|Year : 2019 | Volume
| Issue : 4 | Page : 351-358
GeneXpert Mycobacterium tuberculosis/rifampicin assay for molecular epidemiology of rifampicin-Resistant Mycobacterium tuberculosis in an Urban Setting of Banten province, Indonesia
Paulus Mario Christopher1, Cucunawangsih1, Allen Widysanto2
1 Department of Microbiology, Faculty of Medicine, Pelita Harapan University, Tangerang, Banten, Indonesia
2 Department of Respirology, Faculty of Medicine, Pelita Harapan University, Tangerang, Banten, Indonesia
|Date of Submission||03-Sep-2019|
|Date of Acceptance||16-Oct-2019|
|Date of Web Publication||26-Nov-2019|
Paulus Mario Christopher
Jenderal Sudirman Lippo Karawaci Boulevard Road, Tangerang, Banten
Source of Support: None, Conflict of Interest: None
Background: Tuberculosis (TB) is the fourth leading cause of death in Indonesia. In 2017, the World Health Organization (WHO) estimated that only 2% of the TB patients in Indonesia had only been tested with rapid diagnostics at the time of diagnosis, resulting in largely underdetected rifampicin-resistant TB (RR-TB). Utilization of GeneXpert Mycobacterium tuberculosis/rifampicin (MTB/RIF) assay as a point-of-care molecular assay to detect TB and RR-TB and serving its purpose in accordance with the first pillar of the WHO End-TB Strategy. Objective: This study investigated the use of GeneXpert MTB/RIF assay to determine the molecular epidemiology of RR-TB in an urban setting of Indonesia. Methods: All molecular epidemiological and microbiological databases were retrospectively examined from GeneXpert MTB/RIF assay results in Siloam Hospital Lippo Village. The sociodemographic characteristics and results of microbiological examinations consisting of Ziehl–Neelsen staining and GeneXpert MTB/RIF assay were analyzed. Results: During the study period, 600 cases were registered, and GeneXpert MTB/RIF tests were done in which the tests yielded 597 (99.5%) valid results; 62.0% were male and adult of age category; of whom 29 samples (4.9%) were found to be RR-TB, 186 samples (31.2%) were RIF sensitive, and remainders were negative. Conclusions: The results of GeneXpert MTB/RIF to be a fundamental diagnosis of RR-TB and subsequently to notify MDR-TB were satisfying and valuable in this study. This further increased and reinforced TB surveillance and national TB program to finally bring about WHO end-TB strategy one step closer in Indonesia.
Keywords: End-TB Strategy, GeneXpert, MTB/RIF, Indonesia, resistance, rifampicin
|How to cite this article:|
Christopher PM, Cucunawangsih, Widysanto A. GeneXpert Mycobacterium tuberculosis/rifampicin assay for molecular epidemiology of rifampicin-Resistant Mycobacterium tuberculosis in an Urban Setting of Banten province, Indonesia. Int J Mycobacteriol 2019;8:351-8
|How to cite this URL:|
Christopher PM, Cucunawangsih, Widysanto A. GeneXpert Mycobacterium tuberculosis/rifampicin assay for molecular epidemiology of rifampicin-Resistant Mycobacterium tuberculosis in an Urban Setting of Banten province, Indonesia. Int J Mycobacteriol [serial online] 2019 [cited 2019 Dec 9];8:351-8. Available from: http://www.ijmyco.org/text.asp?2019/8/4/351/271469
| Introduction|| |
Tuberculosis (TB) is a communicable disease caused by intracellular bacteria from the genus Mycobacterium with the species of Mycobacterium tuberculosis (MTB) that has caused one of the health burdens in the world, being the tenth leading cause of death worldwide., Globally, in 2017, according to the World Health Organization (WHO), it is estimated that there were 1.3 million deaths from TB among HIV-negative patients with additional 300,000 deaths from TB among HIV-positive people. Nationally, Indonesia ranked number 3 in the 30 high TB burden countries, and is estimated to have mortality of 107,000 among HIV-negative people and 9,400 among HIV-positive people. Most of these deaths could be prevented with early recognition and appropriate treatment.
The recommended core standard treatment of TB constitutes four basic treatment regimens that are known or presumed to be susceptible to rifampicin (RIF), isoniazid (INH), pyrazinamide, and ethambutol. Each of the drugs in the treatment contributes to an important role. RIF and INH allow for short-course regimens with high cure rates, with RIF being arguably the most important drug in the treatment of TB. In 2017, globally, there were an estimated 558,000 new cases of rifampicin-resistant resistant TB (RR-TB), with an estimated 82% having multidrug-resistant-TB (MDR-TB) and nationally, Indonesia contributed 12,000 cases of estimated MDR/RR-TB cases among notified pulmonary TB (PTB) cases, with 2.4% of TB cases with MDR/RR-TB among new cases and 13% among previously treated cases.
