ArticlePharmacogenetics and genomics2014
Comparison of study designs used to detect and characterize pharmacogenomic interactions in nonexperimental studies: a simulation study.
Article in Pharmacogenetics and genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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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.
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Who cites it
2 citing papers in PubMed, 7 citations in OpenAlex.
- A genome-wide interaction analysis of tricyclic/tetracyclic antidepressants and RR and QT intervals: a pharmacogenomics study from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium.Journal of medical genetics · 2017Article
- Identifying genetic loci affecting antidepressant drug response in depression using drug-gene interaction models.Pharmacogenomics · 2016Review
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
objectivesAdverse drug reactions are common, serious, difficult to predict, and may be influenced by genetics, prompting the increasing popularity of pharmacogenomic studies. Many pharmacogenomic studies are conducted in nonexperimental settings, yet little is known about the influence of confounding by contraindication. We, therefore, compared the two designs [the overall population (OPD) and the treated-only (TOD) design] by simulating a pharmacogenomic study of the ECG QT interval (QT).
methodsSimulations were informed by data from the Atherosclerosis Risk in Communities Study and a literature review examining QT, QT-prolonging drug use, and modification by single nucleotide polymorphisms (SNP). Drug treatment was assigned on the basis of age, sex, and QTlong, representing confounding by contraindication. QT was simulated as a function of drug treatment, one SNP, the drug-SNP interaction, and clinical covariates.
resultsFailure to adjust for confounding by contraindication produced a varying degree of bias in the OPD, whereas the TOD was biased by the SNP main effect. For example, in the OPD, the false-positive proportion for the drug-SNP interaction was 5% across the range of SNP main effects (0-10 ms), but increased to 19% without adjusting for confounding by contraindication. In the TOD, the false-positive proportion increased to 89% with SNP main effects greater than 4 ms, although bias was reduced by 39% with adjustment for covariates affected by the SNP.
conclusionThe potential for bias from confounding by contraindication (OPD) should be weighed against bias from SNP main effects (TOD) when selecting the study design that best suits the given context.
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