Validation and comparison between two warfarin dosing clinical algorithms and warfarin fixed dosing in specialized heart center: cross-sectional study

Main Article Content

Keywords

Accuracy, Clinical safety, Over-prediction, Practicality, Warfarin clinical algorithms, Warfarin fixed standard dosing strategy, Under-prediction

Abstract

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. Method: We have conducted a cross-sectional study recruited from the out-patient clinic at a tertiary specialized heart center. We included subjects with unchanged warfarin dose (stabilized), and with therapeutic international normalized ratio. The predicted doses of warfarin in the two models were calculated by three different methods (accuracy, clinical practicality, and the clinical safety of the clinical algorithms). Main outcome measure: The primary outcomes were the measurements of the clinical (accuracy, practicality, and safety) in each of the two clinical algorithms models compared to warfarin 5 mg fixed standard dose strategy. Results: We have enrolled 71 Sudanese subjects with mean age (51.7 ± 14 years), of which (49, 69.0%) were females. There was no significant difference between the warfarin 5 mg fixed standard dose strategy and the predicted doses of the two clinical algorithm models (MAE 1.44, 1.45, and 1.49 mg/day [P =0.4]) respectively. In the clinical practicality, all of the three models had a high percent of subjects (95.0%, 51.9%, and 66.7%) in the ideal dose range in middle dose group (3-7 mg/ day) for warfarin 5 mg fixed standard dosing strategy, Gage, and IWPC clinical algorithm models respectively. However, a small percent of subjects was exhibited in the warfarin low dose group ≤ 3 mg/day (0.0%, 15.0%, and 10.0%) and warfarin high dose group ≥ 7 mg/day (0.0%, 33.3%, and 33.3%) for warfarin 5 mg fixed standard dosing strategy, Gage, and IWPC clinical algorithms respectively. In terms of clinical safety, the percent of subjects with severely over-prediction were 28.2%, 22.5%, and 22.5% for warfarin 5 mg fixed standard dosing, Gage, and IWPC, respectively. While the percent of severely under-prediction was 12.7%, 7.0%, and 5.6% for the warfarin 5 mg fixed standard dosing, Gage, and IWPC, respectively. Conclusion: The Gage and IWPC clinical algorithm models were accurate, more clinically practical, and clinically safe than warfarin 5 mg standard dosing in the study population. The cardiologist can use either models (Gage and IWPC) to stratify subjects for accurate, practical, and clinically safe warfarin dosing..

