Journal Information
Vol. 58. Issue 12.
Pages 809-820 (December 2022)
Share
Share
Download PDF
More article options
Visits
3228
Vol. 58. Issue 12.
Pages 809-820 (December 2022)
Original Article
Full text access
Rapid Diagnosis of XDR and Pre-XDR TB: A Systematic Review of Available Tools
Visits
3228
Laura Saderia, Mariangela Pucia, Biagio Di Lorenzoa, Rosella Centisb, Lia D’Ambrosioc, Onno W. Akkermand,e, Jan-Willem C. Alffenaarf,g,h, José A. Camineroi,j, Jeremiah Muhwa Chakayak,l, Justin T. Denholmm, Xhevat Kurhasanin, Catherine W.M. Ongo,p,q, Adrian Rendonr, Denise Rossato Silvas, Simon Tiberit, Dominik Zenneru, Andrea M. Cabibbev, Giovanni Battista Migliorib,
Corresponding author
, Giovanni Sotgiua
a Department of Medicine, Surgery and Pharmacy, University of Sassari, Sassari, Italy
b Respiratory Diseases Clinical Epidemiology Unit, Istituti Clinici Scientifici Maugeri, IRCCS, Tradate, Italy
c Public Health Consulting Group, Lugano, Switzerland
d University of Groningen, University Medical Center Groningen, Department of Pulmonary Diseases and Tuberculosis, Groningen, The Netherlands
e University of Groningen, University Medical Center Groningen, TB Center Beatrixoord, Haren, The Netherlands
f Sydney Institute for Infectious Diseases, University of Sydney, Sydney, NSW, Australia
g School of Pharmacy, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
h Westmead Hospital, Sydney, NSW, Australia
i Pneumology Department, Universitary Hospital of Gran Canaria “Dr. Negrin”, Las Palmas de Gran Canaria, Spain
j ALOSA TB Academy, Las Palmas de Gran Canaria, Spain
k Department of Medicine, Therapeutics and Dermatology, Kenyatta University, Nairobi, Kenya
l Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
m Victorian Tuberculosis Program, Melbourne Health and Department of Infectious Diseases, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Parkville, Victoria, Australia
n UBT Higher Education Institution, Prishtina, Kosovo
o Infectious Diseases Translational Research Programme, Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
p Division of Infectious Diseases, Department of Medicine, National University Hospital of Singapore, Singapore
q Institute for Health Innovation and Technology (iHealthtech), National University of Singapore, Singapore
r Centro de Investigación, Prevención y Tratamiento de Infecciones Respiratorias CIPTIR, Hospital Universitario “Dr. Jose Eleuterio Gonzalez”, Universidad Autónoma de Nuevo León, Monterrey, Mexico
s Faculdade de Medicina, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
t Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
u Global Public Health Unit, Wolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
v Emerging Bacterial Pathogens Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
Ver más
This item has received
Article information
Abstract
Full Text
Bibliography
Download PDF
Statistics
Figures (6)
Show moreShow less
Tables (3)
Table 1. Summary of the included studies.
Table 2. Diagnostic performance indicators of the Xpert MTB/XDR test.
Table 3. Summary of the main indicators of diagnostic accuracy of the selected molecular techniques.
Show moreShow less
Additional material (1)
Abstract
Introduction

No previous systematic reviews have comprehensively investigated the features of Xpert MTB/XDR and other rapid tests to diagnose pre-XDR/XDR-TB. The aim of this systematic review is to assess existing rapid diagnostics for pre-XDR/XDR-TB from a point-of-care perspective and describe their technical characteristics (i.e., sensitivity, specificity, positive and negative predictive values).

Methods

Embase, PubMed, Scopus, and Web of Science were searched to detect the articles focused on the accuracy of commercially available rapid molecular diagnostic tests for XDR-TB according to PRISMA guidelines. The analysis compared the diagnostic techniques and approaches in terms of sensitivity, specificity, laboratory complexity, time to confirmed diagnosis.

Results

Of 1298 records identified, after valuating article titles and abstracts, 97 (7.5%) records underwent full-text evaluation and 38 records met the inclusion criteria.

Two rapid World Health Organization (WHO)-endorsed tests are available: Xpert MTB/XDR and GenoType MTBDRsl (VER1.0 and VER 2.0). Both tests had similar performance, slightly favouring Xpert, although only 2 studies were available (sensitivity 91.4–94; specificity 98.5–99; accuracy 97.2–97.7; PPV 88.9–99.1; NPV 95.8–98.9).

Conclusions

Xpert MTB/XDR could be suggested at near-point-of-care settings to be used primarily as a follow-on test for laboratory-confirmed TB, complementing existing rapid tests detecting at least rifampicin-resistance.

Both Xpert MTB/XDR and GenoType MTBDRsl are presently diagnosing what WHO defined, in 2021, as pre-XDR-TB.

Keywords:
Tuberculosis
MDR-TB
XDR-TB
Pre-XDR
Drug susceptibility test
Xpert MTB/XDR
GenoType MTBDRsl
Line probe assay
Sensitivity
Specificity
Full Text
Introduction

The appearance of drug-resistance has followed in the wake of extensive programmatic use of anti-tuberculosis (TB) drugs.1 The increasing problem of drug resistance poses different levels of diagnostic challenge: to identify the presence of drug resistance, define the extent of resistance present; and support the design of an effective anti-TB regimen.2

Defining the drug resistance profile and its severity. The appearance of strains of Mycobacterium tuberculosis resistant to both isoniazid and rifampicin, the two core anti-TB drugs, has defined multidrug-resistant tuberculosis (MDR-TB) from the outset. Later in 2006, when more resistant forms of TB appeared, the definition of extensively drug-resistant tuberculosis (XDR-TB) was agreed, referring to MDR-TB strains of M. tuberculosis with additional resistance to any fluoroquinolone and at least one of the three injectable anti-TB drugs (capreomycin, kanamycin and amikacin). The XDR-TB definition was made on the assumption that these classes of drugs were essential to successfully treat a patient with MDR-TB.3–5

More recent evidence demonstrated that XDR-TB patients had worse outcomes than MDR-TB patients with susceptibility to these drugs (those with resistance to fluoroquinolones faring worse than those resistant to injectables).6 The scientific community also considered codification of patterns of resistance beyond XDR7 and the possibility of defining so-called “total drug-resistance”, although no agreement was found on this.8,9

Although not formally recognized by the World Health Organization (WHO), clinicians widely adopted the term pre-XDR to indicate MDR-TB patients with additional resistance to either fluoroquinolones or injectables.9,10

In 2021 WHO introduced the definition pre-XDR-TB (e.g., MDR-TB plus resistance to fluoroquinolones) and modified the definition of XDR-TB, now being MDR-TB plus additional resistance to any fluoroquinolone and at least one WHO Group A drug (bedaquiline, linezolid).5,11,12

Diagnosing and treating pre- and XDR-TB. Considering the difficulty of treating XDR-TB, typically with costly and often toxic second-line anti-TB drugs, the importance of achieving rapid and effective diagnosis to design an effective regimen is obvious.

