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

Jonathan S. Schildcrout; Yaping Shi; Ioana Danciu; Erica Bowton; Julie R. Field; Jill M. Pulley; Melissa A. Basford; William Gregg; James D. Cowan; Frank E. Harrell; Dan M. Roden; Josh F. Peterson; Joshua C. Denny

doi:10.1016/j.jclinepi.2015.08.028

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

Jonathan S. Schildcrout
, Yaping Shi
, Ioana Danciu
, Erica Bowton
, Julie R. Field
, Jill M. Pulley
, Melissa A. Basford
, William Gregg
, James D. Cowan
, Frank E. Harrell
, Dan M. Roden
, Josh F. Peterson
, Joshua C. Denny

Human Analysis and Biometrics

Research output: Contribution to journal › Article › peer-review

22 Scopus citations

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 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.

Original language	English
Pages (from-to)	107-115
Number of pages	9
Journal	Journal of Clinical Epidemiology
Volume	72
DOIs	https://doi.org/10.1016/j.jclinepi.2015.08.028
State	Published - Apr 1 2016

Funding

Authors'' contributions: J.S.S., J.M.P., J.F.P., W.G., D.M.R., and J.C.D. developed the study concept and design. I.D., E.B., M.B., J.R.F., and J.C. acquired data; J.S.S., Y.S., and F.E.H. analyzed data and generated tables and figures. All authors contributed to data interpretation. J.S.S., Y.S., J.F.P., and J.C.D. drafted the report, and all authors contributed to the final version. Funding: This project was funded by Vanderbilt University, the Centers for Disease Control and Prevention (U47CI000824), the National Heart, Lung, and Blood Institute (U01HL122904, U19HL065962, and R01HL094786), the National Institute of General Medical Sciences (U19HL065962 and RC2GM092318), the National Human Genome Research Institute (U01HG006378), and the National Center for Advancing Translational Sciences (UL1TR000445). The analyses described herein are solely the responsibility of the authors alone and do not necessarily represent official views of the Centers for Disease Control and Prevention or the National Institutes of Health.

Keywords

Clopidogrel
Computer decision support
Electronic health records
Precision medicine
Statin
Warfarin

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10.1016/j.jclinepi.2015.08.028

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Schildcrout, J. S., Shi, Y., Danciu, I., Bowton, E., Field, J. R., Pulley, J. M., Basford, M. A., Gregg, W., Cowan, J. D., Harrell, F. E., Roden, D. M., Peterson, J. F., & Denny, J. C. (2016). A prognostic model based on readily available clinical data enriched a pre-emptive pharmacogenetic testing program. Journal of Clinical Epidemiology, 72, 107-115. https://doi.org/10.1016/j.jclinepi.2015.08.028

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

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 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.",

keywords = "Clopidogrel, Computer decision support, Electronic health records, Precision medicine, Statin, Warfarin",

author = "Schildcrout, \{Jonathan S.\} and Yaping Shi and Ioana Danciu and Erica Bowton and Field, \{Julie R.\} and Pulley, \{Jill M.\} and Basford, \{Melissa A.\} and William Gregg and Cowan, \{James D.\} and Harrell, \{Frank E.\} and Roden, \{Dan M.\} and Peterson, \{Josh F.\} and Denny, \{Joshua C.\}",

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year = "2016",

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doi = "10.1016/j.jclinepi.2015.08.028",

language = "English",

volume = "72",

pages = "107--115",

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Schildcrout, JS, Shi, Y, Danciu, I, Bowton, E, Field, JR, Pulley, JM, Basford, MA, Gregg, W, Cowan, JD, Harrell, FE, Roden, DM, Peterson, JF & Denny, JC 2016, 'A prognostic model based on readily available clinical data enriched a pre-emptive pharmacogenetic testing program', Journal of Clinical Epidemiology, vol. 72, pp. 107-115. https://doi.org/10.1016/j.jclinepi.2015.08.028

TY - JOUR

T1 - A prognostic model based on readily available clinical data enriched a pre-emptive pharmacogenetic testing program

AU - Schildcrout, Jonathan S.

AU - Shi, Yaping

AU - Danciu, Ioana

AU - Bowton, Erica

AU - Field, Julie R.

AU - Pulley, Jill M.

AU - Basford, Melissa A.

AU - Gregg, William

AU - Cowan, James D.

AU - Harrell, Frank E.

AU - Roden, Dan M.

AU - Peterson, Josh F.

AU - Denny, Joshua C.

PY - 2016/4/1

Y1 - 2016/4/1

N2 - 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 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.

AB - 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 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.

KW - Clopidogrel

KW - Computer decision support

KW - Electronic health records

KW - Precision medicine

KW - Statin

KW - Warfarin

UR - https://www.scopus.com/pages/publications/84961063635

U2 - 10.1016/j.jclinepi.2015.08.028

DO - 10.1016/j.jclinepi.2015.08.028

M3 - Article

C2 - 26628336

AN - SCOPUS:84961063635

SN - 0895-4356

VL - 72

SP - 107

EP - 115

JO - Journal of Clinical Epidemiology

JF - Journal of Clinical Epidemiology

ER -

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

Abstract

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Keywords

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