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A Pharmacogenetic Prediction Model of Progression‐Free Survival in Breast Cancer using Genome‐Wide Genotyping Data from CALGB 40502 (Alliance)
Author(s) -
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.
Publication year - 2019
Publication title -
clinical pharmacology and therapeutics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.941
H-Index - 188
eISSN - 1532-6535
pISSN - 0009-9236
DOI - 10.1002/cpt.1241
Subject(s) - pharmacogenetics , ixabepilone , oncology , breast cancer , taxane , medicine , single nucleotide polymorphism , genotyping , genome wide association study , bioinformatics , genotype , cancer , metastatic breast cancer , biology , genetics , gene
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 ( SNP s) 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.