A New Pharmacogenetic Algorithm to Predict the Most Appropriate Dosage of Acenocoumarol for Stable Anticoagulation in a Mixed Spanish Population
There is a strong association between genetic polymorphisms and the acenocoumarol dosage requirements. Genotyping the polymorphisms involved in the pharmacokinetics and pharmacodynamics of acenocoumarol before starting anticoagulant therapy would result in a better quality of life and a more efficie...
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| Vydané v: | PLOS ONE Ročník 11; číslo 3; s. e0150456 |
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| Hlavní autori: | , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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United States
Public Library of Science (PLoS)
15.03.2016
Public Library of Science |
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| ISSN: | 1932-6203, 1932-6203 |
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| Abstract | There is a strong association between genetic polymorphisms and the acenocoumarol dosage requirements. Genotyping the polymorphisms involved in the pharmacokinetics and pharmacodynamics of acenocoumarol before starting anticoagulant therapy would result in a better quality of life and a more efficient use of healthcare resources. The objective of this study is to develop a new algorithm that includes clinical and genetic variables to predict the most appropriate acenocoumarol dosage for stable anticoagulation in a wide range of patients. We recruited 685 patients from 2 Spanish hospitals and 1 primary healthcare center. We randomly chose 80% of the patients (n = 556), considering an equitable distribution of genotypes to form the generation cohort. The remaining 20% (n = 129) formed the validation cohort. Multiple linear regression was used to generate the algorithm using the acenocoumarol stable dosage as the dependent variable and the clinical and genotypic variables as the independent variables. The variables included in the algorithm were age, weight, amiodarone use, enzyme inducer status, international normalized ratio target range and the presence of CYP2C9*2 (rs1799853), CYP2C9*3 (rs1057910), VKORC1 (rs9923231) and CYP4F2 (rs2108622). The coefficient of determination (R2) explained by the algorithm was 52.8% in the generation cohort and 64% in the validation cohort. The following R2 values were evaluated by pathology: atrial fibrillation, 57.4%; valve replacement, 56.3%; and venous thromboembolic disease, 51.5%. When the patients were classified into 3 dosage groups according to the stable dosage (<11 mg/week, 11-21 mg/week, >21 mg/week), the percentage of correctly classified patients was higher in the intermediate group, whereas differences between pharmacogenetic and clinical algorithms increased in the extreme dosage groups. Our algorithm could improve acenocoumarol dosage selection for patients who will begin treatment with this drug, especially in extreme-dosage patients. The predictability of the pharmacogenetic algorithm did not vary significantly between diseases. |
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| AbstractList | There is a strong association between genetic polymorphisms and the acenocoumarol dosage requirements. Genotyping the polymorphisms involved in the pharmacokinetics and pharmacodynamics of acenocoumarol before starting anticoagulant therapy would result in a better quality of life and a more efficient use of healthcare resources. The objective of this study is to develop a new algorithm that includes clinical and genetic variables to predict the most appropriate acenocoumarol dosage for stable anticoagulation in a wide range of patients. We recruited 685 patients from 2 Spanish hospitals and 1 primary healthcare center. We randomly chose 80% of the patients (n = 556), considering an equitable distribution of genotypes to form the generation cohort. The remaining 20% (n = 129) formed the validation cohort. Multiple linear regression was used to generate the algorithm using the acenocoumarol stable dosage as the dependent variable and the clinical and genotypic variables as the independent variables. The variables included in the algorithm were age, weight, amiodarone use, enzyme inducer status, international normalized ratio target range and the presence of CYP2C9*2 (rs1799853), CYP2C9*3 (rs1057910), VKORC1 (rs9923231) and CYP4F2 (rs2108622). The