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A prognostic model based on readily available clinical data enriched a preemptive pharmacogenetic testing program
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Nov 25 2015
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Source: J Clin Epidemiol. 72:107-115.
[PDF-1.75 MB]
Details:
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Alternative Title:J Clin Epidemiol
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Description:Objective
We describe the development, implementation, and evaluation of a model to preemptively select patients for genotyping based on medication exposure risk.
Study Design and Setting
Using de-identified electronic health records (EHR), we derived a prognostic model for the prescription of statins, warfarin, or clopidogrel. The model was implemented into a clinical decision support (CDS) tool to recommend preemptive genotyping for patients exceeding a prescription risk threshold. We evaluated the rule on an independent validation cohort, and on an implementation cohort, representing the population in which the CDS tool was deployed.
Results
The model exhibited moderate discrimination with area under the receiver operator characteristic curves ranging from 0.68 to 0.75 at one and two years following index dates. Risk estimates tended to underestimate true risk. The cumulative incidences of medication prescriptions at one and two years were 0.35 and 0.48, respectively, among 1673 patients flagged by the model. The cumulative incidences in the same number of randomly sampled subjects were 0.12 and 0.19, and in patients over 50 years with the highest body mass indices, they were 0.22 and 0.34.
Conclusion
We demonstrate that prognostic algorithms can guide preemptive pharmacogenetic testing towards those likely to benefit from it.
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Pubmed ID:26628336
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Pubmed Central ID:PMC4779720
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