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Influence of genetic variants on toxicity to anti-tubercular agents: a systematic review and meta-analysis (protocol)

Overview of attention for article published in Systematic Reviews, July 2017
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Title
Influence of genetic variants on toxicity to anti-tubercular agents: a systematic review and meta-analysis (protocol)
Published in
Systematic Reviews, July 2017
DOI 10.1186/s13643-017-0533-4
Pubmed ID
Authors

Marty Richardson, Jamie Kirkham, Kerry Dwan, Derek Sloan, Geraint Davies, Andrea Jorgensen

Abstract

Tuberculosis patients receiving anti-tuberculosis treatment may experience serious adverse drug reactions, such as hepatotoxicity. Genetic risk factors, such as polymorphisms of the NAT2, CYP2E1 and GSTM1 genes, may increase the risk of experiencing such toxicity events. Many pharmacogenetic studies have investigated the association between genetic variants and anti-tuberculosis drug-related toxicity events, and several meta-analyses have synthesised data from these studies, although conclusions from these meta-analyses are conflicting. Many meta-analyses also have serious methodological limitations, such as applying restrictive inclusion criteria, or not assessing the quality of included studies. Most also only consider hepatotoxicity outcomes and specific genetic variants. The purpose of this systematic review and meta-analysis is to give a comprehensive evaluation of the evidence base for associations between any genetic variant and anti-tuberculosis drug-related toxicity. We will search for studies in MEDLINE, EMBASE, BIOSIS and Web of Science. We will also hand search reference lists from relevant studies and contact experts in the field. We will include cohort studies, case-control studies and randomised controlled trials that recruited patients with tuberculosis who were either already established on anti-tuberculosis treatment or were commencing treatment and who were genotyped to investigate the effect of genetic variants on any anti-tuberculosis drug-related toxicity outcome. One author will screen abstracts to identify potentially relevant studies and will then obtain the full text for each potentially relevant study in order to assess eligibility. At each of these stages, a second author will independently screen/assess 10% of studies. Two authors will independently extract data and assess the quality of studies using a pre-piloted data extraction form. If appropriate, we will pool estimates of effect for each genotype on each outcome using meta-analyses stratified by ethnicity. Our review and meta-analysis will update and add to the existing research in this field. By not restricting the scope of the review to a specific drug, genetic variant, or toxicity outcome, we hope to synthesise data for associations between genetic variants and anti-tuberculosis drug-related toxicity outcomes that have previously not been summarised in systematic reviews, and consequently, add to the knowledge base of the pharmacogenetics of anti-tuberculosis drugs. PROSPERO CRD42017068448.

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 55 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 9 16%
Student > Ph. D. Student 8 15%
Researcher 5 9%
Student > Doctoral Student 3 5%
Lecturer 2 4%
Other 9 16%
Unknown 19 35%
Readers by discipline Count As %
Medicine and Dentistry 11 20%
Biochemistry, Genetics and Molecular Biology 8 15%
Pharmacology, Toxicology and Pharmaceutical Science 7 13%
Social Sciences 2 4%
Nursing and Health Professions 1 2%
Other 4 7%
Unknown 22 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 25 July 2017.
All research outputs
#14,945,861
of 22,988,380 outputs
Outputs from Systematic Reviews
#1,561
of 2,005 outputs
Outputs of similar age
#185,969
of 312,390 outputs
Outputs of similar age from Systematic Reviews
#42
of 57 outputs
Altmetric has tracked 22,988,380 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,005 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.8. This one is in the 20th percentile – i.e., 20% 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 312,390 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 57 others from the same source and published within six weeks on either side of this one. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.