Xpert Mycobacterium tuberculosis/Rifampicin-Detected Rifampicin Resistance is a Suboptimal Surrogate for Multidrug-resistant Tuberculosis in Eastern Democratic Republic of the Congo: Diagnostic and Clinical Implications

BACKGROUND

Rifampicin (RIF) resistance is highly correlated with isoniazid (INH) resistance and used as proxy for multidrug-resistant tuberculosis (MDR-TB). Using MTBDRplus as a comparator, we evaluated the predictive value of Xpert MTB/RIF (Xpert)-detected RIF resistance for MDR-TB in eastern Democratic Republic of the Congo (DRC).

METHODS

We conducted a cross-sectional study involving data from new or retreatment pulmonary adult TB cases evaluated between July 2013 and December 2016. Separate, paired sputa for smear microscopy and MTBDRplus were collected. Xpert testing was performed subject to the availability of Xpert cartridges on sample remnants after microscopy.

RESULTS

Among 353 patients, 193 (54.7%) were previously treated and 224 (63.5%) were MTBDRplus TB positive. Of the 224, 43 (19.2%) were RIF monoresistant, 11 (4.9%) were INH monoresistant, 53 (23.7%) had MDR-TB, and 117 (52.2%) were RIF and INH susceptible. Overall, among the 96 samples detected by MTBDRplus as RIF resistant, 53 (55.2%) had MDR-TB. Xpert testing was performed in 179 (50.7%) specimens; among these, 163 (91.1%) were TB positive and 73 (44.8%) RIF resistant. Only 45/73 (61.6%) Xpert-identified RIF-resistant isolates had concomitant MTBDRplus-detected INH resistance. Xpert had a sensitivity of 100.0% (95% CI, 92.1-100.0) for detecting RIF resistance but a positive-predictive value of only 61.6% (95% CI, 49.5-72.8) for MDR-TB. The most frequent mutations associated with RIF and INH resistance were S531L and S315T1, respectively.

CONCLUSIONS

In this high-risk MDR-TB study population, Xpert had low positive-predictive value for the presence of MDR-TB. Comprehensive resistance testing for both INH and RIF should be performed in this setting.

Deep amplicon sequencing for culture-free prediction of susceptibility or resistance to 13 anti-tuberculous drugs

Conventional molecular tests for detecting Mycobacterium tuberculosis complex (MTBC) drug resistance on clinical samples cover a limited set of mutations. Whole-genome sequencing (WGS) typically requires culture.

Here, we evaluated the Deeplex Myc-TB targeted deep-sequencing assay for prediction of resistance to 13 anti-tuberculous drugs/drug classes, directly applicable on sputum.

With MTBC DNA tests, the limit of detection was 100–1000 genome copies for fixed resistance mutations. Deeplex Myc-TB captured in silico 97.1–99.3% of resistance phenotypes correctly predicted by WGS from 3651 MTBC genomes. On 429 isolates, the assay predicted 92.2% of 2369 first- and second-line phenotypes, with a sensitivity of 95.3% and a specificity of 97.4%. 56 out of 69 (81.2%) residual discrepancies with phenotypic results involved pyrazinamide, ethambutol and ethionamide, and low-level rifampicin or isoniazid resistance mutations, all notoriously prone to phenotypic testing variability. Only two out of 91 (2.2%) resistance phenotypes undetected by Deeplex Myc-TB had known resistance-associated mutations by WGS analysis outside Deeplex Myc-TB targets. Phenotype predictions from Deeplex Myc-TB analysis directly on 109 sputa from a Djibouti survey matched those of MTBSeq/PhyResSE/Mykrobe, fed with WGS data from subsequent cultures, with a sensitivity of 93.5/98.5/93.1% and a specificity of 98.5/97.2/95.3%, respectively. Most residual discordances involved gene deletions/indels and 3–12% heteroresistant calls undetected by WGS analysis or natural pyrazinamide resistance of globally rare “Mycobacterium canettii” strains then unreported by Deeplex Myc-TB. On 1494 arduous sputa from a Democratic Republic of the Congo survey, 14 902 out of 19 422 (76.7%) possible susceptible or resistance phenotypes could be predicted culture-free.

Deeplex Myc-TB may enable fast, tailored tuberculosis treatment.