Of the 4.8 million people diagnosed with pulmonary TB worldwide in 2020, only 59% were bacteriologically confirmed and 71% of them were tested for rifampicin resistance. Notably, a WHO-recommended rapid molecular test was used as the initial diagnostic test for only 33% of new TB diagnoses, contributing to reasons why only about one third of the 157,903 MDR/rifampicin-resistant TB cases detected in 2020 had access to treatment.12

In a recent rapid communication,13,14 WHO recommended the use of shorter regimens on a programmatic basis. The pivotal initial tests which are used globally to classify patients as drug-susceptible or drug-resistant are the Xpert MTB/RIF and Xpert MTB/RIF Ultra, which allow detection of resistance to rifampicin only, and other new low-complexity molecular assays (Truenat MTB-RIF Dx) or moderate complexity nucleic acid amplification tests (NAATs) systems (Abbott Molecular RealTime MTB RIF/INH; Becton Dickinson BD MAX MDR-TB; Bruker-Hain Diagnostics FluoroType MTBDR; Roche Diagnostics Cobas MTB-RIF/INH) have been recently conditionally recommended as well.15 As the shorter MDR/RR-TB regimens are based on WHO Group A drugs, and no rapid WHO-approved tests are available for bedaquiline and linezolid, it is crucial that at least resistance to fluoroquinolones is rapidly detected, together with resistance to isoniazid.16 In case longer regimens are used, rapid detection of resistance to other drugs could be important (e.g., to injectables and ethionamide). Xpert MTB/XDR (isoniazid, ethionamide, fluoroquinolones, amikacin, capreomycin and kanamycin), first-line Line Probe Assays (LPAs; rifampicin and isoniazid) and second-line LPAs (fluoroquinolones, amikacin, capreomycin and kanamycin), plus other moderate complexity automated NAATs and high complexity reverse hybridization-based NAATs (Nipro Genoscholar PZA-TB) are the follow on rapid diagnostic tests currently recommended for the detection of additional drug-resistance beyond rifampicin.15,17

Despite advances, treatment success of MDR-TB remains low (globally at 59%); being lower for pre-XDR and XDR-TB patients and higher in settings where all oral regimens including new drugs are used.12,18,19 Improving treatment success will require access to rapid diagnostic tests able to reliably detect and classify drug resistance, and inform clinicians designing individual regimens.20

In 2021–2022 a Cochrane Review21,22 investigated the efficacy of Xpert MTB/XDR to rapidly detect resistance to isoniazid, fluoroquinolones, ethionamide, and amikacin (but not to the other injectable drugs kanamycin and capreomycin). However, no previous systematic reviews have comprehensively investigated the features of tests available to diagnose pre-XDR/XDR-TB. The aim of this systematic review is to assess all the tools able to rapidly diagnose pre-XDR/XDR-TB (including LPAs, and the Xpert XDR assay) under a point-of-care perspective and describe their technical characteristics (i.e., sensitivity, specificity, positive and negative predictive values).

MethodsSearch strategy

Four electronic search engines repositories (i.e., Embase, PubMed, Scopus, and Web of Science) were searched for the detection of articles focused on the accuracy of rapid molecular diagnostic tests in the diagnosis of extensively drug-resistant tuberculosis (XDR-TB) cases.

The following keywords, combined in different strings, depending on the electronic database, were used to search articles published until February 2022: “Xpert MTB/XDR”, “drug susceptibility test”, “XDR-TB”, “sensitivity”, “specificity”, “tuberculosis”, “TB”, “Mycobacteriumtuberculosis”, “GenoType MTBDRsl”, and “line probe assay (LPA)”.

Reports published in the grey literature or in the social and conventional media were excluded following the risk of unreliable and poor scientific information on the adopted methodology. Reports that were not written in English language were excluded.

Study selection

Only manuscripts describing the diagnostic accuracy of Xpert MTB/XDR compared to the drug susceptibility test (DST) were initially included.

All the studies with an experimental and observational design were selected with the exclusion of editorials, narrative reviews, case-reports or -series, laboratory studies, letters, study protocols, or correspondences.

Titles and abstracts were screened to evaluate the suitability of the manuscripts based on the above-mentioned inclusion and exclusion criteria.

The first assessment, carried out by two investigators (BDL and MVP), was supervised by a third investigator (GS). Full-texts were independently assessed by the same investigators and potential disagreement in the article selection process was resolved by consensus of the third investigator.

Study quality assessment

This study was conducted and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines.23

The Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) checklist was used to evaluate the methodological quality and applicability of the included studies.24 The following items were assessed: patient selection methods; index text description, conduction, and interpretation; reference standard (standard gold test) description, conduction, and interpretation.

Statistical analysis

Descriptive statistics were used to summarize data. Meta-analytic estimates were computed and described with pooled and heterogeneity indicators. Forest plots were used to represent study variability with 95% confidence intervals (CI) for prevalence of drug resistance and for diagnostic accuracy of molecular techniques in the resistance identification. To assess the heterogeneity among studies the inconsistency indicator (I2) was calculated, where an I2 value>50% indicated substantial heterogeneity. Thus, fixed- and random-effects models were computed keeping into consideration the expected between-study heterogeneity. Bias assessment plots and Egger weighted regression test methods were used to assess the publication bias. A two-tailed p-value less than 0.05 was considered statistically significant. Data analyses were performed with the statistical softwares StatsDirect version 3.1.12 (StatsDirect Ltd.) and STATA version 17 (StatsCorp, College Station, Texas, USA).

ResultsStudy characteristics

The search strategy identified 1298 records. After the evaluation of article titles and abstracts, 97 (7.5%) records underwent to the full-text evaluation. 3825–62 records met the inclusion criteria, whereas 59 (60.8%) were excluded for the following reasons: no technical data available (n=22), other detection tests (n=15), other topics (n=10), no XDR-TB isolates/samples included (n=5), sample size<10 (n=2), laboratory research (n=2), only abstract available (n=2), and only research protocol description (n=1) (Fig. 1).

Fig. 1.

PRISMA 2020 flow diagram for new systematic reviews which included searches of databases.

(0.5MB).

Publication year ranged from 200962 to 202225 (Table 1). All the included studies had an observational design, and the minority were multicentric (8, 21.1%).25,28,30,32,42,43,47,48 The patient recruitment period ranged from 199254 to 2020,25 with a sample size ranging from 1753 to 264949 (Table 1). Following the list of WHO regions,63 20 reference centres enrolled patients from the European region,25,28,41,42,44,47–49,52,54,55,57,59,62 10 from the Western Pacific Region,28,32,34,36,38,45,46,51,60,61 8 from the African Region,25,30,39,40,43,48,56,58 6 from the South-East Asian Region,25,29,31,33,35,48,53 3 from the Eastern Mediterranean Region,26,27,37 3 from the Region of the Americas.28,50

Table 1.

Summary of the included studies.

