Journal of internal medicine
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Treatment effects, especially when comparing two or more therapeutic alternatives as in comparative effectiveness research, are likely to be heterogeneous across age, gender, co-morbidities and co-medications. Propensity scores (PSs), an alternative to multivariable outcome models to control for measured confounding, have specific advantages in the presence of heterogeneous treatment effects. ⋯ Sensitivity analyses based on PSs can help to assess such unmeasured confounding. PSs should be considered a primary or secondary analytic strategy in nonexperimental medical research, including pharmacoepidemiology and nonexperimental comparative effectiveness research.
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A solid foundation of evidence of the effects of an intervention is a prerequisite of evidence-based medicine. The best source of such evidence is considered to be randomized trials, which are able to avoid confounding. ⋯ Randomized point-of-care trials have been initiated recently to recruit and follow patients using the data from EHR databases. In this review, we describe how EHR databases can be used for conducting large-scale simple trials and discuss the advantages and disadvantages of their use.
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Inter-individual variability in drug responses is a common problem in pharmacotherapy. Several factors (non-genetic and genetic) influence drug responses in patients. ⋯ This review describes the definition of pharmacogenetics, gene selection and study design for pharmacogenetic research. It also summarizes the potential of linking pharmacoepidemiology and pharmacogenetics (along with its strengths and limitations) and provides examples of pharmacogenetic studies utilizing electronic health record databases.
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The aim of the study was to examine whether various lifestyle factors modify genetic influences on coronary heart disease (CHD). ⋯ The difference in the genetic component of CHD as a function of BMI suggests that genetic factors may play a more prominent role for disease development in the absence of important environmental factors. Increased knowledge of gene-environment interactions will be important for a full understanding of the aetiology of CHD.