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Evaluation of the predictive performance of Bayesian dosing for warfarin in Chinese patients
Jing Dong1, Guo-Hua Shi1, Man Lu1
1Department of Pharmacy, Gongli Hospital, The Second Military Medical University, 219 Miaopu Road, Shanghai 200135, PR China.
Aim:
To evaluate the accuracy and predictive performance of Bayesian dosing for warfarin in Chinese patients.
Materials & Methods:
Six multiple linear regression algorithms (Wei, Lou, Miao, Huang, Gage and IWPC) and a Bayesian method implemented in Warfarin Dose Calculator were compared with each other.
Results:
Six multiple linear regression warfarin dosing algorithms had similar predictive ability, except Miao and Lou. The mean prediction error of Bayesian priori and posteriori method were 0.01 mg/day (95% CI: -0.18 to 0.19) and 0.17 mg/day (95% CI: -0.05 to 0.29), respectively, and Bayesian posteriori method demonstrated better performance in all dose ranges.
Conclusion:
The Bayesian method showed a good potential for warfarin maintenance dose prediction in Chinese patients requiring less than 6 mg/day.
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