First author  Title  Year  Country  Mono-/multi-centre study  Study period  Sample size, n 
Penn-Nicholson A  Detection of isoniazid, fluoroquinolone, ethionamide, amikacin, kanamycin, and capreomycin resistance by the Xpert MTB/XDR assay: a cross-sectional multicentre diagnostic accuracy study  2022  India, Moldova, South Africa  Multicenter  Jul 2019–Mar 2020  611 
Kardan-Yamchi J  Assessment of the GenoType MTBDRsl VER 2.0 compared to the phenotypic drug susceptibility testing and whole genome sequencing for the rapid detection of resistance to fluoroquinolone and second-line injectable drugs among rifampicin-resistant Mycobacterium tuberculosis isolates  2021  Iran  Monocenter    35 
Bouzouita I  Performance of the GenoType MTBDRsl V 2.0 for detecting second-line drugs resistance of Mycobacterium tuberculosis isolates in Tunisia  2021  Tunisia  Monocenter  May 2015–Dec 2019  103 
Cao Y  Xpert MTB/XDR: a 10-Colour Reflex Assay Suitable for Point-of-Care Settings To Detect Isoniazid, Fluoroquinolone, and Second-Line-Injectable-Drug Resistance Directly from Mycobacterium tuberculosis-Positive Sputum  2021  US, Georgia, Moldova, Peru, Vietnam, Italy  Multicenter    314 
Singh K  Direct detection of resistance to fluoroquinolones/SLIDs in sputum specimen by GenoType MTBDRsl v.2.0 assay A study from Eastern Uttar Pradesh, India  2021  India  Monocenter  Jan 2019–Dec 2019  225 
Ejo M  Effectiveness of GenoType MTBDRsl in excluding TB drug resistance in a clinical trial  2021  Africa  Multicenter  Jul 2012–Jun 2015  413 
Chandak RJ  Evaluation of MTBDRsl for detecting resistance in Mycobacterium tuberculosis to second-line drugs  2019  India  Monocenter    205 
Gao Y  Multi-centre evaluation of GenoType MTBDRsl line probe assay for rapid detection of pre-XDR and XDR Mycobacterium tuberculosis in China  2018  Province of China  Multicenter  2015–2017  353 
Rufai SB  Association of gyrA and rrs gene mutations detected by MTBDRsl V1 on Mycobacterium tuberculosis strains of diverse genetic background from India  2018  India  Monocenter    359 
Jian J  Evaluation of the GenoType MTBDRplus and MTBDRsl for the detection of drug-resistant Mycobacterium tuberculosis on isolates from Beijing, China  2018  China  Monocenter  2015–2016  96 
Yadav R  Diagnostic accuracy of GenoType(®) MTBDRsl VER 2.0 in detecting second-line drug resistance to M. tuberculosis  2018  India  Monocenter    415 
Zeng X  Performance of the MTBDRsl Line probe assay for rapid detection of resistance to second-line anti-tuberculosis drugs and ethambutol in China  2017  China  Monocenter    162 
Ennassiri W  Extensively drug-resistant tuberculosis (XDR-TB) in Morocco  2017  Morocco  Monocenter  2015  155 
Lee YS  Performance of the GenoType MTBDRsl assay for the detection second-line anti-tuberculosis drug resistance  2017  South Korea  Monocenter  Dec 2011–Feb 2017  107 
Gardee Y  Evaluation of the GenoType MTBDRsl Version 2.0 Assay for Second-Line Drug Resistance Detection of Mycobacterium tuberculosis Isolates in South Africa  2017  South Africa  Monocenter  2012–2014  268 
Maningi NE  Comparison of line probe assay to BACTEC MGIT 960 system for susceptibility testing of first and second-line anti-tuberculosis drugs in a referral laboratory in South Africa  2017  South Africa  Monocenter  Jan 2014–Jun 2014  97 
Tekin K  Evaluation of the BACTEC MGIT 960 SL DST Kit and the GenoType MTBDRsl Test for Detecting Extensively Drug-resistant Tuberculosis Cases  2017  Turkey  Monocenter    46 
Bang D  Performance of the GenoType MTBDRplus assay (v2.0) and a new extended GenoType MTBDRsl assay (v2.0) for the molecular detection of multi- and extensively drug-resistant Mycobacterium tuberculosis on isolates primarily from Lithuania  2016  Lithuania, Denmark  Multicenter  2009–2010  43 
Tomasicchio M  The diagnostic accuracy of the MTBDRplus and MTBDRsl assays for drug-resistant TB detection when performed on sputum and culture isolates  2016  South Africa  Multicenter    234 
Brossier F  Performance of the New Version (v2.0) of the GenoType MTBDRsl Test for Detection of Resistance to Second-Line Drugs in Multidrug-Resistant Mycobacterium tuberculosis Complex Strains  2016  France  Monocenter  2005–2015  127 
Lu W  Evaluation of MTBDRplus and MTBDRsl in Detecting Drug-Resistant Tuberculosis in a Chinese Population  2016  China  Monocenter  May 2008–Dec 2008  99 
Jeong HY  Evaluation of the GenoType® MTBDRsl assay in Korean patients with MDR or XDR tuberculosis  2016  Korea  Monocenter  Apr 2008–Jun 2008  40 
Tagliani E  Diagnostic Performance of the New Version (v2.0) of GenoType MTBDRsl Assay for Detection of Resistance to Fluoroquinolones and Second-Line Injectable Drugs: a Multicenter Study  2015  Italy, Sweden, Germany, Moldova  Multicenter  2009–2013  459 
Catanzaro A  Performance Comparison of Three Rapid Tests for the Diagnosis of Drug-Resistant Tuberculosis  2015  India, Moldova, South Africa  Multicenter    914 
Simons SO  Molecular drug susceptibility testing in the Netherlands: performance of the MTBDRplus and MTBDRsl assays  2015  Netherlands  Monocenter  2007–2012  2649 
Tukvadze N  Performance of the MTBDRsl assay in Georgia  2014  Georgia (USA)  Monocenter  Nov 2011–Apr 2012  138 
Jin J  Underestimation of the resistance of Mycobacterium tuberculosis to second-line drugs by the new GenoType MTBDRsl test  2013  China  Monocenter  2006–2009  261 
Kontsevaya I  Diagnostic accuracy of the genotype MTBDRsl assay for rapid diagnosis of extensively drug-resistant tuberculosis in HIV-coinfected patients  2013  Russian  Monocenter  2008–2010  90 
Singh AK  Rapid detection of drug resistance and mutational patterns of extensively drug-resistant strains by a novel GenoType® MTBDRsl assay  2013  India  Monocenter  Jan 2011–Aug 2012  17 
Lopez-Roa P  Susceptibility testing to second-line drugs and ethambutol by GenoType MTBDRsl and Bactec MGIT 960 comparing with agar proportion method  2012  Spain  Monocenter  1992–2010  26 
Lacoma A  GenoType MTBDRsl for molecular detection of second-line-drug and ethambutol resistance in Mycobacterium tuberculosis strains and clinical samples  2012  Spain  Monocenter    88 
Barnard M  Genotype MTBDRsl line probe assay shortens time to diagnosis of extensively drug-resistant tuberculosis in a high-throughput diagnostic laboratory  2012  South Africa  Monocenter  Mar 2010–Sep 2011  516 
Miotto P  GenoType MTBDRsl performance on clinical samples with diverse genetic background  2012  Italy  Monocenter    234 
Said HM  Evaluation of the GenoType® MTBDRsl assay for susceptibility testing of second-line anti-tuberculosis drugs  2012  South Africa  Monocenter    336 
Zivanovic I  Detection of drug-resistant Mycobacterium tuberculosis strains isolated in Serbia by the genotype MTBDRsl assay  2012  Serbia  Monocenter  2011  19 
Huang WL  Performance assessment of the GenoType MTBDRsl test and DNA sequencing for detection of second-line and ethambutol drug resistance among patients infected with multidrug-resistant Mycobacterium tuberculosis  2011  Taiwan  Monocenter  Jan 2008–Feb 2009  234 
Kiet VS  Evaluation of the MTBDRsl test for detection of second-line-drug resistance in Mycobacterium tuberculosis  2010  Vietnam  Monocenter  Jan 2005–Jul 2006  62 
Hillemann D  Feasibility of the GenoType MTBDRsl assay for fluoroquinolone, amikacin-capreomycin, and ethambutol resistance testing of Mycobacterium tuberculosis strains and clinical specimens  2009  Germany  Monocenter    170 

