We assessed the predictive accuracy of the Warfarin Pharmacogenetics Consortium (IWPC) algorithm in a prospective cohort of 376 high-risk elderly patients (≥65 years) who required new treatment with warfarin for either medical (non valvular atrial fibrillation) or surgical conditions (heart valve replacement), had ≥1 comorbid conditions, and regularly used ≥2 other drugs. Follow-up visits were performed according to clinical practice and lasted for a maximum of 1 year. Two hundred and eighty-three (75%) patients achieved a stable maintenance dose. Warfarin maintenance doses were low on average (median 20.3 mg/week, interquartile range, 14.1-27.7 mg/week) and were substantially overestimated by the IWPC algorithm. Overall the percentage of patients whose predicted dose of warfarin was within 20% of the actual stable dose was equal to 37.5%, (95% CI 32.0-43.3%). IWPC algorithm explained only 31% of the actual warfarin dose variability. Modifications of the IWPC algorithm are needed in high-risk elderly people.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1038/s41397-019-0129-6 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Comparative performance of pharmacogenetics-based warfarin dosing algorithms in Chinese population: use of a pharmacokinetic/pharmacodynamic model to explore dosing regimen through clinical trial simulation.
Pharmacogenet Genomics
December 2024
School of Nursing and Health, Henan University, Kaifeng, China.
Objective: Warfarin has a narrow therapeutic window and large variability in dosing that are affected by clinical and genetic factors. To help guide the dosing of warfarin, the Clinical Pharmacogenetics Implementation Consortium has recommended the use of pharmacogenetic algorithms, such as the ones developed by the International Warfarin Pharmacogenetics Consortium (IWPC) and by Gage et al. when genotype information is available.
View Article and Find Full Text PDFDevelopment and validation wise assessment of genotype guided warfarin dosing algorithm in Indian population.
Drug Metab Pers Ther
September 2023
Department of Pharmacology, Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh, India.
Article Synopsis
- - A study was conducted to create and validate a warfarin dose optimization algorithm specifically for Asian patients, following CPIC recommendations, by assessing genetic factors affecting individual responses to the medication.
- - The research involved 300 patients, assessing genetic polymorphisms and clinical factors, revealing significant influences on warfarin doses, and resulting in an algorithm that correlates well with established Western algorithms.
- - The newly developed algorithm demonstrated strong predictive capabilities (73% sensitivity and 96% positive predictive value), indicating its potential readiness for further clinical trial evaluation.
Validation and comparison between two warfarin dosing clinical algorithms and warfarin fixed dosing in specialized heart center: cross-sectional study.
Pharm Pract (Granada)
September 2022
PhD, Msc. Department of Pharmacology, Faculty of Pharmacy, University of Gezira, Wad Medani-Sudan.
Background: Warfarin is well known as a narrow therapeutic index that has prodigious variability in response which challenges dosing adjustment for the maintenance of therapeutic international normalized ratio. However, an appreciated population not on new oral anticoagulants may still need to be stabilized with warfarin dosing.
Objective: The current study's main objective was to validate and compare two models of warfarin clinical algorithm models namely the Gage and the International Warfarin Pharmacogenetics Consortium (IWPC) with warfarin 5 mg fixed standard dosing strategy in a sample of Sudanese subjects.
Automated warfarin dose prediction for Asian, American, and Caucasian populations using a deep neural network.
Comput Biol Med
February 2023
Laboratory of Clinical Pharmacology, Division of Cellular & Molecular Research, National Cancer Centre Singapore, Singapore; Singapore Immunology Network, Agency for Science, Technology & Research (A*STAR), Singapore; Centre for Clinician Scientist Development, Duke-NUS Medical School, Singapore. Electronic address:
Article Synopsis
- * This study developed a deep learning-based model using a large, curated dataset from over 6000 patients to enhance the accuracy of warfarin dose predictions by incorporating diverse patient data, including medical history and genetic information.
- * The deep learning model showed promising results with low mean absolute error rates across different ethnic groups, potentially allowing for more accurate warfarin dosing in clinical practice if validated with similar populations.
Comparison of Maintenance Dose Predictions by Warfarin Dosing Algorithms Based on Chinese and Western Patients.
J Clin Pharmacol
May 2023
Department of Thoracic Surgery, First Affiliated Hospital of Henan University, Kaifeng, China.
Warfarin has a long record of safe and effective clinical use, and it remains one of the most commonly prescribed drugs for the prevention and treatment of thromboembolic conditions even in the era of direct oral anticoagulants. To address its large interindividual variability and narrow therapeutic window, the Clinical Pharmacogenetics Implementation Consortium has recommended using pharmacogenetic dosing algorithms, such as the ones developed by the International Warfarin Pharmacogenetics Consortium (IWPC) and by Gage et al, to dose warfarin when genotype information is available. In China, dosing algorithms based on local patient populations have been developed and evaluated for predictive accuracy of warfarin maintenance doses.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!