Detection of drug(s) resistant TB has been traditionally burdensome requiring lengthy time for cultures, drug susceptibility tests (DSTs), sophisticated biosafety, and laboratory infrastructures. Nevertheless, drug resistant, in particular RR-TB, can be detected rapidly with GeneXpert MTB/RIF assay, which is the newest method endorsed by the WHO able to detect RR-TB in a short period of time with high sensitivity and specificity., In Indonesia, only a few published reports have been published, and data concerning molecular epidemiology of RR/MDR-TB in the province scale were limited nor made readily accessible. This study aimed to use the data from GeneXpert MTB/RIF assay to determine the molecular epidemiology of RR-TB in an urban setting of Banten province, Indonesia.
| Methods|| |
According to the Guidelines for National TB Control (Pedoman Nasional Pengendalian Tuberkulosis) algorithm for diagnosing TB, TB is to be diagnosed essentially with clinical examinations by physicians and sputum or GeneXpert MTB/RIF (Cepheid®) assay test. The study protocol was approved by the Ethics Committee of the Faculty of Medicine, University of Pelita Harapan (Ref: 151/K-LKJ/ETIK/II/2019). Data were anonymized before analysis by de-identifying patient data.
Study design and population
The study was performed in Banten Province, Indonesia. This was a retrospective study enrolling 600 samples which were based on the database of epidemiological data and microbiological data of patients who were tested for RR from the hospital database of all samples processed with the GeneXpert MTB/RIF assay from November 2017, when the utilization of GeneXpert MTB/RIF began, to June 2019. The population of the study included patients who were referred to the Siloam Hospital's microbiological laboratory from out-/inpatient in hospitals in Banten province.
Variable definitions of TB were made adapting from the WHO definitions in terms of anatomical site of TB disease and history of previous treatment: patient registration group.
Diagnosis of TB case was determined by specialists, based on the criteria with a minimum of one out of the three criteria: (1) Signs and symptoms of TB established by physicians; (2) MTB complex identified positively from a clinical specimen for smear examinations of acid–fast bacilli (AFB); and/or (3) by GeneXpert MTB/RIF assay positivity.
A patient with a TB case involving the lung parenchyma. Miliary TB is included as PTB. A patient with PTB and extra PTB (EPTB) should be classified as a case of PTB.
A patient with a TB case involving organs other than the lungs, for example, lymph nodes, abdomen, skin, joints and bones, meninges, and pleura. Diagnosis should be based on strong clinical evidence consistent with active EPTB or at least one specimen with confirmed MTB or histological.
A patient with a TB case who never received treatment for TB, or have taken anti-TB drugs for <1 month, may have positive or negative bacteriological specimens, and may have disease at any anatomical site.
Previously treated patients
A patient with a TB case who have received 1 month or more of anti-TB drugs in the past, may have positive or negative bacteriological specimens, and may have disease at any anatomical site.
A patient with a TB case that does not fit the above definitions, such as patients who do not know whether they have been previously treated, previously treated but with unknown outcome of that previous treatment, and/or who have returned to treatment with smear-negative PTB or bacteriologically negative EPTB.
Bacteriologic examinations and identifications
After registration, the samples were sent to the microbiological laboratory at the Central Laboratory of Siloam Hospitals Lippo Village, which is one of the reference laboratory centers for GeneXpert MTB/RIF assay in Banten Province. All the specimens were done for Ziehl–Neelsen (ZN) staining using the ZN method and GeneXpert MTB/RIF assay following the instruction guide from the company. Sputum AFB smear test results were reported semi-quantitatively and were interpreted using the International Union against Tuberculosis and Lung Disease. Results of GeneXpert MTB/RIF assays were reported and collected qualitatively.
Data collection and analysis
The data collected for the study consisted of (1) sociodemographic characteristics derived from patient's family certificate, consisting of their sex, age, address, education level and job, (2) type of samples for examination, (3) national TB registry form, and/or (4) GeneXpert MTB/RIF test request forms, diagnosis in terms of site of disease, type of patient (new-, previously treated patients, or others). Results of the ZN staining and GeneXpert MTB/RIF test were entered into Excel files. Statistical analysis was performed using SPSS Version 21.0 (IBM Corp., Released 2012, Armonk, NY).
| Results|| |
Characteristics of the study population
During the study period, from the total of 600 samples that were collected and processed, the assay provided valid results in 597 (99.5%) samples and unsuccessful results in 3 (0.5%) samples. Hence, the total number of samples eligible in the research are 597 samples. The sociodemographic aspect of the samples gave results of a mean age (range) of 47.91 (1–90) years and a median of 49 years. Majority of the samples were adult (61.1%) and male (62.0%). Regarding their educational status, most samples had a secondary education (52.6%), with occupational status of the samples predominated by white-collar jobs (34.0%). Anatomically, most samples came from PTB (77.6%) samples, whilst new cases (56.3%) of TB dominated the treatment history group [Table 1].