coefficient of determination (R2) explained by the algorithm was 52.8% in the generation cohort and 64% in the validation cohort. The following R2 values were evaluated by pathology: atrial fibrillation, 57.4%; valve replacement, 56.3%; and venous thromboembolic disease, 51.5%. When the patients were classified into 3 dosage groups according to the stable dosage (<11 mg/week, 11–21 mg/week, >21 mg/week), the percentage of correctly classified patients was higher in the intermediate group, whereas differences between pharmacogenetic and clinical algorithms increased in the extreme dosage groups. Our algorithm could improve acenocoumarol dosage selection for patients who will begin treatment with this drug, especially in extreme-dosage patients. The predictability of the pharmacogenetic algorithm did not vary significantly between diseases. There is a strong association between genetic polymorphisms and the acenocoumarol dosage requirements. Genotyping the polymorphisms involved in the pharmacokinetics and pharmacodynamics of acenocoumarol before starting anticoagulant therapy would result in a better quality of life and a more efficient use of healthcare resources. The objective of this study is to develop a new algorithm that includes clinical and genetic variables to predict the most appropriate acenocoumarol dosage for stable anticoagulation in a wide range of patients. We recruited 685 patients from 2 Spanish hospitals and 1 primary healthcare center. We randomly chose 80% of the patients (n = 556), considering an equitable distribution of genotypes to form the generation cohort. The remaining 20% (n = 129) formed the validation cohort. Multiple linear regression was used to generate the algorithm using the acenocoumarol stable dosage as the dependent variable and the clinical and genotypic variables as the independent variables. The variables included in the algorithm were age, weight, amiodarone use, enzyme inducer status, international normalized ratio target range and the presence of CYP2C9*2 (rs1799853), CYP2C9*3 (rs1057910), VKORC1 (rs9923231) and CYP4F2 (rs2108622). The coefficient of determination (R.sup.2) explained by the algorithm was 52.8% in the generation cohort and 64% in the validation cohort. The following R.sup.2 values were evaluated by pathology: atrial fibrillation, 57.4%; valve replacement, 56.3%; and venous thromboembolic disease, 51.5%. When the patients were classified into 3 dosage groups according to the stable dosage (21 mg/week), the percentage of correctly classified patients was higher in the intermediate group, whereas differences between pharmacogenetic and clinical algorithms increased in the extreme dosage groups. Our algorithm could improve acenocoumarol dosage selection for patients who will begin treatment with this drug, especially in extreme-dosage patients. The predictability of the pharmacogenetic algorithm did not vary significantly between diseases. There is a strong association between genetic polymorphisms and the acenocoumarol dosage requirements. Genotyping the polymorphisms involved in the pharmacokinetics and pharmacodynamics of acenocoumarol before starting anticoagulant therapy would result in a better quality of life and a more efficient use of healthcare resources. The objective of this study is to develop a new algorithm that includes clinical and genetic variables to predict the most appropriate acenocoumarol dosage for stable anticoagulation in a wide range of patients. We recruited 685 patients from 2 Spanish hospitals and 1 primary healthcare center. We randomly chose 80% of the patients (n = 556), considering an equitable distribution of genotypes to form the generation cohort. The remaining 20% (n = 129) formed the validation cohort. Multiple linear regression was used to generate the algorithm using the acenocoumarol stable dosage as the dependent variable and the clinical and genotypic variables as the independent variables. The variables included in the algorithm were age, weight, amiodarone use, enzyme inducer status, international normalized ratio target range and the presence of CYP2C9*2 (rs1799853), CYP2C9*3 (rs1057910), VKORC1 (rs9923231) and CYP4F2 (rs2108622). The coefficient of determination (R 2 ) explained by the algorithm was 52.8% in the generation cohort and 64% in the validation cohort. The following R 2 values were evaluated by pathology: atrial fibrillation, 57.4%; valve replacement, 56.3%; and venous thromboembolic disease, 51.5%. When the patients were classified into 3 dosage groups according to the stable dosage (<11 mg/week, 11–21 mg/week, >21 mg/week), the percentage of correctly classified patients was higher in the intermediate group, whereas differences between pharmacogenetic and clinical algorithms increased in the extreme dosage groups. Our algorithm could improve acenocoumarol dosage selection for patients who will begin treatment with this drug, especially in extreme-dosage patients. The predictability of the pharmacogenetic algorithm did not vary significantly between diseases. |
