ReviewPharmacogenomics2010
Identifying genomic and developmental causes of adverse drug reactions in children.
Review in Pharmacogenomics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 33 citations in OpenAlex.
- No population left behind: Improving paediatric drug safety using informatics and systems biology.British journal of clinical pharmacology · 2022Review
- Genophenotypic Factors and Pharmacogenomics in Adverse Drug Reactions.International journal of molecular sciences · 2021Review
- Evaluating risk detection methods to uncover ontogenic-mediated adverse drug effect mechanisms in children.BioData mining · 2021Article
- Pharmacogenetics: can genes determine treatment efficacy and safety in JIA?Nature reviews. Rheumatology · 2014Review
- Impact of glutathione S-transferase M1 and T1 on anti-tuberculosis drug-induced hepatotoxicity in Chinese pediatric patients.PloS one · 2014Article
- Pediatric critical care: grand challenges for a glowing future.Frontiers in pediatrics · 2014Article
- Pharmacogenomics and adverse drug reactions in children.Frontiers in genetics · 2014Review
- Relevance of G-quadruplex structures to pharmacogenetics.Frontiers in pharmacology · 2014Article
- HLA-A 31:01 and HLA-B 15:02 as genetic markers for carbamazepine hypersensitivity in children.Clinical pharmacology and therapeutics · 2013Article
- Strategic biomarkers for drug development in treating rare diseases and diseases in neonates and infants.The AAPS journal · 2013Review
- Chloramphenicol toxicity revisited: a 12-year-old patient with a brain abscess.The journal of pediatric pharmacology and therapeutics : JPPT : the official journal of PPAG · 2012Article
- Your clinical pharmacist can save your life, the impact of pharmacist's intervention.Pharmacy practiceArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Adverse drug reactions are a concern for all clinicians who utilize medications to treat adults and children; however, the frequency of adult and pediatric adverse drug reactions is likely to be under-reported. In this age of genomics and personalized medicine, identifying genetic variation that results in differences in drug biotransformation and response has contributed to significant advances in the utilization of several commonly used medications in adults. In order to better understand the variability of drug response in children however, we must not only consider differences in genotype, but also variation in gene expression during growth and development, namely ontogeny. In this article, recommendations for systematically approaching pharmacogenomic studies in children are discussed, and several examples of studies that investigate the genomic and developmental contribution to adverse drug reactions in children are reviewed.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.