Outcomes of GeneXpert Mycobacterium tuberculosis/ rifampicin assay tests and microscopy
The GeneXpert MTB/RIF assay test for the detection of MTB was positive in 382 (64.0%) samples and negative in 215 (36.0%) samples; 82.3% of the positive samples were with positive ZN staining and 3.6% of the positive GeneXpert MTB/RIF assay tests were negative on ZN staining [Table 2].
|Table 2: Results of GeneXpert test and Ziehl-Neelsen staining for the detection of Mycobacterium tuberculosis|
Click here to view
Epidemiology rifampicin-resistant Mycobacterium tuberculosis and characteristics of samples
During the study period, the number of samples with RR-TB varied from year to year. Of the 36.0% of cases with a positive GeneXpert MTB/RIF assay test, 4.9% showed RR. The rate of resistance was 0.0% in 2017, 8.6% in 2018, and 1.0% in 2019 [Figure 1].
|Figure 1: Tabulation and Graph of GeneXpert mycobacterium tuberculosis/ rifampicin assay tests, 2017–2019|
Click here to view
Resistance was observed primarily in male (65.5%) and adult age group (69.0%) within Banten area (86.2%) followed by outside and unspecified area (6.9%, respectively). Education status of resistance samples was mostly secondary education (48.3%) with employment status as white-collar jobs (34.5%) as well as unemployed (31.0%) being the top contributors. Majority of the diagnoses were contributed from PTB samples (82.8%) and found most frequently in new cases (48.3%) followed by previously treated (34.5%) and other (17.2%).
| Discussion|| |
This study has identified data of sociodemographic and epidemiology of MTB and RR-TB identification by ZN staining and GeneXpert MTB/RIF assay test. According to the Guidelines for National TB Control (Pedoman Nasional Pengendalian Tuberkulosis) algorithm for diagnosing TB, GeneXpert MTB/RIF assay test will be chosen in terms of accessibility to facilities in health-care facilities or in patients with a history of TB treatment, history of close contact with drug-resistant TB, and/or HIV patients. Nonetheless, the GeneXpert MTB/RIF assay test has been able to provide the diagnosis of TB within a short period of time and was able to provide results that were sufficiently reliable and accurate in terms of sample needed. The GeneXpert MTB/RIF assay test required a minimum of 100 cells/mL sputum compared to ZN staining which required a minimum of 10,000 cells/mL sputum to recognize MTB or to be positive.,, GeneXpert MTB/RIF assay is also recommended by the WHO for its use as a point-of-care molecular assay, indicating that these results can be considered sufficient in the absence of complementary conventional or molecular tests.
Males dominated the study with 62.0%, as seen in other studies,,,,,,,,,, in which sex was found to be statistically not significant as shown also in our study [Table 3].,, Sociodemographic characteristics of age have shown the cases of TB referred for verification were in patients of all ages, likewise elsewhere in regions of Indonesia, ranging from 0 to 65 + years, with the most referred patients belong in the adult age category. This is in line with the trend of rapid aging of the Indonesian population, and similar ranges of TB cases have been reported from various researches and similar results have shown in our study.,,,,,,
|Table 3: Sosiodemographic Characteristic of GeneXpert MTB/RIF Assay Test|
Click here to view
In our study, the urban area was found to be statistically insignificant as evidenced in other studies., The result is contradictory toward other studies in which urban area carries significance in risk of developing RR/MDR-TB for it could be interpreted as urban areas of having better houses – where walls, roofs, and windows are built with more solid materials, are well less ventilated, and therefore increase the risk of within-household transmission.,,, Another possible pathway is increased risk of household crowding because those with better houses may spend more time indoors to socialize.
