|Year : 2021 | Volume
| Issue : 2 | Page : 75-81
Primary drug resistance among Mycobacterium tuberculosis isolates from treatment naïve and new pulmonary tuberculosis patients in relation to their socio-economic status
Thushara Balakrishnan, N Girish
Department of Microbiology, Vydehi Institute of Medical Sciences and Research Centre, Bengaluru, Karnataka, India
|Date of Submission||10-Jul-2021|
|Date of Decision||13-Oct-2021|
|Date of Acceptance||26-Nov-2021|
|Date of Web Publication||27-Jan-2022|
Dr. Thushara Balakrishnan
Department of Microbiology, Institute of Medical Sciences and Research Centre, Whitefield, Bengaluru - 560 066, Karnataka
Source of Support: None, Conflict of Interest: None
BACKGROUND: Multidrug-resistant Tuberculosis (TB) has become an area of growing concern throughout the World, despite the global efforts in eliminating TB. Detection of primary drug resistance in treatment naïve patients, either due to spontaneous mutation or due to transmission of drug-resistant strains is an important indicator of the presence of drug-resistant strains in the community.
OBJECTIVES: The objective is to estimate the prevalence of primary drug resistance in treatment naïve pulmonary TB patients and to identify the socio-economic class of the resistant population.
MATERIALS AND METHODS: A total of 272 treatment naïve presumptive TB patients were enrolled in the study from September 2018 to December 2020. The samples were subjected to GeneXpert, for detecting the presence of Mycobacterium TB (MTB) along with Rifampicin (RIF) resistance detection. Phenotypic drug susceptibility testing (DST) was performed on all positive mycobacterial cultures using the 1% proportion method against first-line anti-tuberculous drugs. Socioeconomic status of the patients was also assessed based on updated Kuppuswamy Socioeconomic scale (2018).
RESULTS: Of the 272 samples subjected to GeneXpert MTB/RIF assay, MTB was detected in 193 (71%) samples and RIF resistance (rpoB gene) was detected in 25 (9%) samples. Phenotypic DST detected multidrug-resistant (MDR) in 22 (8%) samples. Majority of the MDR patients (55%) were belonging to the upper lower (IV) class of Kuppuswamy socio-economic scale.
CONCLUSION: High prevalence of MDR-TB among treatment naïve pulmonary TB patients was noted in patients belonging to Class IV of Kuppuswamy socio-economic scale.
Keywords: Drug susceptibility testing, Kuppuswamy socioeconomic scale, multidrug-resistant-tuberculosis
|How to cite this article:|
Balakrishnan T, Girish N. Primary drug resistance among Mycobacterium tuberculosis isolates from treatment naïve and new pulmonary tuberculosis patients in relation to their socio-economic status. J Acad Clin Microbiol 2021;23:75-81
|How to cite this URL:|
Balakrishnan T, Girish N. Primary drug resistance among Mycobacterium tuberculosis isolates from treatment naïve and new pulmonary tuberculosis patients in relation to their socio-economic status. J Acad Clin Microbiol [serial online] 2021 [cited 2022 Jul 1];23:75-81. Available from: https://www.jacmjournal.org/text.asp?2021/23/2/75/336586
| Introduction|| |
Tuberculosis (TB), a communicable disease caused by the bacillus, Mycobacterium TB (MTB), continues to remain the world's most deadly infectious disease infecting and killing millions of people every year, adding great impact on families and communities. India, the highest TB burden country in the world estimated an incidence of 26.9 lakh cases in 2019. The phenomenon of drug resistance in TB, observed some 50 years ago continues to remain, posing a great threat to the global target of ending TB by 2035., A quarter of the global burden of multidrug-resistant TB (MDR-TB) (Isoniazid [INH] and Rifampicin [RIF] resistant) was contributed by India. According to Global TB report 2020, 3.3% of new TB cases and 17.7% of previously treated cases had MDR/RR-TB in 2019, globally. Despite the introduction of WHO-approved rapid molecular diagnostic technologies such as Xpert MTB/RIF assay and Line Probe Assay, only 29% of all estimated (RIF-resistant TB) RR-TB/MDR-TB was diagnosed in India in 2017. Such larger gaps in the diagnosis of DR-TB can lead to pre-extensively drug-resistant and extensively drug-resistant TB, poorer treatment outcomes and continue the transmission of drug-resistant TB in the community.