Among the included studies, two (5.3%),25,28 10 (26.3%),26,29,34,35,39,40,42,47,48,54 and 26 (68.4%)30–33,35–38,41,43–46,49–57,59–62 articles described the application of Xpert MTB/XDR, GenoType MTBDRsl VER 2.0, and GenoType MTBDRsl VER 1.0, respectively, for the detection of XDR-TB in strains or clinical isolates in comparison with the DST. The definition of XDR-TB used in the evaluated studies was the 2006 one.64

Resistance patterns

The overall pooled prevalence of XDR-TB pattern estimated by the DST was assessed in 28 (73.7%) studies26,27,29,32–52,56,58,59,61 and was 15% (95% CI=11–20; I2=95.6%). The pooled prevalence of resistance was higher for fluoroquinolones (FQ) (34%; 95% CI=27–41; I2=97.6%), followed by kanamycin (KAN) (28%; 95% CI=21–36; I2=97%), amikacin (AMK) (18%; 95% CI=14–23; I2=93.6%), and capreomycin (CM) (17%; 95% CI=13–21; I2=92%) (Fig. 2).

Fig. 2.

Forest plots of pooled prevalence of XDR-TB detection (A), and for resistance to FQ (B), KAN (C), AMK (D), and CM (E). The point estimates of prevalence from each study are indicated as a square and a 95% confidence interval is shown with a horizontal line; the yellow diamond is representative for the combined prevalence.

(0.53MB).
Xpert MTB/XDR

Two studies evaluated the diagnostic accuracy of the Xpert MTB/XDR test.25,28 Both assessed the resistance genes to FQ, KAN, AMK, and CM. Cao and colleagues estimated a sensitivity of 91.4%, 98.1%, 91.0%, and 70.0% for FQ, KAN, AMK, CM, respectively, whereas Penn-Nicholson and colleagues assessed a sensitivity of 94.0%, 86.0%, 73.0%, and 61.0% for FQ, KAN, AMK, CM (Table 2). Specificity and the other diagnostic characteristics for Xpert MTB/XDR were included in Table 2.

Table 2.

Diagnostic performance indicators of the Xpert MTB/XDR test.

Study  TP  FP  FN  TN  Sensitivity, %  Specificity, %  Accuracy, %  PPV, %  NPV, % 
Fluoroquinolones
Penn-Nicholson A, 2022  222  13  295  94.0  99.0  97.2  99.1  95.8 
Cao Y, 2021  32  266  91.4  98.5  97.7  88.9  98.9 
Kanamycin
Penn-Nicholson A, 2022  181  29  300  86.0  98.0  93.4  97.3  91.2 
Cao Y, 2021  101  197  98.1  97.4  97.4  94.4  99.0 
Amikacin
Penn-Nicholson A, 2022  60  22  427  73.0  100.0  95.3  96.8  95.1 
Cao Y, 2021  20  278  91.0  98.9  98.3  87.0  99.3 
Capreomycin
Penn-Nicholson A, 2022  53  34  425  61.0  100.0  93.2  98.1  92.6 
Cao Y, 2021  14  284  70.0  99.7  97.7  93.3  97.9 
GenoType MTBDRsl VER 2.0

The pooled proportion of diagnostic sensitivity and specificity of GenoType MTBDRsl VER 2.0 in detecting XDR-TB were evaluated by 9 out of 10 (90%) studies,26,27,29,34,35,39,40,42,47 and were 85% (95% CI=72–94; I2=75.6%) and 98% (95% CI=95–100; I2=88.3%), respectively (Figs. 3 and 4).

Fig. 3.

Forest plots of pooled sensitivity of XDR-TB detection (A), and for resistance to FQ (B), KAN (C), AMK (D), and CM (E) of GenoType MTBDRsl VER 2.0. The point estimates of sensitivity from each study are indicated as a square and a 95% confidence interval is shown with a horizontal line; the yellow diamond is representative for the combined sensitivity.

(0.29MB).
Fig. 4.

Forest plots of pooled specificity of XDR-TB detection (A), and for resistance to FQ (B), KAN (C), AMK (D), and CM (E) of GenoType MTBDRsl VER 2.0. The point estimates of specificity from each study are indicated as a square and a 95% confidence interval is shown with a horizontal line; the yellow diamond is representative for the combined specificity.

(0.3MB).

The pooled sensitivity and specificity for FQ resistance were high, reaching 95% (95% CI=91–98; I2=81.4%) and 98% (95% CI=97–99; I2=55.1%). When the test was used for the detection of second line injectable drugs (SLIDs), the pooled sensitivity and specificity estimates were: 89% (95% CI=72–99; I2=92.1%) and 98% (95% CI=96–100; I2=83.9%) for KAN; 90% (95% CI=84–95; I2=0%) and 100% (95% CI=98–100; I2=62.2%) for AMK; and 89% (95% CI=76–97; I2=73%) and 99% (95% CI=97–100; I2=77.4%) for CM. The diagnostic variables, including accuracy, PPV, and NPV, for XDR-TB detection and for resistance to FQ, KAN, AMK, and CM were described in Table S1.

GenoType MTBDRsl VER 1.0

The GenoType MTBDRsl VER 1.0 showed a pooled sensitivity and specificity for XDR-TB detection of 75% (95% CI=56–90; I2=91.5%) and 99% (95% CI=99–100; I2=21.7%), respectively, based on the evaluation of 11 studies.31–33,36,41,43,44,46,49,50,52 The pooled proportions of diagnostic sensitivity for resistance to FQ, KAN, AMK, and CM were 84% (95% CI=79–88; I2=80%), 64% (95% CI=46–80; I2=94%), 87% (95% CI=79–94; I2=79.9%), and 73% (95% CI=59–85; I2=85%), respectively. Furthermore, the pooled specificity for resistance to all tested drugs was higher than 95%: 98% (95% CI=97–99; I2=69%), 99% (95% CI=98–99; I2=8.6%), 99% (95% CI=99–100; I2=26.2%), and 97% (95% CI=94–99; I2=82.6%) for resistance to FQ, KAN, AMK, and CM, respectively (Figs. 5 and 6). Additional diagnostic performance variables of GenoType MTBDRsl VER 1.0 were summarized in Table S2.

Fig. 5.

Forest plots of pooled sensitivity of XDR-TB detection (A), and for resistance to FQ (B), KAN (C), AMK (D), and CM (E) of GenoType MTBDRsl VER 1.0. The point estimates of sensitivity from each study are indicated as a square and a 95% confidence interval is shown with a horizontal line; the yellow diamond is representative for the combined sensitivity.

(0.42MB).
Fig. 6.

Forest plots of pooled specificity of XDR-TB detection (A), and for resistance to FQ (B), KAN (C), AMK (D), and CM (E) of GenoType MTBDRsl VER 1.0. The point estimates of specificity from each study are indicated as a square and a 95% confidence interval is shown with a horizontal line; the yellow diamond is representative for the combined specificity.

(0.38MB).
Quality assessment for the included studies

The quality of included studies was assessed using the QUADAS-2 tool.24 Within the patient selection domain, 7 (18.4%) and 8 (21.1%) studies were evaluated as at high and unclear risk of bias, respectively. A high risk of bias was found in 4 studies in relation to the index and reference standard test domains (blinding evaluation). Moreover, 65.8% of the selected studies did not clarify if index test results were interpreted without previous knowledge of the reference standard results. All studies included a reference standard and were judged to have a low risk of bias in the flow and timing domains. No concerns emerged on the applicability of the study domains (Fig. S1).