Occupational/socioeconomic and educational status have mixed evidence from other studies on whether higher socioeconomic and educational status is associated with a reduced or increased trend of TB, notably MDR-TB. In our study, socioeconomic status showed statistically significant association, whereas education did not, as confirmed by different literature in different countries.,,,,,,,, The reason in which the high number of TB cases found in workers, especially white-collar jobs, may lay in the new policy implemented by the Indonesian government through regulation of national health-care insurance which workers are to be enrolled in the health-care insurance effective per 2015, giving better chances in a better healthcare-seeking behaviour among workers. TB percentage in white-collar workers was higher compared to other jobs as supported by studies in India, contradictory to findings in studies, in which other occupational sub-groups (blue-collar or unemployed) was found higher.,,,, Our findings suggest complex and context-specific relationship between socioeconomic factors in a transitioning health system.
Other studies have found association between educational status that were showing correlation,,,, in which low literacy/education level to be significantly associated with TB in areas of education being the prerequisite for improving health and living standards,, high odds of low comprehensive TB knowledge, poor awareness of disease transmission, proper method of sputum disposal and poor income or unemployment effect in a decreasing manner towards health care seeking behaviour and proper care during illness. However, not all TB patients with low educational status equalizes as someone with low knowledge about TB as information about TB medications has been readily available in different types of media, namely television, radio, leaflets in health care facilities.
Numerous studies have reported to show the association between the development of drug resistance and its risk factors,,,,,,,, in which (1) previous treatment has been recognized having significance inducing MDR-TB serving as a powerful predictor for the presence of MDR-TB, (2) the prevalence of MDR-TB has been predicted to be up to 10–21 times higher after unsuccessful treatment, (3) incorrect TB treatment associated with intermittent drug use, errors in medical prescription, poor patient adherence, and low quality of TB drugs, and (4) have diagnostic and treatment delay.,, The resistance could be due to repeated and inappropriate ways of taking the medication or treatment dropout that made the bacteria mutate and develop resistance against the drugs., Patients with nonadherence to treatment may remain infectious, experience increased risk of TB recurrence, TB-related mortality or increased probability of resistance. Thus, prompting adherence to treatment and further shorten the time needed for diagnosis to reduce the chain of infection and resistance. Nevertheless, our study showed that patients with previous TB status did not show association with the development of RR-TB. This could be based on (1) primary transmission of MDR-TB strains is ongoing, (2) the low mutation rate of MTBin vitro but higher in the host in which host genetic predisposition ofin vivo environment that might drive mutagenesis acting as the basis for the development of MDR-TB with spontaneous chromosomally-borne mutation in MTB at predictable rates are thought to confer resistance to anti-TB drugs as the major underlying event,, (3) failure to recognize nontuberculous Mycobacteria causing condition similar of that caused by MTB, and/or (4) our results may be limited by the definition of MDR-TB that combined patients confirmed with culture and DST which detect about 95-98% of MDR-TB compared to those tested with GeneXpert MTB/RIF alone.
The overall prevalence of RR-TB throughout the study was 4.80%, contributing approximately 31.20% compared to the reported national RR/MDR-TB in Indonesia (15.40%) during the year of 2017. The increase in the overall prevalence of detected cases are contributed due to Indonesia advancement in TB surveillance and control by the implementation and achieving better recording of case through nation-wide coverage of the electronic recording and reporting system in National Tuberculosis Program (NTP) facilities,, introduction of mandatory TB notification, establishment of public-public and public-private engagement schemes, improvement of health sector performance and the enforcement of the usage of GeneXpert MTB/RIF assay made available with Regulation of Minister of Health (MoH) issued in 2016., These efforts were based on the high burden of TB in Indonesian society in which annually, TB affects an estimation of 4 million people in the WHO South–East Asia (SEA) Region contributing for 41% of estimated global TB cases with most deaths reported from Bangladesh, India, Indonesia, Myanmar, and Thailand and since 2011, TB has been the primary cause of death from a single infectious agent, topping above HIV/AIDS. This further heightens the alertness for the detection of TB and subsequently drug resistant TB, either RR/MDR-TB or Extensively Drug Resistant TB (XDR-TB), with emphasis of RIF holds its importance as one of the most effect anti-TB drugs due to its effective against actively-and slow-metabolizing bacilli contributing as primary component of the current first-line treatment regimen. In addition, RIF monoresistance is rare as RIF resistance occurs concomitantly with resistance towards other drug, mostly associated with INH, making RIF targets a surrogate marker or proxy for MDR phenotype and the need of accurate drug resistance surveillance data.,,,,, Further understanding of drug resistant TB can be achieved in line for uses to assess and improve NTP, initiating effective therapy as soon as possible, preventing drug resistant TB through accurate determination of patient requiring treatment and follow-up for TB, and leading to eradication of this disease nationwide and worldwide.
