Literature DB >> 31361818

Pharmacogenomic potential in advanced cancer patients.

Dan Nichols1, Susanne Arnold2, Heidi L Weiss2, Jianrong Wu2, Eric B Durbin2, Rachel Miller2, Jill Kolesar3.   

Abstract

PURPOSE: The prevalence of pharmacogenetically actionable medications in advanced cancer patients whose therapy may be optimized with genotype data was determined.
METHODS: Patients enrolled in our institutional molecular tumor board observational cohort were included in this study. Collected data included demographics, type(s) of cancer, and outpatient medications. Medications were classified as "pharmacogenetically actionable" if there are Clinical Pharmacogenetics Implementation Consortium (CPIC) therapeutic recommendations for that medication based on the presence of germline variations. The prevalence of pharmacogenetically actionable medications in the study population was determined, and the frequency of opportunities for pharmacogenetic prescribing and adverse event (AE) mitigation were estimated.
RESULTS: In a cohort of 193 patients with advanced cancer, 65% of patients were taking a pharmacogenetically actionable medication. Approximately 10% of the outpatient medications taken by the study population had a pharmacogenetic association. The most common pharmacogenetically actionable medications being used were ondansetron (47%), capecitabine (10%), and sertraline (7%). Using published genetic variation frequencies and AE risk, we conservatively estimated that 7.1% of cancer patients would be eligible for genetic-based medication adjustment, and 101 AEs would be prevented in 10,000 patients genotyped.
CONCLUSION: Medications with pharmacogenetic associations are used commonly in the advanced cancer patient population. This widespread exposure supports the implementation of prospective genotyping in the treatment of these high-risk patients. © American Society of Health-System Pharmacists 2019. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  Cancer; germline; oncology; pharmacogenetics; pharmacogenomics

Mesh:

Substances:

Year:  2019        PMID: 31361818     DOI: 10.1093/ajhp/zxy079

Source DB:  PubMed          Journal:  Am J Health Syst Pharm        ISSN: 1079-2082            Impact factor:   2.637


  4 in total

1.  Analytical Validation of a Computational Method for Pharmacogenetic Genotyping from Clinical Whole Exome Sequencing.

Authors:  Reynold C Ly; Tyler Shugg; Ryan Ratcliff; Wilberforce Osei; Ty C Lynnes; Victoria M Pratt; Bryan P Schneider; Milan Radovich; Steven M Bray; Benjamin A Salisbury; Baiju Parikh; S Cenk Sahinalp; Ibrahim Numanagić; Todd C Skaar
Journal:  J Mol Diagn       Date:  2022-04-20       Impact factor: 5.341

2.  Description of a Lung Cancer Hotspot: Disparities in Lung Cancer Histology, Incidence, and Survival in Kentucky and Appalachian Kentucky.

Authors:  Christine F Brainson; Bin Huang; Quan Chen; Laurie E McLouth; Chunyan He; Zhonglin Hao; Susanne M Arnold; Ralph G Zinner; Timothy W Mullett; Therese J Bocklage; David K Orren; John L Villano; Eric B Durbin
Journal:  Clin Lung Cancer       Date:  2021-03-26       Impact factor: 4.785

Review 3.  Genophenotypic Factors and Pharmacogenomics in Adverse Drug Reactions.

Authors:  Ramón Cacabelos; Vinogran Naidoo; Lola Corzo; Natalia Cacabelos; Juan C Carril
Journal:  Int J Mol Sci       Date:  2021-12-10       Impact factor: 5.923

4.  Real-World Evaluation of Universal Germline Screening for Cancer Treatment-Relevant Pharmacogenes.

Authors:  Megan L Hutchcraft; Nan Lin; Shulin Zhang; Catherine Sears; Kyle Zacholski; Elizabeth A Belcher; Eric B Durbin; John L Villano; Michael J Cavnar; Susanne M Arnold; Frederick R Ueland; Jill M Kolesar
Journal:  Cancers (Basel)       Date:  2021-09-08       Impact factor: 6.639

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.