Introduction: Pharmacometrics time-to-event (TTE) modelling complements therapeutic drug monitoring (TDM) in assessing drug efficacy and safety. In atrial fibrillation (AF) patients on rivaroxaban, heart failure (HF) is an independent predictor of bleeding. Given rivaroxaban’s high protein binding and hepatic metabolism, organ congestion in HF may influence drug disposition and anticoagulation outcomes.
Objectives: This study aimed to identify risk factors for major bleeding after rivaroxaban initiation in patients with and without HF using pharmacometrics TTE modelling, focusing on HF severity markers—serum albumin and right ventricular (RV) function.
Methods: Retrospective data from rivaroxaban-treated AF patients at the National Heart Institute were analysed using Nonlinear Mixed-Effect Modelling (NONMEM) software for parametric TTE modelling. Model validation included Kaplan-Meier visual predictive check (KM-VPC) and sampling-importance resampling (SIR).
Results: The final Weibull model indicated a decreasing hazard, with the highest bleeding risk early in treatment. Among 363 patients (876 observations), 32 experienced major bleeding over a median follow-up of 2.64 years (follow up time ranged from 1 day to 10.12 years). Higher serum albumin (>35 g/L) and tricuspid annular plane systolic excursion (TAPSE >1.8 cm) reduced bleeding risk by 18.5% (aHR 0.81; 95% CI 0.78–0.86) and 81.4% (aHR 0.19; 95% CI 0.08–0.43), respectively. Concomitant use of aspirin, dual antiplatelet therapy, clopidogrel, and hypertension significantly increased bleeding risk.
Conclusions: Serum albumin and RV function may serve as protective markers, highlighting the impact of HF-related hypoalbuminaemia and hepatic congestion on drug disposition and anticoagulation outcomes. Integrating these factors into risk stratification may improve patient management.
Keywords: rivaroxaban, atrial fibrillation, major bleeding, albumin, right ventricular function