Basha participated in the design, coordination of the study, and manuscript revision and correction. Ashenafi Abate Woya was involved in data analysis and interpretation. Ashenafi Abate Woya and Abay Kassa Tekile drafted and reviewed the manuscript. All authors read and approved the final manuscript.