The novel Deeplex Myc-TB molecular assay shows a high degree of accuracy for extensive prediction of susceptibility and resistance to 13 anti-tuberculous drugs, directly achievable without culture, which may enable fast, tailored tuberculosis treatmenthttps://bit.ly/3bAvcAt

Prevalence, Predictors, and Successful Treatment Outcomes of Xpert MTB/RIF-identified Rifampicin-resistant Tuberculosis in Post-conflict Eastern Democratic Republic of the Congo, 2012-2017: A Retrospective Province-Wide Cohort Study

Background

Multidrug-resistant tuberculosis (MDR-TB) jeopardizes global TB control. The prevalence and predictors of Rifampicin-resistant (RR) TB, a proxy for MDR-TB, and the treatment outcomes with standard and shortened regimens have not been assessed in post-conflict regions, such as the South Kivu province in the eastern Democratic Republic of the Congo (DRC). We aimed to fill this knowledge gap and to inform the DRC National TB Program.

Methods

of adults and children evaluated for pulmonary TB by sputum smear microscopy and Xpert MTB/RIF (Xpert) from February 2012 to June 2017. Multivariable logistic regression, Kaplan–Meier estimates, and multivariable Cox regression were used to assess independent predictors of RR-TB and treatment failure/death.

Results

Of 1535 patients Xpert-positive for TB, 11% had RR-TB. Independent predictors of RR-TB were a positive sputum smear (adjusted odds ratio [aOR] 2.42, 95% confidence interval [CI] 1.63–3.59), retreatment of TB (aOR 4.92, 95% CI 2.31–10.45), and one or more prior TB episodes (aOR 1.77 per episode, 95% CI 1.01–3.10). Over 45% of RR-TB patients had no prior TB history or treatment. The median time from Xpert diagnosis to RR-TB treatment initiation was 12 days (interquartile range 3–60.2). Cures were achieved in 30/36 (83%) and 84/114 (74%) of patients on 9- vs 20/24-month MDR-TB regimens, respectively (P = .06). Predictors of treatment failure/death were the absence of directly observed therapy (DOT; adjusted hazard ratio [aHR] 2.77, 95% CI 1.2–6.66) and any serious adverse drug event (aHR 4.28, 95% CI 1.88–9.71).

Conclusions

Favorable RR-TB cure rates are achievable in this post-conflict setting with a high RR-TB prevalence. An expanded Xpert scale-up; the prompt initiation of shorter, safer, highly effective MDR-TB regimens; and treatment adherence support are critically needed to optimize outcomes.

The relationship between transmission time and clustering methods in Mycobacterium tuberculosis epidemiology

BACKGROUND

Tracking recent transmission is a vital part of controlling widespread pathogens such as Mycobacterium tuberculosis. Multiple methods with specific performance characteristics exist for detecting recent transmission chains, usually by clustering strains based on genotype similarities. With such a large variety of methods available, informed selection of an appropriate approach for determining transmissions within a given setting/time period is difficult.

METHODS

This study combines whole genome sequence (WGS) data derived from 324 isolates collected 2005-2010 in Kinshasa, Democratic Republic of Congo (DRC), a high endemic setting, with phylodynamics to unveil the timing of transmission events posited by a variety of standard genotyping methods. Clustering data based on Spoligotyping, 24-loci MIRU-VNTR typing, WGS based SNP (Single Nucleotide Polymorphism) and core genome multi locus sequence typing (cgMLST) typing were evaluated.

FINDINGS

Our results suggest that clusters based on Spoligotyping could encompass transmission events that occurred almost 200 years prior to sampling while 24-loci-MIRU-VNTR often represented three decades of transmission. Instead, WGS based genotyping applying low SNP or cgMLST allele thresholds allows for determination of recent transmission events, e.g. in timespans of up to 10 years for a 5 SNP/allele cut-off.

INTERPRETATION

With the rapid uptake of WGS methods in surveillance and outbreak tracking, the findings obtained in this study can guide the selection of appropriate clustering methods for uncovering relevant transmission chains within a given time-period. For high resolution cluster analyses, WGS-SNP and cgMLST based analyses have similar clustering/timing characteristics even for data obtained from a high incidence setting.