Optimization of vitamin K antagonist drug dose finding by replacement of the international normalized ratio by a bidirectional factor: validation of a new algorithm.

UNLABELLED: ESSENTIALS: We developed a new algorithm to optimize vitamin K antagonist dose finding. Validation was by comparing actual dosing to algorithm predictions. Predicted and actual dosing of well performing centers were highly associated. The method is promising and should be tested in a randomized trial. BACKGROUND: Oral vitamin K antagonists (VKAs) have a narrow therapeutic window and thus require frequent monitoring of its intensity by the international normalized ratio (INR). Improvement of VKA dosing defined as more time in therapeutic range (TTR) can reduce thrombotic disease and bleeding. Computerized decision support programs (CDSs) are used to optimize VKA dosing, but the effects are heterogeneous. CDSs significantly improve the proportion of time in the therapeutic INR range for initiation therapy but not the quality of anticoagulant management in an outpatient setting. One of the major problems of VKA dose finding is that the INR is a ratio and does not present linearity. We developed a new dose-finding algorithm, based on a novel bidirectional factor (BF). This BF is linear transformation of the nonlinear INR. METHODS: We compared the outcomes of the new algorithm, called BF-N, with dose finding performed at three highly ranked Dutch anticoagulation centers, using both acenocoumarol and phenprocoumon. RESULTS: The outcomes of the BF-N algorithm showed a linear correlation with VKA doses of the three centers (y = 1.001x, r(2) 0.999 for acenocoumarol and y = 0.999x, r(2) 0.999 for phenprocoumon), with a standard deviation of 3.83%. The rate of automated dosage proposals increased to 100%. CONCLUSION: The BF-N algorithm performs well in real-life settings and increases the rate of automated dosage proposals. The algorithm can be easily built into existing CDSs. Experienced staff remains necessary for complicated situations. The new algorithm needs to be evaluated in a prospective trial.