Our study has several limitations. First, our findings may not be able to fully representative of Indonesia nor Banten province as data collection was only done in one secondary hospital. Second, we did not perform mycobacterial culture nor DSTs. Thus, we could not estimate the proportion of false positive and negative results of the Xpert assay to diagnose TB or RR-TB compared with the gold standard. Third, rpoB gene sequencing was not done, so we could not establish the specific rpoB mutations nor, therefore, the specificity and sensibility of the assay to detect mutations in the rpoB gene. Lastly, the availability of certain data, such as the mode of TB contact and other characteristics or risk factors was limited due to the retrospective manner and relied on collected data.
To our best knowledge, this is the first study to report on the molecular epidemiology of RR– TB in the province scale in Indonesia. Many patients with RR-TB.
| Conclusions|| |
The risk factor associated for RR/MDR-TB among patients is employment status. Results of GeneXpert MTB/RIF to be a paramount for diagnosis of RR-TB and subsequently to notify MDR-TB were satisfying and valuable in urban setting of Banten province. This further increased and augmented TB surveillance and national TB program to finally bring about WHO End TB Strategy one step closer in Indonesia.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Murray P, Rosenthal K, Pfaller M. Mycobacterium
and related acid-fast Bacteria. In: Medical Microbiology. 8th
ed. Philadelphia: Elsevier; 2013. p. 218-25.
World Health Organization. Case definitions. In: Treatment of Tuberculosis Guideline. 4th
ed. Geneva: World Health Organization; 2010. p. 23-8.
Steingart KR, Schiller I, Horne DJ, Pai M, Boehme CC, Dendukuri N. Xpert® MTB/RIF assay for pulmonary tuberculosis and rifampicin resistance in adults. Cochrane Database Syst Rev 2014;1:CD009593.
Bajrami R, Mulliqi G, Kurti A, Lila G, Raka L. Assessment of diagnostic accuracy of genexpert Mycobacterium tuberculosis
/rifampicin in diagnosis of pulmonary tuberculosis in Kosovo. Biomed Biotechnol Res J 2018;2:191-5. [Full text]
Global Laboratory Initiative Advancing TB Diagnosis. Laboratory Diagnosis of Tuberculosis by Sputum Microscopy. Adelaide: SA Pathology; 2013. p. 31.
Directorate General for Control of Diseases and Environmental Health of Indonesian Ministry of Health. Guidelines for National Tuberculosis Control. Indonesia; 2014.
Dwija Putra IB, Tarini NM, Fatmawati NN, Sri Budayanti NN. MDR-TB di RSUP Sanglah Denpasar Tahun 2014; 2014.
Alisjahbana B, van Crevel R, Danusantoso H, Gartinah T, Soemantri ES, Nelwan RH, et al.
Better patient instruction for sputum sampling can improve microscopic tuberculosis diagnosis. Int J Tuberc Lung Dis 2005;9:814-7.
van Kampen SC, Susanto NH, Simon S, Astiti SD, Chandra R, Burhan E, et al.
Effects of introducing xpert MTB/RIF on diagnosis and treatment of drug-resistant tuberculosis patients in Indonesia: A pre-post intervention study. PLoS One 2015;10:e0123536.
Stosic M, Vukovic D, Babic D, Antonijevic G, Foley KL, Vujcic I, et al.
Risk factors for multidrug-resistant tuberculosis among tuberculosis patients in Serbia: A case-control study. BMC Public Health 2018;18:1114.
Tao N, Li Y, Liu Y, Liu J, Song W, Liu Y, et al.
Epidemiological characteristics of pulmonary tuberculosis among children in Shandong, China, 2005-2017. BMC Infect Dis 2019;19:1-9.
Rohit RT, Niranjan A, Pawan PA. Socio-demographic profile and outcome of TB patients registered at DTC rewa of central India. Indian J Tuberc 2018;65:140-4.
Baya B, Achenbach CJ, Kone B, Toloba Y, Dabitao DK, Diarra B, et al.
Clinical risk factors associated with multidrug-resistant tuberculosis (MDR-TB) in Mali. Int J Infect Dis 2019;81:149-55.
GBD Tuberculosis Collaborators. The global burden of tuberculosis: Results from the global burden of disease study 2015. Lancet Infect Dis 2018;18:261-84.
Soeroto AY, Lestari BW, Santoso P, Chaidir L, Andriyoko B, Alisjahbana B, et al.
Evaluation of xpert MTB-RIF guided diagnosis and treatment of rifampicin-resistant tuberculosis in Indonesia: A retrospective cohort study. PLoS One 2019;14:e0213017.
Rifat M, Hall J, Oldmeadow C, Husain A, Hinderaker SG, Milton AH. Factors related to previous tuberculosis treatment of patients with multidrug-resistant tuberculosis in Bangladesh. BMJ Open 2015;5:e008273.
