The case for dosing dabigatran: how tailoring dose to patient renal function, weight and age could improve the benefit–risk ratio

Abstract

Dabigatran is increasingly being used in clinical practice for the thromboprophylaxis in atrial fibrillation as a convenient therapy that needs no drug level monitoring. However, analysis of the data of the same clinical trial that led to the adoption of dabigatran in fixed-dosing regimens has indicated a small subgroup of patients that could be either over-treated, risking bleeding, or under-treated, risking embolism. Additional post-marketing data lends support to the favorable therapeutic profile of dabigatran but at the same time raises doubts about patient characteristics such as weight, age, renal function and their pharmacokinetic effects that, in some cases, could be serious enough to expose a minority of patients to risk. We will present a clinical case of a patient with an ischemic stroke while on dabigatran that was found with low dabigatran plasma levels and we will discuss the currently available data on the effects of inherent patient characteristics on dabigatran pharmacokinetics, the clinical impact of dabigatran plasma levels on safety and efficacy as well as the possibility of improving the risk-benefit profile of this agent by tailoring the dose for selected patient groups.

Rivaroxaban and apixaban induce clotting factor Xa fibrinolytic activity

“…The apparent difference between these is surprising, as they target nearly identical positions within the FXa catalytic site , but it may be attributable to the five‐fold higher affinity of apixaban. Interestingly, as compared with the use of warfarin for stroke prevention in patients with atrial fibrillation, apixaban may give a somewhat improved outcome relative to thrombin‐specific dabigatran . Analogous thrombin‐specific DOACs, i.e.…”

Being precise with anticoagulation to reduce adverse drug reactions: are we there yet?

“…Increased BMI is strongly associated with increased glomerular filtration rates (GFRs) [ 89 ] and increased drug clearance [ 90 ]. Hence the inverse correlation between weight and dabigatran levels could impact efficacy in very obese patients [ 91 ]. Two case studies of incident ischaemic stroke [ 92 , 93 ] have been reported in obese patients (BMI > 39 kg/m 2 ) on long-term anticoagulation with dabigatran for AF.…”

Refining estimates of prescription durations by using observed covariates in pharmacoepidemiologic databases: Necessary refinements to stimulate alternative approaches

“…Moreover, dose is a more reasonable response variable to depend on individual characteristics. For example, it can depend on age (e.g., the bleeding risk under the direct oral anticoagulant dabigatran 5,6 or blood pressure targets with antihypertensive drugs 7 ), sex (e.g., a more sensitive response to beta blockers 8 or antipsychotics 9,10 ), indication (e.g., angiotensin-converting enzyme inhibitors to treat hypertension or heart failure 11 ), comorbidity (e.g., antihypertensive drugs in patients with or without diabetes mellitus, 7 direct oral anticoagulants and renal insufficiency, or previous adverse events 12 ), or comedication (e.g., combined antihypertensive therapy 13 To explore the potential of Støvring's idea, 1 we adapted our recent modeling and simulation framework of our comparative method evaluation. 3 Although the distribution of administered daily doses and their ratio to the dispensed dose unit are still based on primary data from an observational cohort, 15,16 we introduce random variables to be related to this measure and can therefore be used to predict "true" doses in situations of only single redemptions.…”

“…Moreover, dose is a more reasonable response variable to depend on individual characteristics. For example, it can depend on age (e.g., the bleeding risk under the direct oral anticoagulant dabigatran or blood pressure targets with antihypertensive drugs), sex (e.g., a more sensitive response to beta blockers or antipsychotics), indication (e.g., angiotensin‐converting enzyme inhibitors to treat hypertension or heart failure), comorbidity (e.g., antihypertensive drugs in patients with or without diabetes mellitus, direct oral anticoagulants and renal insufficiency, or previous adverse events), or comedication (e.g., combined antihypertensive therapy), to name just a few. Beyond comprehensive brand information, insurance claims data usually provide such information by coded diagnoses.…”