The effectiveness of split tablet dosing versus alternate-day dosing of warfarin: a randomized control trial

Due to large dosage variation, a variety of warfarin prescription regimens are utilized for specific doses such as tablet splitting, or pill strength alternating. The clinical comparison between the two is lacking. We hypothesize that both approaches result in different times in therapeutic range. We randomized patients with specific warfarin dosage and stable INR for 6 months or longer to receive the whole tablet, alternate-day dosing or the split tablet, same daily-dosing regimen without initial dose change and followed them every 6 weeks for 6 months. The primary outcome was a time in therapeutic range of 2.0–3.0. The secondary outcomes included dosage, compliance, INR, anticoagulant-related events. A total of 66 patients were enrolled, 32 randomly assigned to the split tablet regimen (group S) and 34 to the alternate-day regimen (group A) with two withdrawers. The mean age was 58.6 ± 8.5 years. All baseline characteristics of both groups were similar. The average time in therapeutic range was 72.8 ± 25.4% in group S and 74.9 ± 22.0% in group A (p = 0.72). There were no significant differences in warfarin dosage, compliance, INR and, complications between the two groups. Both warfarin prescription methods, the split tablet and the alternate-day had comparable time in the therapeutic range.

The Effectiveness of Split Tablet Dosing Versus Alternate-Day Dosing of Warfarin: A Randomized Control Trial

Due to large dosage variation, a variety of warfarin prescription regimens are utilized for specific doses such as tablet splitting, or pill strength alternating. The clinical comparison between the two is lacking. We hypothesize that both approaches result in different times in therapeutic range. We randomized patients with specific warfarin dosage and stable INR for 6 months or longer to receive the whole tablet, alternate-day dosing or the split tablet, same daily-dosing regimen without initial dose change and followed them every 6 weeks for 6 months. The primary outcome was a time in therapeutic range of 2.0 to 3.0. The secondary outcomes included dosage, compliance, INR, anticoagulant-related events. A total of 66 patients were enrolled, 32 randomly assigned to the split tablet regimen (group S) and 34 to the alternate-day regimen (group A) with two withdrawals. The mean age was 58.6 ± 8.5 years. All baseline characteristics of both groups were similar. The average time in therapeutic range was 72.8 ± 25.4% in group S and 74.9 ± 22.0% in group A (p = 0.72). There were no significant differences in warfarin dosage, compliance, INR and, complications between the two groups. Both warfarin prescription methods, the split tablet and the alternate-day had comparable time in the therapeutic range.

Plasma miRNA profiles associated with stable warfarin dosage in Chinese patients

Background We used bioinformatic analysis and quantitative reverse transcription polymerase chain reaction (RT-qPCR) assays to investigate the association between plasma microRNAs (miRNAs) and stable warfarin dosage in a Chinese Han population. Methods Bioinformatics analysis was used to screen out potential warfarin dose-associated miRNAs. Three plasma miRNAs were validated in 99 samples by RT-qPCR. Kruskal–Wallis test and multivariate logistic regression were used to compare differences in plasma miRNAs expression levels between three warfarin dosage groups. Results There were significant between-group differences among the three dose groups for hsa-miR-133b expression (p = 0.005), but we observed an “n-shaped” dose-dependent curve rather than a linear relationship. Expression levels of hsa-miR-24-3p (p = 0.475) and hsa-miR-1276 (p = 0.558) were not significantly different in the multivariate logistic regression. Conclusion miRNAs have received extensive attention as ideal biomarkers and possible therapeutic targets for various diseases. However, they are not yet widely used in precision medicine. Our results indicate that hsa-miR-133b may be a possible reference factor for the warfarin dosage algorithm. These findings emphasize the importance of a comprehensive evaluation of complex relationships in warfarin dose prediction models and provide new avenues for future pharmacogenomics studies.

