A prognostic model based on readily available clinical data enriched a pre-emptive pharmacogenetic testing program

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• 作者：Jonathan S. Schildcrout^a ; ^b ; ^{jonathan.schildcrout@vanderbilt.edu" class="auth_mail" title="E-mail the corresponding author} ; Yaping Shi^a ; Ioana Danciu^c ; Erica Bowton^c ; Julie R. Field^c ; Jill M. Pulley^c ; Melissa A. Basford^c ; William Gregg^d ; ^e ; James D. Cowan^c ; Frank E. Harrell Jr.^a ; Dan M. Roden^e ; ^f ; Josh F. Peterson^d ; ^e ; Joshua C. Denny^d ; ^e
• 关键词：Clopidogrel ; Computer decision support ; Electronic health records ; Precision medicine ; Statin ; Warfarin
• 刊名：Journal of Clinical Epidemiology
• 出版年：2016
• 出版时间：April 2016
• 年：2016
• 卷：72
• 期：Complete
• 页码：107-115
• 全文大小：624 K

文摘

We describe the development, implementation, and evaluation of a model to pre-emptively select patients for genotyping based on medication exposure risk.

Study Design and Setting

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.