Rifat M, Milton AH, Hall J, Oldmeadow C, Islam MA, Husain A, et al.
Development of multidrug resistant tuberculosis in Bangladesh: A case-control study on risk factors. PLoS One 2014;9:e105214.
Kementrian Kesehatan Republik Indonesia. The Joint External TB Monitoring Mission (JEMM) TB Indonesia 2017. Kementrian Kesehatan Republik Indonesia; 2017.
N'guessan Kouassi K, Riccardo A, Dutoziet Christian C, André G, Férilaha C, Hortense SA, et al.
Genotyping of mutations detected with geneXpert. Int J Mycobacteriol 2016;5:142-7.
Sajith M, Thomas A, Kothia JJ, Chandrakar B, Bargaje MD. Socio-demographic characteristics of tuberculosis patients in a tertiary care hospital. Int J Med 2015;1:25-8.
Bhawalkar J, Khedkar D, Lanjewar B, Landge J, Ghonge S. Socio-demogrpahic factors associated with tuberculosis cases registered under RNTCP in an urban area of Pune, Maharashtra. Natl J Community Med 2018;9:130-4.
Reviono R, Kusnanto P, Eko V, Pakiding H, Nurwidiasih D. Multidrug Resistant Tuberculosis (MDR-TB): Epidemiological Review and Risk Factor for Side Effect of Anti Tuberculosis Drugs. MKB 2014;46:189-96.
Faustini A, Hall AJ, Perucci CA. Risk factors for multidrug resistant tuberculosis in Europe: A systematic review. Thorax 2006;61:158-63.
Rajeswari R, Balasubramanian R, Muniyandi M, Geetharamani S, Thresa X, Venkatesan P. Socio-economic impact of tuberculosis on patients and family in India. Int J Tuberc Lung Dis 1999;3:869-77.
World Health Organization. Anti-Tuberculosis Drug Resistance Among Tuberculosis Patients in Ukraine and Risk Factors for MDR-TB. World Health Organization; 2016. p. 13-6.
Jiamsakul A, Lee MP, Nguyen KV, Merati TP, Cuong DD, Ditangco R, et al.
Socio-economic status and risk of tuberculosis: A case-control study of HIV-infected patients in Asia. Int J Tuberc Lung Dis 2018;22:179-86.
Khatun UF, Amin R, Islam M, Rob A, Rahim A. Socio-demogrpahic profile and drug sensitivity pattern of suspected drug resistant tuberculosis among patients in regional tuberculosis reference laboratory (R.T.R.L) of a tertiary hospital. J Med 2017;18:62-7.
Pradipta IS, Forsman LD, Bruchfeld J, Hak E, Alffenaar JW. Risk factors of multidrug-resistant tuberculosis: A global systematic review and meta-analysis. J Infect 2018;77:469-78.
Prado TN, Caus AL, Marques M, Maciel EL, Golub JE, Miranda AE. Epidemiological profile of adult patients with tuberculosis and AIDS in the state of Espírito Santo, Brazil: Cross-referencing tuberculosis and AIDS databases. J Bras Pneumol 2011;37:93-9.
Shen X, DeRiemer K, Yuan ZA, Shen M, Xia Z, Gui X, et al.
Drug-resistant tuberculosis in Shanghai, China, 2000-2006: Prevalence, trends and risk factors. Int J Tuberc Lung Dis 2009;13:253-9.
Odone A, Calderon R, Becerra MC, Zhang Z, Contreras CC, Yataco R, et al.
Acquired and transmitted multidrug resistant tuberculosis: The role of social determinants. PLoS One 2016;11:e0146642.
Khan MS, Hutchison C, Coker RJ, Yoong J, Hane KM, Innes AL. Preventing emergence of drug resistant tuberculosis in Myanmar's transitioning health system. Health Policy Plan 2017;32:i43-50.
Duarte R, Lönnroth K, Carvalho C, Lima F, Carvalho ACC, Muñoz-Torrico M, et al.
Tuberculosis, social determinants and co-morbidities (including HIV). Pulmonology 2018;24:115-9.
Johnston JC, Shahidi NC, Sadatsafavi M, Fitzgerald JM. Treatment outcomes of multidrug-resistant tuberculosis: A systematic review and meta-analysis. PLoS One 2009;4:e6914.
Zhao Y, Xu S, Wang L, Chin DP, Wang S, Jiang G, et al.
National survey of drug-resistant tuberculosis in China. N
Engl J Med 2012;366:2161-70.
