Why the study?
Warfarin's narrow therapeutic window and individual variability make dose determination difficult after mechanical valve replacement, necessitating advanced dosing algorithms.
Does a pharmacogenetic algorithm incorporating VKORC1, CYP2C9, and GGCX polymorphisms accurately predict warfarin maintenance dose in South Chinese patients after mechanical heart valve replacement?
Does a pharmacogenetic algorithm incorporating VKORC1, CYP2C9, and GGCX polymorphisms accurately predict warfarin maintenance dose in South Chinese patients after mechanical heart valve replacement?
A new pharmacogenetic algorithm incorporating VKORC1, CYP2C9, and GGCX polymorphisms along with age and body surface area explains 61.7% of warfarin dose variability in South Chinese patients after mechanical valve replacement.
Model explains 62% dose variability with 69% ideal predictions in southern Chinese patients; leaves open prospective validation before clinical use.
BACKGROUND: Warfarin is the most recommended oral anticoagulant after artificial mechanical valve replacement therapy. However, the narrow therapeutic window and varying safety and efficacy in individuals make dose determination difficult. It may cause adverse events such as hemorrhage or thromboembolism. Therefore, advanced algorithms are urgently required for the use of warfarin. OBJECTIVE: To establish a warfarin dose model for patients after prosthetic mechanical valve replacement in southern China in combination with clinical and genetic variables, and to improve the accuracy and ideal prediction percentage of the model. METHODS: Clinical data of 476 patients were tracked and recorded in detail. The gene polymorphisms of VKORC1 (rs9923231, rs9934438, rs7196161, and rs7294), CYP2C9 (rs1057910), CYP1A2 (rs2069514), GGCX (rs699664), and UGT1A1 (rs887829) were determined using Sanger sequencing. Multiple linear regressions were used to analyze the gene polymorphisms and the contribution of clinical data variables; the variables that caused multicollinearity were screened stepwise and excluded to establish an algorithm model for predicting the daily maintenance dose of warfarin. The ideal predicted percentage was used to test clinical effectiveness. RESULTS: A total of 395 patients were included. Univariate linear regression analysis suggested that CYP1A2 (rs2069514) and UGT1A1 (rs887829) were not associated with the daily maintenance dose of warfarin. The new algorithm model established based on multiple linear regression was as follows: Y = 1.081 - 0.011 (age) + 1.532 (body surface area)-0.807 (rs9923231 AA) + 1.788 (rs9923231 GG) + 0.530 (rs1057910 AA)-1.061 (rs1057910 AG)-0.321 (rs699664 AA). The model accounted for 61.7% of individualized medication differences, with an ideal prediction percentage of 69%. CONCLUSION: GGCX (rs699664) may be a potential predictor of warfarin dose, and our newly established model is expected to guide the individualized use of warfarin in clinical practice in southern China.
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Li et al. (2022) studied this question.
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