As patterns of drug resistance differ from place to place and vary at different time period, knowing the magnitude and patterns of drug resistance is very important to formulate an effective therapeutic regimen. As patients infected with MDR-TB require a longer duration of therapy with expensive and toxic drugs and lower success rate, it is imperative to determine the level and pattern of MDR-TB and other factors associated with drug resistance to assist the National TB Control program in strengthening the treatment strategies for improved outcomes. Hence, the present study was undertaken to assess the rate of primary drug resistance to first-line drugs in newly diagnosed or treatment naïve pulmonary TB patients and also to identify the socioeconomic risk factors for acquiring the primary drug resistance.
| Materials and Methods|| |
Study design, area and period
This was a hospital-based observational, cross-sectional study conducted on 272 treatment naïve or newly diagnosed pulmonary TB patients, who visited the TB and Chest department, during September 2018-December 2020.
Patients of all age groups, both male and female, presumptive for pulmonary TB and no previous treatment history of anti-tubercular therapy (or <1 month history) were included in this study.
Extra-pulmonary TB patients and those who have taken anti-tubercular drugs for more than 28 days were excluded from the study.
The study was approved by the Vydehi Institutional Ethics Committee. Permission and support letter were also obtained from TB ward head. Sociodemographic data were obtained for each patient by a structured questionnaire after informed consent. The factors included: Age, sex, occupation, educational Status, monthly income, HIV infection, diabetes status and social habits like smoking/tobacco and alcohol.
All the samples were simultaneously subjected for acid-fast bacilli (AFB) detection by Ziehl–Neelsen (ZN) staining technique and molecular method, Xpert MTB/RIF assay, for simultaneous detection of MTB and RIF resistance. The number of AFB detected by ZN method was counted as per Revised National TB Control Program now National TB Elimination Program-(NTEP) guidelines. All the sample were cultured on to Lowenstein Jenson (LJ) slopes in a biological safety cabinet Class 2, Type 2A after decontamination by modified Petroff's method. The cultures were incubated at 37°C and observed for growth every week up to a maximum of 8 weeks. The isolates were identified as MTB by their slow growth rate, colony morphology, smear microscopy from cultures and SD Bioline TB Ag MPT64 Rapid test [Figure 1]. All culture positive samples with sufficient growth for the preparation of inoculum was subjected to drug susceptibility testing using economic variant of 1% proportion method on LJ medium slants for five first line anti-TB drugs (HI Media Laboratories) which included streptomycin (STR) (4 μg/ml), INH (0.2 μg/ml), RIF (40 μg/ml) Ethambutol (EMB) (2 μg/ml) and pyrazinamide (PZA) (200 μg/ml). A loopful of bacterial suspension matching McFarland standard No. 1 opacity with a concentration of 1 mg/ml of culture isolate and two appropriate dilutions (10−2 and 10−4 of undiluted suspension) of the bacilli were inoculated on drug containing and drug-free medium with a 3 mm diameter 24 SWG loop. The slants were incubated at 37°C and the results were read on 28th day and finalised on the 42nd day as per the NTEP protocol. Any strain with 1% (the critical proportion) of bacilli resistant to any of the antibiotics, was classified as resistant to that drug. The standard sensitive strain, H37Rv procured from National TB Institute, Bengaluru, was tested in each set of the tests. The test was considered valid, only when H37Rv showed sensitivity to all the tested drugs. Socioeconomic risk factors for acquiring the primary drug resistance were assessed using the questionnaire method of data collection based on Kuppuswamy Socio-economic scale (updated 2018).
Data were entered into MS Excel and analysed using Statistical package for the social sciences-spss-19, IBM, Armonk, Newyork, USA . Descriptive statistics including frequencies and proportions were used to summarise the data.
| Results|| |
A total of 272 clinical specimens were received from treatment naïve/newly diagnosed pulmonary TB patients attending Vydehi Institute of medical Sciences and Research Centre, Bengaluru, from September 2018 to December 2020. Overall, 256 (94%) were sputum specimens, 15 (5.5%) were BAL (Broncho Alveolar Lavage) and 1 (0.4%) was gastric lavage. The study population comprised of 190 (70%) males and 82 (30%) females, resulting in a sex-ratio (men/women) 2.3:1. Median age of the study population was 37 years (range 5–85).
Gene Xpert MTB/RIF assay detected MTB in 193 (71%) samples and RIF resistance in 25 (9%) samples; MTB was not detected in 79 (29%) samples [Table 1]. All of the 272 clinical specimens from presumptive pulmonary TB patients underwent culture on solid LJ media and the culture positive isolates were subjected to drug susceptibility testing (DST) by 1% proportion method. DSTs were performed and drug resistance pattern was determined for 149 isolates with sufficient growth (more than 20 colonies), out of the 155 culture-positive isolates.