Discussion

The aim of our study was to assess all the tools able to rapidly diagnose pre-XDR/XDR-TB (and describe their technical characteristics), as well as to compare the diagnostic techniques and approaches in terms of sensitivity, specificity, laboratory complexity, time to confirmed diagnosis (Table 3).

Table 3.

Summary of the main indicators of diagnostic accuracy of the selected molecular techniques.

  Xpert MTB/XDRGenoType MTBDRsl VER 2.0GenoType MTBDRsl VER 1.0
  XDR  FQ  KAN  AMK  CM  XDR  FQ  KAN  AMK  CM  XDR  FQ  KAN  AMK  CM 
Sensitivity (%)  –  94.0 91.4  86.0 98.1  73.0 91.0  61.0 70.0  85.0  95.0  89.0  90.0  89.0  75.0  84.0  64.0  87.0  73.0 
Specificity (%)  –  99.0 98.5  98.0 97.4  100.0 98.9  100.0 99.7  98.0  98.0  98.0  100.0  99.0  99.0  98.0  99.0  99.0  97.0 

The results of our study demonstrated that two rapid WHO-endorsed tests are available for these purposes, namely the Xpert MTB/XDR and GenoType MTBDRsl (VER1.0 and VER 2.0).

Xpert MTB/XDR test is a rapid, automated NAAT test at low complexity.21,22 It does not require any sophisticated laboratory infrastructure. The molecular amplification of small quantity of genetic materials takes place inside the cartridge and require less than 2h to provide results. The main advantages over the LPAs are the higher sensitivity for detecting Mycobacterium tuberculosis (it is also recommended in persons with a sputum smear-negative specimen), faster time to response (90min vs. 48–72h), simple handling, reduced number of invalid results for direct testing, its potential implementation outside a sophisticated laboratory, and its safety, as the cartridge represents ‘the laboratory’ where molecular amplification takes place. The Xpert MTB/XDR test can be done taking advantage of existing GeneXpert platforms equipped with 10-colour modules for Xpert MTB/RIF Ultra testing, or through system upgrade from 6-colour modules, with technical capacity to run the Xpert technology available yet on very large scale as infrastructure and procedures are equal. As technology upgrade may be logistically challenging and somehow expensive, different solutions have been conceived, including procurement of new 10-colour GeneXpert modules, new full systems, satellites (instrument only) to connect to existing GeneXpert system or converting an existing system with 6 colours modules to 10 colour modules. In terms of performance of the tests, they are very similar: in our study, it seems to slightly favour Xpert, although only 2 studies were available (sensitivity 91.4–94; specificity 98.5–99; accuracy 97.2–97.7; PPV 88.9–99.1; NPV 95.8–98.9).

The Xpert MTB/XDR is intended as a follow-on test after Xpert MTB/RIF or Xpert MTB/RIF Ultra testing, using left over sample reagent treated specimen, thus not necessarily requesting a second sample or culture to be collected. This approach is attractive with benefits for access to rapid DST, diagnostic laboratory workflow and turnaround time, or after other WHO-endorsed bacteriological tests confirming the presence of pulmonary TB. However, the performance of any rapid assay used as reflex test for a specimen previously determined to be M. tuberculosis positive and harbouring other resistance (e.g., rifampicin) will need to be carefully assessed in future studies, for if the initial rapid test is more sensitive than its reflex assay it may lead to invalid or non-actionable results and challenges with final interpretation of laboratory results.

A second set of considerations relates to the capacity of these tests to reliably diagnose XDR-TB, as newly defined by WHO in 2021.11 Xpert MTB/XDR detects M. tuberculosis complex DNA and mutations associated with resistance to isoniazid, fluoroquinolones (ofloxacin, moxifloxacin, levofloxacin, gatifloxacin), second-line injectable drugs (amikacin, kanamycin, capreomycin), and ethionamide in a single test, whereas GenoType MTBDRplus detects resistance to isoniazid and rifampicin, and GenoType MTBDRsl to fluoroquinolones (ofloxacin and moxifloxacin) and aminoglycosides/cyclic peptides (injectable antibiotics such as kanamycin, amikacin, capreomycin, and viomycin) in its 2 versions. Unfortunately, these tests are testing the drugs defining XDR-TB according to the previous 2006 WHO definition,64 which now reflects pre-XDR due to their capacity to detect resistance to fluoroquinolones, and not XDR-TB as neither these tests nor other genotypic DST assays can rapidly diagnose resistance to linezolid and bedaquiline. This is an important gap that will become more important with time; currently bedaquiline resistance is being detected in over 40% of cases failing the all oral regimen in South Africa, prevalence of bedaquiline resistance is currently 4% in South Africa and 15% in Moldova.65,66 Higher MICs to pretomanid have been detected in Lineage 1 strains.67 A 3 drug BPaL (bedaquiline, pretomanid, linezolid) regimen for pre-XDR with no rapid resistance test beforehand may therefore not be without risk and a shorter duration of lower dose linezolid may select for resistance to linezolid and thwart future salvage regimens. Targeted Next Generation Sequencing solutions are available but there is insufficient understanding of the role of resistance-conferring mutations to these drugs and such technologies are expensive and not implemented yet in many settings.68,69 Nonetheless, the two rapid assays provide valuable information at least on resistance to isoniazid and fluoroquinolones with now also the Xpert MTB/XDR technology and not only LPAs enabling to distinguish low- versus high-level resistance to these drugs.28 The detection of specific mutations is not implemented in the GeneXpert software automated interpretation. This information is nevertheless very relevant for clinicians who can rapidly design the best regimen with high precision guided by the knowledge of the association between specific genetic mutations and phenotypic resistance levels.70 For example, in the case where gyrA A90V, S91P, and D94A mutations associated with low-level fluoroquinolone resistance are identified by specific melting temperature window patterns, high dose moxifloxacin could still work. The detection of resistance to ethionamide and second-line injectables seems currently less clinically relevant, although these medicines can still be added to complete MDR regimens when other options are not available.

Considering the TB diagnostic algorithms and diagnostic characteristics, Xpert MTB/XDR could be placed at or near point-of-care settings to be used primarily as a follow-on test for laboratory-confirmed TB, complementing existing rapid tests that detect only rifampicin, or rifampicin/isoniazid resistance. Detection of fluoroquinolone resistance is essential to inform the use of all-oral 6–12 month standardized shorter regimen for MDR/rifampicin-resistant TB. The assay is conditionally recommended for the initial detection of resistance to isoniazid and fluoroquinolones, rather than culture-based phenotypic DST in people with bacteriologically confirmed pulmonary TB, and for the initial detection of resistance to these drugs and ethionamide and amikacin in people with bacteriologically confirmed pulmonary TB and resistance to rifampicin.17 Xpert MTB/RIF or Xpert Ultra and Xpert MTB/XDR could also be used as the initial diagnostic tests to detect TB, rifampicin, isoniazid and fluoroquinolone resistance in order to achieve universal DST; this algorithm may be preferable in settings with a high MDR-TB burden and also in those with high risk of isoniazid resistance (algorithm 117). If not feasible, it may be used for further evaluation of patients with rifampicin-resistant or MDR-TB, for patients with rifampicin-susceptible TB but no results available for isoniazid but at a high risk for isoniazid resistance (algorithms 3–4).

