2013 - Glasgow - Scotland

PAGE 2013: Model Evaluation
Hesham Al-Sallami

Evaluation of a Bayesian dose-individualisation method for enoxaparin

Hesham S Al-Sallami (1), Michael Barras (2,3), Stephen B Duffull (1)

(1) School of Pharmacy, University of Otago, Dunedin – New Zealand (2) Royal Brisbane & Women's Hospital, Brisbane, Australia (3) School of Pharmacy, University of Queensland, Brisbane, Australia

Objectives: The current approved treatment dose of the anticoagulant enoxaparin is based on total body weight and its dosing frequency is based dichotomously on creatinine clearance. Recent evidence has shown these dosing strategies to be suboptimal and adaptive dose-individualisation (based on Bayesian statistics) has been proposed as a safer and a more effective alternative. A Bayesian dose-individualisation software (TCIWorks) is available but its predictive performance of enoxaparin dosing has not yet been evaluated. The aim of this study was to evaluate TCIWorks use for enoxaparin dosing.

Methods: Demographic data, dosing history, and anti-Xa concentrations of 109 patients who received enoxaparin treatment (Barras, 2008) were entered into TCIWorks. The mean error (ME) and root of mean squared error (RMSE) for the prior predictions (calculated from patient covariates) and posterior predictions (estimated from the posterior parameter estimates) to the future observed anti-Xa concentration were calculated to determine the bias and precision of model predictions.

Results: There were a total of 238 anti-Xa measurements in the dataset: 109 first observations (mean = 4.1 mg/L), 98 second observations (mean = 8.6 mg/L), 26 third observations (mean = 6.9 mg/L), and 5 fourth observations (mean = 8 mg/L). The RMSEs for the posterior predictions decreased from 3.3 to 1.8 mg/L after the third observation. The RMSEs for the prior predictions did not improve and were 2.5, 4.2, 2.8, and 2.8 mg/L for the first, second, third, and fourth observations, respectively.

The prior was negatively biased. The posterior predictions were initially also negatively biased but this became non-significant after the third observation (-0.6, 95% CI -2.3 to 1.1).

Conclusions: TCIWorks provided acceptably accurate predictions of anti-Xa concentrations. There appears to be limited benefit in obtaining more than three observations during dose-individualisation.

References:
[1] Barras et al. CPT 2008 ; 83: 882-8.




Reference: PAGE 22 (2013) Abstr 2818 [www.page-meeting.org/?abstract=2818]
Poster: Model Evaluation
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