Workicho A, Kassahun W, Alemseged F. Risk factors for multidrug-resistant tuberculosis among tuberculosis patients: A case-control study. Infect Drug Resist 2017;10:91-6.
Skrahina A, Hurevich H, Zalutskaya A, Sahalchyk E, Astrauko A, Hoffner S, et al.
Multidrug-resistant tuberculosis in Belarus: The size of the problem and associated risk factors. Bull World Health Organ 2013;91:36-45.
Brewer TF, Choi HW, Seas C, Krapp F, Zamudio C, Shah L, et al.
Self-reported risks for multiple-drug resistance among new tuberculosis cases: Implications for drug susceptibility screening and treatment. PLoS One 2011;6:e25861.
Alikhanova N, Akhundova I, Seyfaddinova M, Mammadbayov E, Mirtskulava V, Rüsch-Gerdes S, et al.
First national survey of anti-tuberculosis drug resistance in Azerbaijan and risk factors analysis. Public Health Action 2014;4:S17-23.
Ali MH, Alrasheedy AA, Hassali MA, Kibuule D, Godman B. Predictors of multidrug-resistant tuberculosis (MDR-TB) in Sudan. Antibiotics (Basel) 2019;8. pii: E90.
Mohamed S, Kanagasabapathy S, Kalifulla S. Socio-economic profile and risk factors among pulmonary tuberculosis patients in Madurai, India: A cross sectional study. Int J Res Med Sci 2015;3:3490-8.
Gupta S, Shenoy VP, Mukhopadhyay C, Bairy I, Muralidharan S. Role of risk factors and socio-economic status in pulmonary tuberculosis: A search for the root cause in patients in a tertiary care hospital, South India. Trop Med Int Health 2011;16:74-8.
Kootbodien T, Wilson K, Tlotleng N, Ntlebi V, Made F, Rees D, et al.
Tuberculosis mortality by occupation in South Africa, 2011 - 2015. Int J Environ Res Public Health 2018;15. pii: E2756.
Law WS, Yew WW, Chiu Leung C, Kam KM, Tam CM, Chan CK, et al.
Risk factors for multidrug-resistant tuberculosis in Hong Kong. Int J Tuberc Lung Dis 2008;12:1065-70.
Ivanovs A, Salmane-Kulokovska I, Viksna L. The Impact of socioeconomic factors on tuberculosis prevalence in Latvia. Univers J Public Health 2016;4:230-8.
Senanayake MGB, Wickramasinghe SI, Samaraweera S, De Silva P, Edirippulige S. Examining the social status, risk factors and lifestyle changes of tuberculosis patients in Sri Lanka during the treatment period: A cross-sectional study. Multidiscip Respir Med 2018;13:9.
Ane-Anyangwe I, Fru-Cho J, Ndukum JA, Nota AD, Meriki HD, Nsongomanyi FR, et al
. Socio-demograhic and environmental factors affecting the prevalence and spread of tuberculosis in South West region of Cameroon. Int J Trop Dis Health 2016;18:1-7.
Alemayehu M, Tigabu A, Yunkura S, Hagos F, Tegene B. Prevalence of smear positive pulmonary tuberculosis and associated risk factors among pulmonary tuberculosis suspected patients at private health institutions in Gondar town, Northwest Ethiopia: A cross-sectional study. Am J Infect Dis Microbiol 2017;5:61-5.
Kapoor AK, Singh K. Demogrpahic dynamics in tuberculosis patients of Delhi. Int J Med Health Res Sci 2016;5:43-9.
Miandad M, Nawaz-Ul-Huda S, Burke F, Hamza S, Azam M. Educational status and awareness among tuberculosis patients of Karachi. J Pak Med Assoc 2016;66:265-9.
Gelaw SM. Socioeconomic factors associated with knowledge on tuberculosis among adults in Ethiopia. Tuberc Res Treat 2016;2016:1-11.
Manna N, Giri K, Mundle M. Drug resistance pattern, related socio- demographic factors and preventive practices among MDR-TB patients: An experience form a tertiary care setting. IOSR J Dent Med Sci 2014;13:16-21.
Sarwani D, Nurlaela S, Zahrotul I. Multidrug resistant tuberculosis risk factor. Kemas 2012;8:60-6.
Chuchottaworn C, Thanachartwet V, Sangsayunh P, Than TZ, Sahassananda D, Surabotsophon M, et al.
Risk factors for multidrug-resistant tuberculosis among patients with pulmonary tuberculosis at the central chest institute of Thailand. PLoS One 2015;10:e0139986.
Caminero JA. Multidrug-resistant tuberculosis: Epidemiology, risk factors and case finding. Int J Tuberc Lung Dis 2010;14:382-90.