Our review is limited by high heterogeneity of the population targets and limited range of laboratory tools available. We also note limitations in the study designs of published work identified, including little clinical outcome data following treatment based on test findings.

Finally, rapid diagnostic tests are not only helpful in existing algorithms for guiding drug selection but may also guide dose selection (higher dose) in case of low-level resistance when limited alternative treatment options exist.20 Further testing options when a patient is demonstrating slower response to TB treatment than expected, despite proven drug susceptibility would be valuable, such as supplementary rapid tests for drug exposure. We foresee that the introduction of saliva- and urine-based point-of-care testing as well as microsampling techniques could be provided in conjunction with rapid DST as they are becoming more affordable for resource-limited settings, and may support laboratory testing efforts towards better outcomes for people affected by TB around the world.

Funding

The systematic review was partially funded via an unrestricted grant by Cepheid Europe SAS to the Public Health Consulting Group, Lugano, Switzerland. The donor had no role in conducting the systematic review, as well as analysing and interpreting the results and writing the manuscript.

Conflict of interest

The authors declare to have no conflict of interest directly or indirectly related to the manuscript contents.

Acknowledgements

The study is part of the scientific activities of the GTN (Global Tuberculosis Network).

Appendix A
Supplementary data

The following are the supplementary data to this article:

References
[1]
D. Falzon, F. Mirzayev, F. Wares, I.G. Baena, M. Zignol, N. Linh, et al.
Multidrug-resistant tuberculosis around the world: what progress has been made?.
Eur Respir J, 45 (2015), pp. 150-160
[2]
J. Caminero.
Likelihood of generating MDR-TB and XDR-TB under adequate National Tuberculosis Control Programme implementation.
Int J Tuberc Lung Dis, 12 (2008), pp. 869-877
[3]
G.B. Migliori, G. Besozzi, E. Girardi, K. Kliiman, C. Lange, O.S. Toungoussova, et al.
Clinical and operational value of the extensively drug-resistant tuberculosis definition.
Eur Respir J, 30 (2007), pp. 623-626
[4]
Collaborative Group for the Meta-Analysis of Individual Patient Data in MDR-TB treatment – 2017, Ahmad N, Ahuja SD, Akkerman OW, Alffenaar J-WC, Anderson LF, et al. Treatment correlates of successful outcomes in pulmonary multidrug-resistant tuberculosis: an individual patient data meta-analysis. Lancet 2018;392:821–34.
[5]
M. Roelens, G. Battista Migliori, L. Rozanova, J. Estill, J.R. Campbell, J.P. Cegielski, et al.
Evidence-based definition for extensively drug-resistant tuberculosis.
Am J Respir Crit Care Med, 204 (2021), pp. 713-722
[6]
G.B. Migliori, C. Lange, R. Centis, G. Sotgiu, R. Mütterlein, H. Hoffmann, et al.
Resistance to second-line injectables and treatment outcomes in multidrug-resistant and extensively drug-resistant tuberculosis cases.
Eur Respir J, 31 (2008), pp. 1155-1159
[7]
G.B. Migliori, G. Sotgiu, N.R. Gandhi, D. Falzon, K. DeRiemer, R. Centis, et al.
Drug resistance beyond extensively drug-resistant tuberculosis: individual patient data meta-analysis.
Eur Respir J, 42 (2013), pp. 169-179
[8]
J.A. Caminero.
Extensively drug-resistant tuberculosis: is its definition correct?.
Eur Respir J, 32 (2008), pp. 1413-1415
[9]
G. Migliori.
Global Tuberculosis Network (GTN). Evolution of programmatic definitions used in tuberculosis prevention and care.
Clin Infect Dis, 68 (2019), pp. 1787-1789
[10]
D. Falzon, N. Gandhi, G.B. Migliori, G. Sotgiu, H.S. Cox, T.H. Holtz, et al.
Resistance to fluoroquinolones and second-line injectable drugs: impact on multidrug-resistant TB outcomes.
Eur Respir J, 42 (2013), pp. 156-168
[11]
Geneva: World Health Organization. WHO operational handbook on tuberculosis. Module 4: treatment – drug-resistant tuberculosis treatment. Licence: CC BY-NC-SA 3.0 IGO. 2020.
[12]
Geneva: World Health Organization. Global tuberculosis report 2021. Licence: CC BY-NC-SA 3.0 IGO. 2021.
[13]
Geneva: World Health Organization. Rapid communication: key changes to the treatment of drug-resistant tuberculosis (WHO/UCN/TB/2022.2). Licence: CC BY-NC-SA 3.0 IGO. 2022.
[14]
J.A. Caminero, A.L. García-Basteiro, A. Rendon, A. Piubello, E. Pontali, G.B. Migliori.
The future of drug-resistant tuberculosis treatment: learning from the past and the 2019 World Health Organization consolidated guidelines.
Eur Respir J, 54 (2019), pp. 1901272
[15]
Geneva: World Health Organization. Update on the use of nucleic acid amplification tests to detect TB and drug-resistant TB: rapid communication. Licence: CC BY-NC-SA 3.0 IGO. 2021.
[16]
R. Alagna, A.M. Cabibbe, P. Miotto, F. Saluzzo, C.U. Köser, S. Niemann, et al.
Is the new WHO definition of extensively drug-resistant tuberculosis easy to apply in practice?.
Eur Respir J, 58 (2021), pp. 2100959
[17]
Geneva: World Health Organization. WHO consolidated guidelines on tuberculosis. Module 3: diagnosis – rapid diagnostics for tuberculosis detection, 2021 update. Licence: CC BY-NC-SA 3.0 IGO. 2021.
[18]
M.J. Nasiri, M. Zangiabadian, E. Arabpour, S. Amini, F. Khalili, R. Centis, et al.
Delamanid-containing regimens and multidrug-resistant tuberculosis: a systematic review and meta-analysis.
Int J Infect Dis, (2022),
[19]
H. Hatami, G. Sotgiu, N. Bostanghadiri, S.S.D. Abadi, B. Mesgarpour, H. Goudarzi, et al.
Bedaquiline-containing regimens and multidrug-resistant tuberculosis: a systematic review and meta-analysis.
J Bras Pneumol, 48 (2022), pp. e20210384
[20]
J.W.C. Alffenaar, S.L. Stocker, L.D. Forsman, A. Garcia-Prats, S.K. Heysell, R.E. Aarnoutse, et al.
Clinical standards for the dosing and management of TB drugs.
Int J Tuberc Lung Dis, 26 (2022), pp. 483-499
[21]
S. Pillay, G.R. Davies, M. Chaplin, M. de Vos, S.G. Schumacher, R. Warren, et al.
Xpert MTB/XDR for detection of pulmonary tuberculosis and resistance to isoniazid, fluoroquinolones, ethionamide, and amikacin.
