Objective: To develop and evaluate a warfarin-dosing algorithm method which can be used to guide the adjustment of warfarin maintenance dose in Chinese Han population.
Methods: A total of 512 patients with steady warfarin taking were recruited from Beijing Hospital during May 2012 to December 2014. Indications for warfarin prescribing included prosthetic heart valve, atrial fibrillation and pulmonary embolism. Genomic DNAs were extracted from blood samples and used for the genetic polymorphism analysis of VKORC1 and CYP2C9 (include (*)3 and (*)13 alleles). Warfarin dose, demographic variabilities and amiodarone compliance were recorded during regular visit. These patients were randomly divided into groups using the method of random number table, 384 patients were randomly selected as derivation group, the remaining 128 cases as the validation group.Using data from derivation group, a warfarin-dosing algorithm was established based on the genetic information, demographic characteristics and concomitant compliance by a multiple linear regression analysis parameter. Then the accuracy of newly developed algorithm method was further evaluated by comparing the predicting dose with the actual dose in the validation group.
Results: The stable dose of warfarin was tightly associated with factors like age, height, weight, VKORC1 -1639G>A, CYP2C9(*)3, CYP2C9(*)13 and amiodarone usage. Newly developed algorithm method exhibited better prediction effect (R(2)=0.682, P<0.01) as compared with that of previously reported algorithm methods. The weights of VKORC1 and CYP2C9 for predicting of warfarin dosage were estimated to more than 50%. Using this method, 62.5% of patients in the validation group could be well recognized, in which the predicting dose of warfarin was within 20% of the actual dose, and only 7.81% patients showed underestimated prediction warfarin dose while 29.69% patients showed overestimated values.
Conclusion: Newly developed algorithm method can be used for the guidance of warfarin maintenance dose adjustment in Chinese Han population.