Downloads

Download data is not yet available.
Abstract 321 | PDF Downloads 226

References

1. Roper N, Storer B, Bona R, et al. Validation and Comparison of Pharmacogenetics-Based Warfarin Dosing Algorithms for Application of Pharmacogenetic Testing. J Mol Diagn. 2010;12(3):283-291. https://doi.org/10.2353/jmoldx.2010.090110
2. Finkelman BS, Gage BF, Johnson JA, et al. Genetic Warfarin Dosing: Tables Versus Algorithms. J Am Coll Cardiol. 2011;57(5):612-618. https://doi.org/10.1016/j.jacc.2010.08.643
3. Kimmel SE, French B, Kasner SE, et al. A Pharmacogenetic versus a Clinical Algorithm for Warfarin Dosing. N Engl J Med.2013;369(24):2283-93. https://doi.org/10.1056/NEJMoa1310669
4. Hamberg A-K, Hellman J, Dahlberg J, et al. A Bayesian decision support tool for efficient dose individualization of warfarin in adults and children. BMC Med Inform Decis Mak. 2015;15:7. https://doi.org/10.1186/s12911-014-0128-0
5. Cho S, Lee K, Choi JR, et al. Development and Comparison of Warfarin Dosing Algorithms in Stroke Patients. Yonsei Med J.2016;57(3):635-640. https://doi.org/10.1056/NEJMoa1310669
6. Pathare A, Al Khabori M, Alkindi S, et al. Warfarin pharmacogenetics: development of a dosing algorithm for Omani patients.J Hum Genet. 2012;57(10):665-669. https://doi.org/10.1038/jhg.2012.94
7. Gage BF, Eby C, Johnson J, et al. Use of Pharmacogenetic and Clinical Factors to Predict the Therapeutic Dose of Warfarin. Clin Pharmacol Ther. 2008;84(3):326-331. https://doi.org/10.1038/clpt.2008.10
8. Bazan NS, Sabry NA, Rizk A, et al. Validation of pharmacogenetic algorithms and warfarin dosing table in Egyptian patients. Int J Clin Pharm. 2012;34(6):837-844. https://doi.org/10.1007/s11096-012-9678-3
9. Zhu Y, Hong X, Wei M, et al. Development of a novel individualized warfarin dose algorithm based on a population pharmacokinetic model with improved prediction accuracy for Chinese patients after heart valve replacement. Acta Pharmacol Sin. 2017;38(3):434-442. https://doi.org/10.1038/aps.2016.163
10. Gaikwad T, Ghosh K, Avery P, et al. Warfarin Dose Model for the Prediction of Stable Maintenance Dose in Indian Patients. Clin Appl Thromb. 2018;24(2):353-359. https://doi.org/10.1177/1076029616683046
11. Klein TE, Altman RB, Eriksson N, et al. International Warfarin Pharmacogenetics Consortium. Estimation of the Warfarin Dose with Clinical and Pharmacogenetic Data. N Engl J Med. 2009;360(4):753-764. https://doi.org/10.1056/NEJMoa0809329
12. Karaca S, Bozkurt NC, Cesuroglu T, et al. International warfarin genotype-guided dosing algorithms in the Turkish population and their preventive effects on major and life-threatening hemorrhagic events. Pharmacogenomics. 2015;16(10):1109-18.https://doi.org/10.2217/pgs.15.58
13. Lin M, Yu L, Qiu H, et al. Verification of five pharmacogenomics-based warfarin administration models. Indian J Pharmacol. 2016;48(3):258. https://doi.org/10.4103/0253-7613.182876
14. Ren Y, Yang C, Chen H, et al. Pharmacogenetic-Guided Algorithm to Improve Daily Dose of Warfarin in Elder Han-Chinese Population. Front Pharmacol. 2020;11:1014. https://doi.org/10.3389/fphar.2020.01014
15. Shaw PB, Donovan JL, Tran MT, et al. Accuracy assessment of pharmacogenetically predictive warfarin dosing algorithms in patients of an academic medical center anticoagulation clinic. J Thromb Thrombolysis. 2010;30(2):220-225. https://doi.org/10.1007/s11239-010-0459-3
16. Shrif Nema, Won HH, Lee ST, et al. Evaluation of the effects of VKORC1 polymorphisms and haplotypes, CYP2C9 genotypes,and clinical factors on warfarin response in Sudanese patients. Eur J Clin Pharmacol. 2011;67(11):1119-1130. https://doi.org/10.1007/s00228-011-1060-1
17. Ahmed NO, Osman B, Abdelhai YM, et al. Impact of clinical pharmacist intervention in anticoagulation clinic in Sudan. Int J Clin 
Pharm. 2017;39(4):769-773. https://doi.org/10.1007/s11096-017-0475-x
18. Selim TE, Azzam HA, Ghoneim HR, et al. Pharmacogenetic Warfarin Dosing Algorithms: Validity in Egyptian Patients. Acta Haematol. 2018;139(4):255-262. https://doi.org/10.1159/000486889
19. Takeuchi F, Kashida M, Okazaki O, et al. Evaluation of Pharmacogenetic Algorithm for Warfarin Dose Requirements in Japanese Patients. Circulation. 2010;74(5):1-6.
20. Poller L, Keown M, Ibrahim S, et al. An international multicenter randomized study of computer-assisted oral anticoagulant dosage vs. medical staff dosage. J Thromb Haemost. 2008;6(6):935-43. https://doi.org/10.1111/j.1538-7836.2008.02959.x
21. Grzymala-Lubanski B, Själander S, Renlund H, et al. Computer aided warfarin dosing in the Swedish national quality registry AuriculA – algorithmic suggestions are performing better than manually changed doses. Thromb Res. 2013;131(2):130-4. 
https://doi.org/10.1016/j.thromres.2012.11.016
22. Lenzini P, Wadelius M, Kimmel S, et al. Integration of genetic, clinical, and INR data to refine warfarin dosing. Clin Pharmacol Ther. 2010;87(5):572-8. https://doi.org/10.1038/clpt.2010.13
23. Asiimwe IG, Blockman M, Cohen K, et al. Stable warfarin dose prediction in sub-Saharan African patients: A machine-learning approach and external validation of a clinical dose-initiation algorithm. CPT Pharmacometrics Syst Pharmacol. 2022;11(1):20-9. ttps://doi.org/10.1002/psp4.12740
24. Asiimwe IG, Waitt C, Sekaggya‐Wiltshire C, et al. Developing and validating a clinical warfarin dose‐initiation model for Black‐African patients in South Africa and Uganda. Clin Pharmacol Ther. 2021;109(6):1564‐74. https://doi.org/10.1002/cpt.2128
25. Cao H, Wu J, Zhang J. Outcomes of warfarin therapy managed by pharmacists via hospital anticoagulation clinic versus online anticoagulation clinic. Int J Clin Pharm. 2018;40(5):1072-7. https://doi.org/10.1007/s11096-018-0674-0
26. Jiang S, Lv M, Zeng Z, et al. Efficacy and safety of app-based remote warfarin management during COVID-19-related lockdown:a retrospective cohort study. J Thromb Thrombolysis. 2022;54(1):20-28. https://doi.org/10.1007/s11239-021-02630-0
27. Qian M, Zhao H, Lou Y, et al. Establishment of prediction algorithm for the Honghe minority group based on warfarin maintenance dose. Pharmacogenomics. 2022. https://doi.org/10.2217/pgs-2022-0038
28. Ndadza A, Muyambo S, Mntla P, et al. Profiling of warfarin pharmacokinetics-associated genetic variants: Black Africans portray unique genetic markers important for an African specific warfarin pharmacogenetics-dosing algorithm. J Thromb Haemost.2021;19(12):2957-2973. https://doi.org/10.1111/jth.15494
29. Manzoor BS, Cheng WH, Lee JC, et al. Quality of Pharmacist-Managed Anticoagulation Therapy in Long-Term Ambulatory Settings: A Systematic Review. Ann Pharmacother. 2017;51(12):1122-1137. https://doi.org/10.1177/1060028017721241  
30. Elewa H, Jalali F, Khudair N, et al. Evaluation of pharmacist-based compared to doctor-based anticoagulation management in Qatar. J Eval Clin Pract. 2016;22(3):433-8. https://doi.org/10.1111/jep.12504 
31. Noor A, Khan MA, Warsi A, et al. Evaluation of a pharmacist vs. Haematologist-managed anticoagulation clinic: A retrospective cohort study. Saudi Pharm J. 2021;29(10):1173-80. https://doi.org/10.1016/j.jsps.2021.08.015 
32. Zhou S, Sheng XY, Xiang Q, et al. Comparing the effectiveness of pharmacist-managed warfarin anticoagulation with other models: a systematic review and meta analysis. J Clin Pharm Ther. 2016;41(6):602-611. https://doi.org/10.1111/jcpt.12438

Most read articles by the same author(s)