| Audience | Academic |
| Author | Luis Javier Martinez-Gonzalez Carmen Fernández-Capitán Alberto M. Borobia Cristina Lucía Dávila-Fajardo Hoi Y. Tong Antonio J. Carcas Xando Díaz-Villamarín R. Lubomirov María Jesús Blanco Bañares Laura María Perea León José Cabeza Barrera |
| AuthorAffiliation | 2 Department of Clinical Pharmacy, San Cecilio University Hospital, Institute for Biomedical Research, Ibs, Granada, Spain 4 Department of Pharmacology, School of Medicine, Autonomous University of Madrid, IdiPAZ, Madrid, Spain 3 Genomics Unit, Centre for Genomics and Oncological Research (GENYO), Pfizer-University of Granada-Andalusian Regional Government, Health Sciences Technology Park, PTS, Granada, Spain 6 Department of Internal Medicine, La Paz University Hospital, IdiPAZ, Madrid, Spain National Cancer Center, JAPAN 1 Department of Clinical Pharmacology, La Paz University Hospital, IdiPAZ, Madrid, Spain 5 Department of Hematology, La Paz University Hospital, Madrid, Spain |
| AuthorAffiliation_xml | – name: 6 Department of Internal Medicine, La Paz University Hospital, IdiPAZ, Madrid, Spain – name: 2 Department of Clinical Pharmacy, San Cecilio University Hospital, Institute for Biomedical Research, Ibs, Granada, Spain – name: 4 Department of Pharmacology, School of Medicine, Autonomous University of Madrid, IdiPAZ, Madrid, Spain – name: National Cancer Center, JAPAN – name: 3 Genomics Unit, Centre for Genomics and Oncological Research (GENYO), Pfizer-University of Granada-Andalusian Regional Government, Health Sciences Technology Park, PTS, Granada, Spain – name: 1 Department of Clinical Pharmacology, La Paz University Hospital, IdiPAZ, Madrid, Spain – name: 5 Department of Hematology, La Paz University Hospital, Madrid, Spain |
| Author_xml | – sequence: 1 fullname: Cabeza Barrera, José – sequence: 1 fullname: Dávila-Fajardo, Cristina Lucía – sequence: 1 fullname: Tong, Hoi Y – sequence: 1 fullname: Perea León, Laura María – sequence: 1 fullname: Martínez-González, Luis Javier – sequence: 1 fullname: Blanco Bañares, María J – sequence: 1 fullname: Fernández-Capitán, Carmen – sequence: 1 fullname: Borobia, Alberto M – sequence: 1 fullname: Lubomirov, Rubin – sequence: 1 fullname: Díaz-Villamarín, Xando – sequence: 1 fullname: Carcas, Antonio J |
| BackLink | https://cir.nii.ac.jp/crid/1871146592944746752$$DView record in CiNii https://www.ncbi.nlm.nih.gov/pubmed/26977927$$D View this record in MEDLINE/PubMed |
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| ContentType | Journal Article |
| Contributor | This study was funded by a grant from the Spanish Ministry of Health and Social Policy (Instituto de Salud Carlos III, PI07/0710) and the Andalusian Regional Ministry of Health (Progress and Health Foundation, PI-0717-2013) UAM. Departamento de Medicina Instituto de Investigación Sanitaria Hospital Universitario de La Paz (IdiPAZ) UAM. Departamento de Farmacología [Tong,HY] Department of Clinical Pharmacology, La Paz University Hospital, IdiPAZ, Madrid, Spain. [Dávila-Fajardo,CL; Perea León,LM; Cabeza Barrera,J] Department of Clinical Pharmacy, San Cecilio University Hospital, Institute for Biomedical Research, Ibs, Granada, Spain. [Borobia,AM] Department of Clinical Pharmacology, La Paz University Hospital, IdiPAZ, Madrid, Spain, Department of Pharmacology, School of Medicine, Autonomous University of Madrid, IdiPAZ, Madrid, Spain. [Martínez-González,LJ] Genomics Unit, Centre for Genomics and Oncological Research (GENYO), Pfizer-University of Granada-Andalusian Regional Government, Health |