Cochrane Database Syst Rev, (2021), pp. 2021
[22]
S. Pillay, K.R. Steingart, G.R. Davies, M. Chaplin, M. de Vos, S.G. Schumacher, et al.
Xpert MTB/XDR for detection of pulmonary tuberculosis and resistance to isoniazid, fluoroquinolones, ethionamide, and amikacin.
Cochrane Database Syst Rev, (2022), pp. 2022
[23]
D. Moher.
Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement.
[24]
P.F. Whiting, A.W. Rutjes, M.E. Westwood, S. Mallett, J.J. Deeks, J.B. Reitsma, et al.
QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies.
[25]
A. Penn-Nicholson, S.B. Georghiou, N. Ciobanu, M. Kazi, M. Bhalla, A. David, et al.
Detection of isoniazid, fluoroquinolone, ethionamide, amikacin, kanamycin, and capreomycin resistance by the Xpert MTB/XDR assay: a cross-sectional multicentre diagnostic accuracy study.
Lancet Infect Dis, 22 (2022), pp. 242-249
[26]
J. Kardan-Yamchi, S. Amini, G. Hamzelou, A. Rahimi Foroushani, A. Ghodousi, D.M. Cirillo, et al.
Assessment of the GenoType MTBDRsl VER 2.0 compared to the phenotypic drug susceptibility testing and whole genome sequencing for the rapid detection of resistance to fluoroquinolone and second-line injectable drugs among rifampicin-resistant Mycobacterium tuberculosis isolates.
Arch Microbiol, 203 (2021), pp. 3989-3996
[27]
I. Bouzouita, H. Draoui, A.M. Cabibbe, L. Essalah, S. Bejaoui, A. Trovato, et al.
Performance of the GenoType MTBDRsl V 2.0 for detecting second-line drugs resistance of Mycobacterium tuberculosis isolates in Tunisia.
Res Microbiol, 172 (2021), pp. 103816
[28]
Y. Cao, H. Parmar, R.L. Gaur, D. Lieu, S. Raghunath, N. Via, et al.
Xpert MTB/XDR: a 10-color reflex assay suitable for point-of-care settings to detect isoniazid, fluoroquinolone, and second-line-injectable-drug resistance directly from mycobacterium tuberculosis-positive sputum.
J Clin Microbiol, (2021), pp. 59
[29]
K. Singh, R. Kumari, S. Gupta, R. Tripathi, A. Srivastava, V. Shakya, et al.
Direct detection of resistance to fluoroquinolones/SLIDs in sputum specimen by GenoType MTBDRsl v.2.0 assay A study from Eastern Uttar Pradesh, India.
Ann Clin Microbiol Antimicrob, 20 (2021), pp. 56
[30]
M. Ejo, A. van Deun, A. Nunn, S. Meredith, S. Ahmed, D. Dalai, et al.
Effectiveness of GenoType MTBDRsl in excluding TB drug resistance in a clinical trial.
Int J Tuberc Lung Dis, 25 (2021), pp. 839-845
[31]
R.J. Chandak, B. Malhotra, S. Bhargava, S.K. Goel, D. Verma, J. Tiwari.
Evaluation of MTBDRsl for detecting resistance in Mycobacterium tuberculosis to second-line drugs.
Int J Tuberc Lung Dis, 23 (2019), pp. 1257-1262
[32]
Y. Gao, Z. Zhang, J. Deng, M. Mansjö, Z. Ning, Y. Li, et al.
Multi-center evaluation of GenoType MTBDRsl line probe assay for rapid detection of pre-XDR and XDR Mycobacterium tuberculosis in China.
J Infect, 77 (2018), pp. 328-334
[33]
S.B. Rufai, J. Singh, P. Kumar, P. Mathur, S. Singh.
Association of gyrA and rrs gene mutations detected by MTBDRsl V1 on Mycobacterium tuberculosis strains of diverse genetic background from India.
[34]
J. Jian, X. Yang, J. Yang, L. Chen.
Evaluation of the GenoType MTBDRplus and MTBDRsl for the detection of drug-resistant Mycobacterium tuberculosis on isolates from Beijing, China.
Infect Drug Resist, 11 (2018), pp. 1627-1634
[35]
R. Yadav, A. Saini, P. Kaur, D. Behera, S. Sethi.
Diagnostic accuracy of GenoType® MTBDRsl VER 2.0 in detecting second-line drug resistance to M. tuberculosis.
Int J Tuberc Lung Dis, 22 (2018), pp. 419-424
[36]
X. Zeng, W. Jing, Y. Zhang, H. Duan, H. Huang, N. Chu.
Performance of the MTBDR sl Line probe assay for rapid detection of resistance to second-line anti-tuberculosis drugs and ethambutol in China.
Diagn Microbiol Infect Dis, 89 (2017), pp. 112-117
[37]
W. Ennassiri, S. Jaouhari, W. Cherki, R. Charof, A. Filali-Maltouf, O. Lahlou.
Extensively drug-resistant tuberculosis (XDR-TB) in Morocco.
J Global Antimicrob Resist, 11 (2017), pp. 75-80
[38]
Y.S. Lee, B.Y. Lee, K.-W. Jo, T.S. Shim.
Performance of the GenoType MTBDR sl assay for the detection second-line anti-tuberculosis drug resistance.
J Infect Chemother, 23 (2017), pp. 820-825
[39]
Y. Gardee, A.W. Dreyer, H.J. Koornhof, S.v. Omar, P. da Silva, Z. Bhyat, et al.
Evaluation of the GenoType MTBDRsl version 2.0 assay for second-line drug resistance detection of Mycobacterium tuberculosis isolates in South Africa.
J Clin Microbiol, 55 (2017), pp. 791-800
[40]
N.E. Maningi, L.A. Malinga, J.F. Antiabong, R.M. Lekalakala, N.M. Mbelle.
Comparison of line probe assay to BACTEC MGIT 960 system for susceptibility testing of first and second-line anti-tuberculosis drugs in a referral laboratory in South Africa.
BMC Infect Dis, 17 (2017), pp. 795
[41]
K. Tekin, A. Albay, H. Simsek, A.K. Sig, M. Guney.
Evaluation of the BACTEC MGIT 960 SL DST Kit and the GenoType MTBDRsl test for detecting extensively drug resistant tuberculosis cases.
Eur J Med, 49 (2017), pp. 183-187
[42]
D. Bang, S.R. Andersen, E. Vasiliauskienė, E.M. Rasmussen.
Performance of the GenoType MTBDRplus assay (v2.0) and a new extended GenoType MTBDRsl assay (v2.0) for the molecular detection of multi- and extensively drug-resistant Mycobacterium tuberculosis on isolates primarily from Lithuania.
Diagn Microbiol Infect Dis, 86 (2016), pp. 377-381
[43]
M. Tomasicchio, G. Theron, E. Pietersen, E.M. Streicher, D. Stanley-Josephs, P. van Helden, et al.
The diagnostic accuracy of the MTBDRplus and MTBDRsl assays for drug-resistant TB detection when performed on sputum and culture isolates.
Sci Rep, 6 (2016), pp. 17850
[44]
F. Brossier, D. Guindo, A. Pham, F. Reibel, W. Sougakoff, N. Veziris, et al.
Performance of the new version (v2.0) of the GenoType MTBDRsl test for detection of resistance to second-line drugs in multidrug-resistant mycobacterium tuberculosis complex strains.
J Clin Microbiol, 54 (2016), pp. 1573-1580
[45]
W. Lu, Y. Feng, J. Wang, L. Zhu.
Evaluation of MTBDRplus and MTBDRsl in detecting drug-resistant tuberculosis in a Chinese population.
Dis Mark, 2016 (2016), pp. 1-9