Liang L, Wu Q, Gao L, Hao Y, Liu C, Xie Y, et al.
Factors contributing to the high prevalence of multidrug-resistant tuberculosis: A study from China. Thorax 2012;67:632-8.
Ormerod LP. Multidrug-resistant tuberculosis (MDR-TB): Epidemiology, prevention and treatment. Br Med Bull 2005;73-74:17-24.
Rumende CM. Risk factors for multidrug-resistant tuberculosis. Acta Med Indones 2018;50:1-2.
Zmak L, Jankovic M, Jankovic VK. Evaluation of xpert MTB/RIF assay for rapid molecular diagnosis of tuberculosis in a two-year period in Croatia. Int J Mycobacteriol 2013;2:179-82. [Full text]
Matteelli A, Roggi A, Carvalho AC. Extensively drug-resistant tuberculosis: Epidemiology and management. Clin Epidemiol 2014;6:111-8.
Narasimhan P, Wood J, Macintyre CR, Mathai D. Risk factors for tuberculosis. Pulm Med 2013;2013:1-11.
Cazabon D, Alsdurf H, Satyanarayana S, Nathavitharana R, Subbaraman R, Daftary A, et al.
Quality of tuberculosis care in high burden countries: The urgent need to address gaps in the care cascade. Int J Infect Dis 2017;56:111-6.
Pedro Hda S, Nardi SM, Pereira MI, Oliveira RS, Suffys PN, Gomes HM. Clinical and epidemiological profiles of individuals with drug-resistant tuberculosis. Mem Inst Oswaldo Cruz 2015;110:235-48.
He XC, Zhang XX, Zhao JN, Liu Y, Yu CB, Yang GR. Epidemiological trends of drug-resistant tuberculosis in China from 2007 to 2014: A retrospective study. Medicine (Baltimore) 2016;95:e3336.
McGrath M, Gey van Pittius NC, van Helden PD, Warren RM, Warner DF. Mutation rate and the emergence of drug resistance in Mycobacterium tuberculosis
. J Antimicrob Chemother 2014;69:292-302.
Maiga M, Siddiqui S, Diallo S, Diarra B, Traoré B, Shea YR. Failure to recognize nontuberculous mycobacteria leads to misdiagnosis of chronic pulmonary tuberculosis. PLoS One 2012;7:e36902.
Surya A, Setyaningsih B, Suryani Nasution H, Gita Parwati C, Yuzwar YE, Osberg M, et al.
Quality tuberculosis care in Indonesia: Using patient pathway analysis to optimize public-private collaboration. J Infect Dis 2017;216:S724-32.
Dookie N, Rambaran S, Padayatchi N, Mahomed S, Naidoo K. Evolution of drug resistance in Mycobacterium tuberculosis
: A review on the molecular determinants of resistance and implications for personalized care. J Antimicrob Chemother 2018;73:1138-51.
Li QJ, Jiao WW, Yin QQ, Xu F, Li JQ, Sun L, et al.
Compensatory mutations of rifampin resistance are associated with transmission of multidrug-resistant Mycobacterium tuberculosis
Beijing genotype strains in China. Antimicrob Agents Chemother 2016;60:2807-12.
Guled AY, Elmi AH, Abdi BM, Rage AM, Ali FM, Abdinur AH, et al
. Prevalence of rifampicin resistance and associated risk factors among suspected multidrug resitant tuberculosis cases in TB centers Mogadishu-Somalia: Descriptive study. Open J Respir Dis 2016;6:15-24.
Kurbatova EV, Cavanaugh JS, Shah NS, Wright A, Kim H, Metchock B. Rifampicin-resistant Mycobacterium tuberculosis
: Susceptibility to isoniazid and other anti-tuberculosis drugs. Int J Tuberc Lung Dis 2012;16:355-7.
Huang H, Zhang Y, Li S, Wang J, Chen J, Pan Z, et al.
Rifampicin resistance and multidrug-resistant tuberculosis detection using xpert MTB/RIF in Wuhan, China: A retrospective study. Microb Drug Resist 2018;24:675-9.
Cohn DL, Bustreo F, Raviglione MC. Drug-resistant tuberculosis: Review of the worldwide situation and the WHO/IUATLD global surveillance project. International union against tuberculosis and lung disease. Clin Infect Dis 1997;24 Suppl 1:S121-30.
Minion J, Gallant V, Wolfe J, Jamieson F, Long R. Multidrug and extensively drug-resistant tuberculosis in Canada 1997-2008: Demographic and disease characteristics. PLoS One 2013;8:e53466.
[Table 1], [Table 2], [Table 3]