A prognostic model based on readily available clinical data enriched a pre-emptive pharmacogenetic testing program.
J Clin Epidemiol
; 72: 107-15, 2016 Apr.
Article
en En
| MEDLINE
| ID: mdl-26628336
ABSTRACT
OBJECTIVES:
We describe the development, implementation, and evaluation of a model to pre-emptively select patients for genotyping based on medication exposure risk. STUDY DESIGN ANDSETTING:
Using deidentified electronic health records, 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 pre-emptive 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 1 and 2 years after index dates. Risk estimates tended to underestimate true risk. The cumulative incidences of medication prescriptions at 1 and 2 years were 0.35 and 0.48, respectively, among 1,673 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 pre-emptive pharmacogenetic testing toward those likely to benefit from it.Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Farmacogenética
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Warfarina
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Ticlopidina
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Inhibidores de Hidroximetilglutaril-CoA Reductasas
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Utilización de Medicamentos
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Registros Electrónicos de Salud
Tipo de estudio:
Etiology_studies
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Evaluation_studies
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Observational_studies
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Prognostic_studies
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Risk_factors_studies
Límite:
Adult
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Aged
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Female
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Humans
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Male
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Middle aged
País/Región como asunto:
America do norte
Idioma:
En
Revista:
J Clin Epidemiol
Asunto de la revista:
EPIDEMIOLOGIA
Año:
2016
Tipo del documento:
Article