Prediction of the international normalized ratio and maintenance dose during the initiation of warfarin therapy

Abstract

Aims A pharmacokinetic/pharmacodynamic model, with Bayesian parameter estimation, was used to retrospectively predict the daily International Normalized Ratios (INRs) and the maintenance doses during the initiation of warfarin therapy in 74 inpatients. Methods INRs and maintenance doses predicted by the model were compared with the actual INRs and the eventual maintenance dose. Cases with drugs or medical conditions interacting with warfarin or receiving concurrent heparin therapy were not excluded. As the study was retrospective, model predictions of the maintenance dose were not those that were administered. Mean prediction error (MPE) and percentage absolute prediction errors (PAPE) were used to assess the model predictions.Results INR MPE ranged from −0.07 to 0.06 and median PAPE from 10% to 20%. Dose MPE ranged from −0.7 to 0.17 mg and median PAPE from 16.7% to 37.5%. Accurate and precise dose predictions were obtained after 3 or more INR feedback's. Conclusions This study shows that the model can accurately predict daily INRs and the maintenance dose in this sample of cases. The model can be incorporated into computer decision-support systems for warfarin therapy and may lead to improvement in the initiation of warfarin therapy.

Development of a Bayesian Forecasting Method for Warfarin Dose Individualisation

“…Bayesian methodologies have not been extensively applied to warfarin dose individualisation (see (40,46) for examples), and few appear to have been developed into tools for use in the clinic. One exception is a Bayesian forecaster developed in the 1980s (37) which is still available on the internet (51).…”

“…Of the remaining models, six did not include adequate details of parameter estimates or error models to enable simulation (e.g. (39)(40)(41)(42)(43)). The remaining four models (28,(44)(45)(46) were included in this research.…”

13. From telemedicine to modeling and proactive medicine

“…In this way they are often used for improving therapies, e.g. warfarin or insulin dosing [21], immunotherapy [22] or chemotherapy [23,24]. Personalized models of a therapy's effect are used by physicians to support them in the therapeutic process, thus their accuracy and comprehension is essential.…”

A Retrospective Comparative Study of Three Data Modelling Techniques in Anticoagulation Therapy

“…There are several existing software products that support anticoagulation clinicians and several studies into their efficacy [2,3,4,5,6]. Other studies have been undertaken to investigate the utility of particular machine learning technologies using anticoagulation data [7,8,9,10,11].…”