|Table 1: GeneXpert Mycobacterium tuberculosis/Rifampicin findings (n=272)|
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Among first-line antibiotics tested, 78/149 (52.3%) isolates were sensitive to all the five antibiotics. 22/149 (14.7%) isolates showed combined resistance to both INH and RIF (MDR), with or without resistance to other first-line drugs. [Figure 2] Mono- RIF resistance was found in 9 (6%) of isolates and mono-INH resistance was found in 4 (2.6%) of isolates. STR and PZA monoresistance was observed in 6 (4%) and 8 (5.3%) of isolates, respectively. None of the isolates showed resistance to EMB. Resistance to an individual drug was highest for RIF (29%), followed by PZA (28%). Least resistance was observed for INH (19%) and STR (17%) [Table 2]. Among all cases enrolled, (272), MDR prevalence was (22/272) 8.0%.
|Figure 2: Mycobacterium tuberculosis isolate showing resistance to rifampicin and isoniazid (multidrug-resistant) by 1% proportion method|
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|Table 2: Drug resistance pattern of Mycobacterium tuberculosis isolates to first line anti-tubercular agents (n=149)|
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The highest number of MDR-TB was found in the age group 41–60 years, 9/22 (41%), followed by 21–40 years of age group, 6/22 (27%). The rate of MDR in males and females were 6.84% and 11%, respectively. The distribution of the socioeconomic status of the MDR patients (Based on Kuppuswamy Socioeconomic scale updated-2018) was also assessed in the present study. Of the 22 MDR patients, 12/22 (55%) were belonging to upper lower (IV) class of the Kuppuswamy Socio-economic scale [Table 3].
|Table 3: Association of sociodemographic characteristics and drug resistance of treatment naïve pulmonary tuberculosis patients|
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GeneXpert was compared with 1% proportion method in detecting RIF resistance. Out of the 149 samples, which were subjected to both GeneXpert and 1% proportion method, resistance to RIF was detected by GeneXpert in 25 cases whereas, 43 isolates showed resistance to RIF by the 1% proportion method (additional 18 cases) [Table 4].
|Table 4: Comparison of GeneXpert and 1% proportion method in detecting rifampicin resistance (n=149)|
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| Discussion|| |
Surveillance of drug resistance in TB must be an inevitable part of TB control program, as drug-resistant TB leads to increased rates of morbidity, mortality and treatment costs for the affected population. The current study was mainly focused on detecting the prevalence of drug resistance in new cases to initiate early treatment and thereby preventing the propagation of drug-resistant mycobacterial strains in the community and also to get information concerning the socio-economic risk factors for acquiring the primary drug resistance.
The present study detected MTB in 193 (71%) samples and RIF resistance (RR) in 25 (9%) samples (25/272) by GeneXpert and MTB was not detected in 79 (29%) samples [Table 1]. The prevalence of RR-TB is found to be less in treatment naïve patients compared to retreatment cases in majority of the studies. Our findings are in line with the studies conducted by Ayalew et al. (9%), Wasihun et al. (8%), Chala and Usmael (3%), Gebretsadik et al. (5%), Angaali et al. (4%), Aricha et al. (3%) and Mulu et al. (4%).
The treatment of drug-resistant TB guided by DST results ensures successful and complete TB treatment thereby reducing the drug-resistant TB burden of a country. The overall prevalence of MDR-TB among new cases of pulmonary TB in the present study was 8% (22/272), which is higher than the expected national average of 3.3%. The prevalence of primary MDR-TB varies in different regions-Sharma et al. (1.1%-New Delhi), Garrido et al. (1.7%-Brazil), Chala and Usmael (1.8%-Ethiopia), Joseph et al. (2%-Kerala), Lobie et al. (2.3%-Ethiopia), Muley et al. (3.6%-Nagpur), Myneedu et al. (4%), Wang et al. (5.7%-China), Welekidan et al. (11.6%-Ethiopia), Jain et al. (13.2%-Lucknow), Banik et al. (20%-Meghalaya), Faye et al. (46.25%-Senegal). Several Indian literatures and literatures from other developing Asian countries has reported wide variation in the prevalence of MDR-TB from study to study. Such variations might be due to the bias in sample collection, differences in methodologies adopted, varied geographical distribution, circulating strain patterns and demographic, ethnic and epidemiological divergences.,
Drug susceptibility testing by 1% proportion method in our study revealed individual drug resistance to RIF in 43 (29%) isolates, PZA in 42 (28%) isolates, INH in 28 (19%) isolates and STR in 25 (17%) isolates. Combined INH and RIF resistance strains were found in 22 (15%) isolates. Seventy-eight (52.3%) isolates were pan sensitive. Monoresistance to RIF, INH, STR and PZA was observed in 9 (6%), 4 (2.6%), 6 (4%) and 8 (5.3%) of isolates, respectively. None of the isolates showed resistance to EMB [Table 2]. Banik et al. observed primary drug resistance to INH at 60%, STR at 30% and RIF, EMB and PZA at 20% each, respectively. The proportion of MDR-TB was 20% in new cases and 3 (30%) of isolates were pan sensitive. Monoresistance was noted only with INH (30%) and PZA (10%).
