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Use of whole-genome sequencing to distinguish relapse from reinfection in a completed tuberculosis clinical trial

Overview of attention for article published in BMC Medicine, March 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)
  • Average Attention Score compared to outputs of the same age and source

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1 policy source
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Title
Use of whole-genome sequencing to distinguish relapse from reinfection in a completed tuberculosis clinical trial
Published in
BMC Medicine, March 2017
DOI 10.1186/s12916-017-0834-4
Pubmed ID
Authors

Adam A. Witney, Anna L. E. Bateson, Amina Jindani, Patrick P. J. Phillips, David Coleman, Neil G. Stoker, Philip D. Butcher, Timothy D. McHugh, RIFAQUIN Study Team

Abstract

RIFAQUIN was a tuberculosis chemotherapy trial in southern Africa including regimens with high-dose rifapentine with moxifloxacin. Here, the application of whole-genome sequencing (WGS) is evaluated within RIFAQUIN for identifying new infections in treated patients as either relapses or reinfections. WGS is further compared with mycobacterial interspersed repetitive units-variable number tandem repeats (MIRU-VNTR) typing. This is the first report of WGS being used to evaluate new infections in a completed clinical trial for which all treatment and epidemiological data are available for analysis. DNA from 36 paired samples of Mycobacterium tuberculosis cultured from patients before and after treatment was typed using 24-loci MIRU-VNTR, in silico spoligotyping and WGS. Following WGS, the sequences were mapped against the reference strain H37Rv, the single-nucleotide polymorphism (SNP) differences between pairs were identified, and a phylogenetic reconstruction was performed. WGS indicated that 32 of the paired samples had a very low number of SNP differences (0-5; likely relapses). One pair had an intermediate number of SNP differences, and was likely the result of a mixed infection with a pre-treatment minor genotype that was highly related to the post-treatment genotype; this was reclassified as a relapse, in contrast to the MIRU-VNTR result. The remaining three pairs had very high SNP differences (>750; likely reinfections). WGS and MIRU-VNTR both similarly differentiated relapses and reinfections, but WGS provided significant extra information. The low proportion of reinfections seen suggests that in standard chemotherapy trials with up to 24 months of follow-up, typing the strains brings little benefit to an analysis of the trial outcome in terms of differentiating relapse and reinfection. However, there is a benefit to using WGS as compared to MIRU-VNTR in terms of the additional genotype information obtained, in particular for defining the presence of mixed infections and the potential to identify known and novel drug-resistance markers.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 118 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 118 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 27 23%
Student > Ph. D. Student 17 14%
Student > Master 16 14%
Student > Bachelor 10 8%
Other 6 5%
Other 14 12%
Unknown 28 24%
Readers by discipline Count As %
Medicine and Dentistry 24 20%
Agricultural and Biological Sciences 17 14%
Immunology and Microbiology 16 14%
Biochemistry, Genetics and Molecular Biology 15 13%
Pharmacology, Toxicology and Pharmaceutical Science 4 3%
Other 10 8%
Unknown 32 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 February 2019.
All research outputs
#3,128,941
of 24,286,850 outputs
Outputs from BMC Medicine
#1,868
of 3,730 outputs
Outputs of similar age
#56,320
of 312,473 outputs
Outputs of similar age from BMC Medicine
#39
of 64 outputs
Altmetric has tracked 24,286,850 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,730 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 45.1. This one is in the 49th percentile – i.e., 49% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 312,473 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 64 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.