title: Assessing the cost-effectiveness of pharmacogenomics.
abstract: The use of pharmacogenomics to individualize drug therapy offers the potential to improve drug effectiveness, reduce adverse side effects, and provide cost-effective pharmaceutical care. However, the combinations of disease, drug, and genetic test characteristics that will provide clinically useful and economically feasible therapeutic interventions have not been clearly elucidated. The purpose of this paper was to develop a framework for evaluating the potential cost-effectiveness of pharmacogenomic strategies that will help scientists better understand the strategic implications of their research, assist in the design of clinical trials, and provide a guide for health care providers making reimbursement decisions. We reviewed concepts of cost-effectiveness analysis and pharmacogenomics and identified 5 primary characteristics that will enhance the cost-effectiveness of pharmacogenomics: 1) there are severe clinical or economic consequence that are avoided through the use of pharmacogenomics, 2) monitoring drug response using current methods is difficult, 3) a well-established association between genotype and clinical phenotype exists, 4) there is a rapid and relatively inexpensive genetic test, and 5) the variant gene is relatively common. We used this framework to evaluate several examples of pharmacogenomics. We found that pharmacogenomics offers great potential to improve patients' health in a cost-effective manner. However, pharmacogenomics will not be applied to all currently marketed drugs, and careful evaluations are needed on a case-by-case basis before investing resources in research and development of pharmacogenomic-based therapeutics and making reimbursement decisions.
authors.affiliation: Pharmaceutical Outcomes Research and Policy Program and Public Health Genetics Program, University of Washington, Department of Pharmacy, Seattle, WA 98195, USA. veenstra@u.washington.edu
authors.forename: D L
authors.initials: DL
authors.lastname: Veenstra
authors.forename: M K
authors.initials: MK
authors.lastname: Higashi
authors.forename: K A
authors.initials: KA
authors.lastname: Phillips
mesh_terms: D000924:Anticholesteremic Agents / Q000627:therapeutic use; D000925:Anticoagulants / Q000493:pharmacokinetics / Q000627:therapeutic use; D000964:Antimetabolites, Antineoplastic / Q000627:therapeutic use; D002318:Cardiovascular Diseases / Q000188:drug therapy / Q000191:economics / Q000201:enzymology; D002352:Carrier Proteins / Q000235:genetics; D002648:Child; D053480:Cholesterol Ester Transfer Proteins; D003362:Cost-Benefit Analysis; D004358:Drug Therapy / Q000191:economics*; D005838:Genotype; D006023:Glycoproteins; D006526:Hepatitis C / Q000188:drug therapy / Q000191:economics; D006801:Humans; D007372:Interferons / Q000627:therapeutic use; D015122:Mercaptopurine / Q000627:therapeutic use; D008780:Methyltransferases / Q000172:deficiency; D010597:Pharmacogenetics / Q000191:economics*; D010601:Pharmacology, Clinical / Q000191:economics / Q000379:methods*; D010641:Phenotype; D017035:Pravastatin / Q000627:therapeutic use; D054198:Precursor Cell Lymphoblastic Leukemia-Lymphoma / Q000188:drug therapy / Q000191:economics / Q000201:enzymology; D012254:Ribavirin / Q000627:therapeutic use; D014859:Warfarin / Q000493:pharmacokinetics / Q000627:therapeutic use
chemical_list: D000924:Anticholesteremic Agents; D000925:Anticoagulants; D000964:Antimetabolites, Antineoplastic; C506642:CETP protein, human; D002352:Carrier Proteins; D053480:Cholesterol Ester Transfer Proteins; D006023:Glycoproteins; D012254:Ribavirin; D014859:Warfarin; D007372:Interferons; D015122:Mercaptopurine; D008780:Methyltransferases; C022745:thiopurine methyltransferase; D017035:Pravastatin