Data analysis of the relationship between drug resistance and age in the present study showed that the largest number of MDR-TB patients was aged 41–60 years (9/22,41%) [Table 3]. A similar finding was observed in the study by Kumar et al. (40–59 years). Kabir et al. and Adane et al. reported the highest number of MDR-TB in the age group of 21–40 and 25–34 years, respectively. Higher number of MDR-TB was observed in the female (11%) population compared to males (6.84%) in our study. Studies by Wang et al., Faye et al. and Kumar et al. have reported higher rate of primary MDR-TB in female patients compared to males, while Kabir et al. reported a higher number of primary MDR-TB from males. However, Li et al. reported no statistically significant difference of drug resistance prevalence between male and female participants and no difference by age group.
Socio-economic status of the MDR patients in the present study was assessed based on Kuppuswamy Socioeconomic scale updated-2018, after analysing different variables such as occupation, education and monthly income of the individual/family. We found that, 12 out of the 22 MDR patients, 12/22 (55%) were belonging to upper lower (IV) class of the Kuppuswamy Socio-economic scale [Table 3]. As several diseases are directly or indirectly related to socioeconomic status of individual/family, the assessment of the socioeconomic standing is very important in many hospital and community-based studies. Scarce data are available on the association between socioeconomic-status and multi drug resistance. Low socioeconomic background can contribute to the risk of TB and development of drug resistance in both high resource rich and resource poor settings. Poverty, along with crowded and poorly ventilated living spaces and working environments, constitute the direct risk factors for TB and eventually MDR transmission in the community. A study by Gaude et al. from northern Karnataka region observed statistically significant association between illiteracy, manual labourers and low-socioeconomic status for the development of MDR in pulmonary TB patients. However, a prospective cohort study conducted by Odone et al. reported 3-fold increased risk of primary drug resistance in higher socioeconomic status compared to acquired resistance and, conversely, increased risk of acquired resistance in lower socioeconomic status.
RIF resistance detected by genotypic (GeneXpert) method and phenotypic method (1% proportion method) showed some discrepancies in our study. Out of the 149 samples, which were subjected to both GeneXpert and 1% proportion method, genotypic resistance to RIF was observed in 25 cases and phenotypic resistance was observed in 43 isolates (additional 18 cases). Zetola et al. reported a lower sensitivity (80%–90%) for Xpert MTB/RIF assay compared to phenotypic DST in their study. When the Xpert assay results for rifampin resistance were compared against phenotypic DST results, 5 results were discordant. One sample showed resistance to rifampin in the Xpert results but not on phenotypic DST (false-positive Xpert assay result for rifampin resistance). Four samples had genotypic/phenotypic discordant DST results showing resistance to rifampin but negative Xpert assay results for such resistance (false-negative Xpert assay result for rifampin resistance). Folkvardsen et al. reported a lower performance for GeneXpert in samples containing mixed (sensitive and resistant) populations of MTB. GeneXpert require 100s of bacillary load/ml of sample to give a positive result, which may lead to false-negative result by this machine especially in smear negative patients, delaying diagnosis and initiation of treatment, while LJ culture-based DST can grow and detect up to 10 live bacilli/ml. Settings, where diagnostic algorithms prioritise the detection of RIF-resistance will miss INH-resistant and RIF-susceptible TB, leading to false therapy. Hence, the detection of drug-resistant TB by the first test, Xpert MTB/RIF assay, which focus only on RIF resistance, should be always complemented by solid culture-based DST to grasp the drug-resistant profile. DNA sequencing methods for confirming RIF resistant mutations in case of discordant results can be also recommended to tackle this situation. As the epidemiology of TB in a community is determined by the interplay between host factors, organism factors, environmental conditions and socio-economic status of the population, we recommend that, every TB-related study must be accompanied by assessment of socioeconomic risk factors of the population under study. The limitations of our study include: (1) A smaller number of patients studied, (2) DST report was not available for culture negative and contaminated cultures. Although our observations may not be generalisable to the entire country, our results remain important in the current scenario of increasing trend of drug resistance among MTB isolates.
| Conclusion|| |
High prevalence of MDR-TB among treatment naïve pulmonary TB patients was noted in patients belonging to Class IV of Kuppuswamy socioeconomic scale in the present study. In conclusion, the assessment of drug-resistant patterns is pre-requisite in clinically diagnosed or microbiologically confirmed TB patients to formulate appropriate treatment regimen as per the drug sensitivity pattern. Hence, early diagnosis of MDR TB by rapid methods coupled with solid culture-based DST and immediate therapeutic interventions and enhanced surveillance measures are highly recommended for the elimination and eradication of MDR-TB from the community.
The authors would like to thank, the Director and staffs of the National TB Institute, Bangalore for providing training to perform Drug Susceptibility Testing and quality control strain H37Rv.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4]