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 language | English |
|---|---|
| Pages (from-to) | 738-745 |
| Number of pages | 8 |
| Journal | Clinical Pharmacology and Therapeutics |
| Volume | 105 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 01-03-2019 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Pharmacology
- Pharmacology (medical)
Cite this
}
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 journal › Article
TY - JOUR
T1 - A Pharmacogenetic Prediction Model of Progression-Free Survival in Breast Cancer using Genome-Wide Genotyping Data from CALGB 40502 (Alliance)
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.
PY - 2019/3/1
Y1 - 2019/3/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85055922262&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85055922262&partnerID=8YFLogxK
U2 - 10.1002/cpt.1241
DO - 10.1002/cpt.1241
M3 - Article
C2 - 30260474
AN - SCOPUS:85055922262
VL - 105
SP - 738
EP - 745
JO - Clinical Pharmacology and Therapeutics
JF - Clinical Pharmacology and Therapeutics
SN - 0009-9236
IS - 3
ER -