| Contributor_xml | – sequence: 1 fullname: PGX-ACE Investigators Group – sequence: 2 fullname: [Tong,HY] Department of Clinical Pharmacology, La Paz University Hospital, IdiPAZ, Madrid, Spain. [Dávila-Fajardo,CL; Perea León,LM; Cabeza Barrera,J] Department of Clinical Pharmacy, San Cecilio University Hospital, Institute for Biomedical Research, Ibs, Granada, Spain. [Borobia,AM] Department of Clinical Pharmacology, La Paz University Hospital, IdiPAZ, Madrid, Spain, Department of Pharmacology, School of Medicine, Autonomous University of Madrid, IdiPAZ, Madrid, Spain. [Martínez-González,LJ] Genomics Unit, Centre for Genomics and Oncological Research (GENYO), Pfizer-University of Granada-Andalusian Regional Government, Health Sciences Technology Park, PTS, Granada, Spain. [Lubomirov,R] Department of Pharmacology, School of Medicine, Autonomous University of Madrid, IdiPAZ, Madrid, Spain. [Blanco Bañares,MJ] Department of Hematology, La Paz University Hospital, Madrid, Spain. [Fernández-Capitán,C] Department of Internal Medicine, La Paz University Hospital, IdiPAZ, Madrid, Spain. [Carcas,AJ] Department of Clinical Pharmacology, La Paz University Hospital, IdiPAZ, Madrid, Spain, Department of Pharmacology, School of Medicine, Autonomous University of Madrid, IdiPAZ, Madrid, Spain – sequence: 3 fullname: This study was funded by a grant from the Spanish Ministry of Health and Social Policy (Instituto de Salud Carlos III, PI07/0710) and the Andalusian Regional Ministry of Health (Progress and Health Foundation, PI-0717-2013) – sequence: 4 fullname: UAM. Departamento de Medicina – sequence: 5 fullname: UAM. Departamento de Farmacología – sequence: 6 fullname: Instituto de Investigación Sanitaria Hospital Universitario de La Paz (IdiPAZ) |
| Copyright | COPYRIGHT 2016 Public Library of Science 2016 Tong et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2016 Tong et al 2016 Tong et al |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Competing Interests: The authors have declared that no competing interests exist. Membership of the PGX-ACE Investigators Group is listed in S1 Appendix. Conceived and designed the experiments: HYT CDF AMB LMG AJC. Performed the experiments: HYT CDF AMB LMG RL LPL MBB XDV CFC JCB AJC and the PGX-ACE Investigators Group. Analyzed the data: HYT CDF AMB RL AJC. Contributed reagents/materials/analysis tools: HYT CDF AMB LPL MBB XDV JCB AJC. Wrote the paper: HYT CDF AMB LMG RL LPL MBB XDV CFC JCB AJC. |
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| SubjectTerms | A new algorithm Acenocoumarol Acenocoumarol - administration & dosage Acenocoumarol - pharmacology Acenocoumarol dosage Aged Algorithms Amiodarone Analysis Anticoagulants Anticoagulants - administration & dosage Anticoagulants - pharmacology Appropriate acenocoumarol dosag Biology and Life Sciences Biomedical research Cardiac arrhythmia Dependent variables Dosage Drug dosages Embolisms Farmacia Female Fibrillation Genetic algorithms Genetic polymorphisms Genomics Genotypes Genotyping Health care Humans Independent variables Male Medical Subject Headings::Check Tags::Female Medical Subject Headings::Check Tags::Male Medical Subject Headings::Chemicals and Drugs::Chemical Actions and Uses::Pharmacologic Actions::Therapeutic Uses::Hematologic Agents::Anticoagulants Medical Subject Headings::Chemicals and Drugs::Heterocyclic Compounds::Heterocyclic Compounds, 2-Ring::Benzopyrans::Coumarins::4-Hydroxycoumarins::Acenocoumarol Medical Subject Headings::Disciplines and Occupations::Natural Science Disciplines::Biological Science Disciplines::Pharmacology::Pharmacogenetics Medical Subject Headings::Geographicals::Geographic Locations::Europe::Spain Medical Subject Headings::Named Groups::Persons::Age Groups::Adult::Aged Medical Subject Headings::Named Groups::Persons::Age Groups::Adult::Middle Aged Medical Subject Headings::Organisms::Eukaryota::Animals::Chordata::Vertebrates::Mammals::Primates::Haplorhini::Catarrhini::Hominidae::Humans Medical Subject Headings::Phenomena and Processes::Mathematical Concepts::Algorithms Medicina Medicine Medicine and Health Sciences Middle Aged Patients Pharmacodynamics Pharmacogenetic Pharmacogenetics Pharmacokinetics Pharmacology Pharmacy Physical Sciences Q Quality of life R Research and Analysis Methods Research Article Science Spain Stable anticoagulation Thromboembolism |
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| Title | A New Pharmacogenetic Algorithm to Predict the Most Appropriate Dosage of Acenocoumarol for Stable Anticoagulation in a Mixed Spanish Population |
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