DBCSMOTE: a clustering-based oversampling technique for data-imbalanced warfarin dose prediction

Background Vitamin K antagonist (warfarin) is the most classical and widely used oral anticoagulant with assuring anticoagulant effect, wide clinical indications and low price. Warfarin dosage requirements of different patients vary largely. For warfarin daily dosage prediction, the data imbalance in dataset leads to inaccurate prediction on the patients of rare genotype, who usually have large stable dosage requirement. To balance the dataset of patients treated with warfarin and improve the predictive accuracy, an appropriate partition of majority and minority groups, together with an oversampling method, is required. Method To solve the data-imbalance problem mentioned above, we developed a clustering-based oversampling technique denoted as DBCSMOTE, which combines density-based spatial clustering of application with noise (DBCSCAN) and synthetic minority oversampling technique (SMOTE). DBCSMOTE automatically finds the minority groups by acquiring the association between samples in terms of the clinical features/genotypes and the warfarin dosage, and creates an extended dataset by adding the new synthetic samples of majority and minority groups. Meanwhile, two ensemble models, boosted regression tree (BRT) and random forest (RF), which are built on the extended dataset generateed by DBCSMOTE, accomplish the task of warfarin daily dosage prediction. Results DBCSMOTE and the comparison methods were tested on the datasets derived from our Hospital and International Warfarin Pharmacogenetics Consortium (IWPC). As the results, DBCSMOTE-BRT obtained the highest R-squared (R2) of 0.424 and the smallest mean squared error (mse) of 1.08. In terms of the percentage of patients whose predicted dose of warfarin is within 20% of the actual stable therapeutic dose (20%-p), DBCSMOTE-BRT can achieve the largest value of 47.8% among predictive models. The more important thing is that DBCSMOTE saved about 68% computational time to achieve the same or better performance than the Evolutionary SMOTE, which was the best oversampling method in warfarin dose prediction by far. Meanwhile, in warfarin dose prediction, it is discovered that DBCSMOTE is more effective in integrating BRT than RF for warfarin dose prediction. Conclusion Our finding is that the genotypes, CYP2C9 and VKORC1, no doubt contribute to the predictive accuracy. It was also discovered left atrium diameter, glutamic pyruvic transaminase and serum creatinine included in the model actually improved the predictive accuracy; When congestive heart failure, diabetes mellitus and valve replacement were absent in DBCSMOTE-BRT/RF, the predictive accuracy of DBCSMOTE-BRT/RF decreased. The oversampling ratio and number of minority clusters have a large impact on the effect of oversampling. According to our test, the predictive accuracy was high when the number of minority clusters was 6 ~ 8. The oversampling ratio for small minority clusters should be large (> 1.2) and for large minority clusters should be small (< 0.2). If the dataset becomes larger, the DBCSMOTE would be re-optimized and its BRT/RF model should be re-trained. DBCSMOTE-BRT/RF outperformed the current commonly-used tool called Warfarindosing. As compared to Evolutionary SMOTE-BRT and RF models, DBCSMOTE-BRT and RF models take only a small computational time to achieve the same or higher performance in many cases. In terms of predictive accuracy, RF is not as good as BRT. However, RF still has a powerful ability in generating a highly accurate model as the dataset increases; the software “WarfarinSeer v2.0” is a test version, which packed DBCSMOTE-BRT/RF. It could be a convenient tool for clinical application in warfarin treatment.

Competitive tight-binding inhibition of VKORC1 underlies warfarin dosage variation and antidotal efficacy

Dose control of warfarin is a major complication in anticoagulation therapy and overdose is reversed by the vitamin K antidote. Improving the dosage management and antidotal efficacy requires mechanistic understanding. Here we find that effects of the major predictor of warfarin dosage, SNP −1639 G&gt;A, follow a general correlation that warfarin 50% inhibitory concentration decreases with cellular level of vitamin K epoxide reductase (VKORC1), suggesting stoichiometric inhibition. Characterization of the inhibition kinetics required the use of microsomal VKORC1 with a native reductant, glutathione, that enables effective warfarin inhibition in vitro. The kinetics data can be fitted with the Morrison equation, giving a nanomolar inhibition constant and demonstrating that warfarin is a tight-binding inhibitor. However, warfarin is released from purified VKORC1-warfarin complex with increasing amount of vitamin K, indicating competitive inhibition. The competition occurs also in cells, resulting in rescued VKORC1 activity that augments the antidotal effects of vitamin K. Taken together, warfarin is a competitive inhibitor that binds VKORC1 tightly and inhibits at a stoichiometric (1:1) concentration, whereas exceeding the VKORC1 level results in warfarin overdose. Thus, warfarin dosage control should use VKORC1 level as a major indicator, and improved antidotes may be designed based on their competition with warfarin.