[46]
H.Y. Jeong, H. Kim, S. Kwon, S. Ryoo.
Evaluation of the GenoType® MTBDRsl assay in Korean patients with MDR or XDR tuberculosis.
Infect Dis, 48 (2016), pp. 361-366
[47]
E. Tagliani, A.M. Cabibbe, P. Miotto, E. Borroni, J.C. Toro, M. Mansjö, et al.
Diagnostic performance of the new version (v2.0) of GenoType MTBDR sl assay for detection of resistance to fluoroquinolones and second-line injectable drugs: a multicenter study.
J Clin Microbiol, 53 (2015), pp. 2961-2969
[48]
A. Catanzaro, T.C. Rodwell, D.G. Catanzaro, R.S. Garfein, R.L. Jackson, M. Seifert, et al.
Performance comparison of three rapid tests for the diagnosis of drug-resistant tuberculosis.
PLOS ONE, 10 (2015), pp. e0136861
[49]
S.O. Simons, T. van der Laan, R. de Zwaan, M. Kamst, J. van Ingen, P.N.R. Dekhuijzen, et al.
Molecular drug susceptibility testing in the Netherlands: performance of the MTBDRplus and MTBDRsl assays.
Int J Tuberc Lung Dis, 19 (2015), pp. 828-833
[50]
N. Tukvadze, N. Bablishvili, R. Apsindzelashvili, H.M. Blumberg, R.R. Kempker.
Performance of the MTBDRsl assay in Georgia.
Int J Tuberc Lung Dis, 18 (2014), pp. 233-239
[51]
J. Jin, Y. Shen, X. Fan, N. Diao, F. Wang, S. Wang, et al.
Underestimation of the resistance of Mycobacterium tuberculosis to second-line drugs by the new GenoType MTBDRsl test.
J Mol Diagn, 15 (2013), pp. 44-50
[52]
I. Kontsevaya, O. Ignatyeva, V. Nikolayevskyy, Y. Balabanova, A. Kovalyov, A. Kritsky, et al.
Diagnostic accuracy of the GenoType MTBDRsl assay for rapid diagnosis of extensively drug-resistant tuberculosis in HIV-coinfected patients.
J Clin Microbiol, 51 (2013), pp. 243-248
[53]
A. Singh, A. Maurya, S. Kant, J. Umrao, R. Kushwaha, V. Nag, et al.
Rapid detection of drug resistance and mutational patterns of extensively drug-resistant strains by a novel GenoType® MTBDRsl assay.
J Postgrad Med, 59 (2013), pp. 179
[54]
P. López-Roa, M.J. Ruiz-Serrano, L. Alcalá, N. García-Escribano Ráez, D. García de Viedma, E. Bouza.
Susceptibility testing to second-line drugs and ethambutol by Genotype MTBDRsl and Bactec MGIT 960 comparing with agar proportion method.
Tuberculosis, 92 (2012), pp. 417-421
[55]
A. Lacoma, N. García-Sierra, C. Prat, J. Maldonado, J. Ruiz-Manzano, L. Haba, et al.
GenoType MTBDRsl for molecular detection of second-line-drug and ethambutol resistance in Mycobacterium tuberculosis strains and clinical samples.
J Clin Microbiol, 50 (2012), pp. 30-36
[56]
M. Barnard, R. Warren, N.G. van Pittius, P. van Helden, M. Bosman, E. Streicher, et al.
GenoType MTBDRsl line probe assay shortens time to diagnosis of extensively drug-resistant tuberculosis in a high-throughput diagnostic laboratory.
Am J Respir Crit Care Med, 186 (2012), pp. 1298-1305
[57]
P. Miotto, A.M. Cabibbe, P. Mantegani, E. Borroni, L. Fattorini, E. Tortoli, et al.
GenoType MTBDRsl performance on clinical samples with diverse genetic background.
Eur Respir J, 40 (2012), pp. 690-698
[58]
H.M. Said, M.M. Kock, N.A. Ismail, K. Baba, S.v Omar, A.G. Osman, et al.
Evaluation of the GenoType® MTBDRsl assay for susceptibility testing of second-line anti-tuberculosis drugs.
Int J Tuberc Lung Dis, 16 (2012), pp. 104-109
[59]
I. Zivanovic, D. Vukovic, I. Dakic, G. Stefanovic, B. Savic.
Detection of drug-resistant mycobacterium tuberculosis strains isolated in Serbia by the GenoType MTBDRsl assay.
Arch Biol Sci, 64 (2012), pp. 1311-1318
[60]
W.-L. Huang, T.-L. Chi, M.-H. Wu, R. Jou.
Performance assessment of the GenoType MTBDRsl test and DNA sequencing for detection of second-line and ethambutol drug resistance among patients infected with multidrug-resistant Mycobacterium tuberculosis.
J Clin Microbiol, 49 (2011), pp. 2502-2508
[61]
V.S. Kiet, N.T.N. Lan, D.D. An, N.H. Dung, D.V. Hoa, N. van Vinh Chau, et al.
Evaluation of the MTBDRsl test for detection of second-line-drug resistance in Mycobacterium tuberculosis.
J Clin Microbiol, 48 (2010), pp. 2934-2939
[62]
D. Hillemann, S. Rüsch-Gerdes, E. Richter.
Feasibility of the GenoType MTBDRsl assay for fluoroquinolone, amikacin-capreomycin, and ethambutol resistance testing of Mycobacterium tuberculosis strains and clinical specimens.
J Clin Microbiol, 47 (2009), pp. 1767-1772
[63]
Geneva: World Health Organization. Regional distribution of WHO members, n.d. https://www.who.int/countries [accessed 28.6.22].
[64]
Geneva: World Health Organization. Extensively drug-resistant tuberculosis (XDR-TB): recommendations for prevention and control. Wkly Epidemiol Rec 2006;81:430–2.
[65]
E. Chesov, D. Chesov, F.P. Maurer, S. Andres, C. Utpatel, I. Barilar, et al.
Emergence of bedaquiline resistance in a high tuberculosis burden country.
Eur Respir J, 59 (2022), pp. 2100621
[66]
A. Ghodousi, A.H. Rizvi, A.Q. Baloch, A. Ghafoor, F.M. Khanzada, M. Qadir, et al.
Acquisition of cross-resistance to bedaquiline and clofazimine following treatment for tuberculosis in Pakistan.
Antimicrob Agents Chemother, (2019), pp. 63
[67]
A. Bateson, J. Ortiz Canseco, T.D. McHugh, A.A. Witney, S. Feuerriegel, M. Merker, et al.
Ancient and recent differences in the intrinsic susceptibility of Mycobacterium tuberculosis complex to pretomanid.
J Antimicrob Chemother, 77 (2022), pp. 1685-1693
[68]
Geneva: World Health Organization. The use of next-generation sequencing technologies for the detection of mutations associated with drug resistance in Mycobacterium tuberculosis complex: technical guide (WHO/CDS/TB/2018.19). Licence: CC BY-NCSA 3.0 IGO. 2018.
[69]
C. Smith, T.A. Halse, J. Shea, H. Modestil, R.C. Fowler, K.A. Musser, et al.
Assessing nanopore sequencing for clinical diagnostics: a comparison of next-generation sequencing (NGS) methods for Mycobacterium tuberculosis.
J Clin Microbiol, (2020), pp. 59
[70]
Geneva: World Health Organization. Catalogue of mutations in Mycobacterium tuberculosis complex and their association with drug resistance. Licence: CC BY-NC-SA 3.0 IGO. 2021.
Copyright © 2022. SEPAR
Archivos de Bronconeumología
Article options
Tools

Are you a health professional able to prescribe or dispense drugs?