A Pharmacogenetic Prediction Model of Progression-Free Survival in Breast Cancer using Genome-Wide Genotyping Data from CALGB 40502 (Alliance)

Sara R. Rashkin, Katherina C. Chua, Carol Ho, Flora Mulkey, Chen Jiang, Tasei Mushiroda, Michiaki Kubo, Paula N. Friedman, Hope S. Rugo, Howard L. McLeod, Mark J. Ratain, Francisco Castillos, Michael Naughton, Beth Overmoyer, Deborah Toppmeyer, John S. Witte, Kouros Owzar, Deanna L. Kroetz

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Genome-wide genotyping data are increasingly available for pharmacogenetic association studies, but application of these data for development of prediction models is limited. Prediction methods, such as elastic net regularization, have recently been applied to genetic studies but only limitedly to pharmacogenetic outcomes. An elastic net was applied to a pharmacogenetic study of progression-free survival (PFS) of 468 patients with advanced breast cancer in a clinical trial of paclitaxel, nab-paclitaxel, and ixabepilone. A final model included 13 single nucleotide polymorphisms (SNPs) in addition to clinical covariates (prior taxane status, hormone receptor status, disease-free interval, and presence of visceral metastases) with an area under the curve (AUC) integrated over time of 0.81, an increase compared to an AUC of 0.64 for a model with clinical covariates alone. This model may be of value in predicting PFS with microtubule targeting agents and may inform reverse translational studies to understand differential response to these drugs.

Original languageEnglish
Pages (from-to)738-745
Number of pages8
JournalClinical Pharmacology and Therapeutics
Volume105
Issue number3
DOIs
Publication statusPublished - 01-03-2019

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Pharmacogenetics
Disease-Free Survival
Area Under Curve
Genome
Breast Neoplasms
Paclitaxel
Microtubules
Single Nucleotide Polymorphism
Clinical Trials
Hormones
Neoplasm Metastasis
Pharmaceutical Preparations
Pharmacogenomic Testing
taxane
130-nm albumin-bound paclitaxel
ixabepilone

All Science Journal Classification (ASJC) codes

  • Pharmacology
  • Pharmacology (medical)

Cite this

Rashkin, Sara R. ; Chua, Katherina C. ; Ho, Carol ; Mulkey, Flora ; Jiang, Chen ; Mushiroda, Tasei ; Kubo, Michiaki ; Friedman, Paula N. ; Rugo, Hope S. ; McLeod, Howard L. ; Ratain, Mark J. ; Castillos, Francisco ; Naughton, Michael ; Overmoyer, Beth ; Toppmeyer, Deborah ; Witte, John S. ; Owzar, Kouros ; Kroetz, Deanna L. / A Pharmacogenetic Prediction Model of Progression-Free Survival in Breast Cancer using Genome-Wide Genotyping Data from CALGB 40502 (Alliance). In: Clinical Pharmacology and Therapeutics. 2019 ; Vol. 105, No. 3. pp. 738-745.
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abstract = "Genome-wide genotyping data are increasingly available for pharmacogenetic association studies, but application of these data for development of prediction models is limited. Prediction methods, such as elastic net regularization, have recently been applied to genetic studies but only limitedly to pharmacogenetic outcomes. An elastic net was applied to a pharmacogenetic study of progression-free survival (PFS) of 468 patients with advanced breast cancer in a clinical trial of paclitaxel, nab-paclitaxel, and ixabepilone. A final model included 13 single nucleotide polymorphisms (SNPs) in addition to clinical covariates (prior taxane status, hormone receptor status, disease-free interval, and presence of visceral metastases) with an area under the curve (AUC) integrated over time of 0.81, an increase compared to an AUC of 0.64 for a model with clinical covariates alone. This model may be of value in predicting PFS with microtubule targeting agents and may inform reverse translational studies to understand differential response to these drugs.",
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Rashkin, SR, Chua, KC, Ho, C, Mulkey, F, Jiang, C, Mushiroda, T, Kubo, M, Friedman, PN, Rugo, HS, McLeod, HL, Ratain, MJ, Castillos, F, Naughton, M, Overmoyer, B, Toppmeyer, D, Witte, JS, Owzar, K & Kroetz, DL 2019, 'A Pharmacogenetic Prediction Model of Progression-Free Survival in Breast Cancer using Genome-Wide Genotyping Data from CALGB 40502 (Alliance)' Clinical Pharmacology and Therapeutics, vol. 105, no. 3, pp. 738-745. https://doi.org/10.1002/cpt.1241

A Pharmacogenetic Prediction Model of Progression-Free Survival in Breast Cancer using Genome-Wide Genotyping Data from CALGB 40502 (Alliance). / Rashkin, Sara R.; Chua, Katherina C.; Ho, Carol; Mulkey, Flora; Jiang, Chen; Mushiroda, Tasei; Kubo, Michiaki; Friedman, Paula N.; Rugo, Hope S.; McLeod, Howard L.; Ratain, Mark J.; Castillos, Francisco; Naughton, Michael; Overmoyer, Beth; Toppmeyer, Deborah; Witte, John S.; Owzar, Kouros; Kroetz, Deanna L.

In: Clinical Pharmacology and Therapeutics, Vol. 105, No. 3, 01.03.2019, p. 738-745.

Research output: Contribution to journalArticle

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AU - Rashkin, Sara R.

AU - Chua, Katherina C.

AU - Ho, Carol

AU - Mulkey, Flora

AU - Jiang, Chen

AU - Mushiroda, Tasei

AU - Kubo, Michiaki

AU - Friedman, Paula N.

AU - Rugo, Hope S.

AU - McLeod, Howard L.

AU - Ratain, Mark J.

AU - Castillos, Francisco

AU - Naughton, Michael

AU - Overmoyer, Beth

AU - Toppmeyer, Deborah

AU - Witte, John S.

AU - Owzar, Kouros

AU - Kroetz, Deanna L.

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