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Optimizing Predictive Performance of Bayesian Forecasting for Vancomycin Concentration in Intensive Care Patients.
Pharmaceutical Research ( IF 3.7 ) Pub Date : 2020-08-23 , DOI: 10.1007/s11095-020-02908-7 Tingjie Guo 1, 2, 3 , Reinier M van Hest 2 , Laura B Zwep 3, 4 , Luca F Roggeveen 1 , Lucas M Fleuren 1 , Rob J Bosman 5 , Peter H J van der Voort 5 , Armand R J Girbes 1 , Ron A A Mathot 2 , Paul W G Elbers 1 , Johan G C van Hasselt 3
中文翻译:
优化重症监护患者万古霉素浓度贝叶斯预测的预测性能。
更新日期:2020-08-23
Pharmaceutical Research ( IF 3.7 ) Pub Date : 2020-08-23 , DOI: 10.1007/s11095-020-02908-7 Tingjie Guo 1, 2, 3 , Reinier M van Hest 2 , Laura B Zwep 3, 4 , Luca F Roggeveen 1 , Lucas M Fleuren 1 , Rob J Bosman 5 , Peter H J van der Voort 5 , Armand R J Girbes 1 , Ron A A Mathot 2 , Paul W G Elbers 1 , Johan G C van Hasselt 3
Affiliation
Purpose
Bayesian forecasting is crucial for model-based dose optimization based on therapeutic drug monitoring (TDM) data of vancomycin in intensive care (ICU) patients. We aimed to evaluate the performance of Bayesian forecasting using maximum a posteriori (MAP) estimation for model-based TDM.Methods
We used a vancomycin TDM data set (n = 408 patients). We compared standard MAP-based Bayesian forecasting with two alternative approaches: (i) adaptive MAP which handles data over multiple iterations, and (ii) weighted MAP which weights the likelihood contribution of data. We evaluated the percentage error (PE) for seven scenarios including historical TDM data from the preceding day up to seven days.Results
The mean of median PEs of all scenarios for the standard MAP, adaptive MAP and weighted MAP method were − 7.7%, −4.5% and − 6.7%. The adaptive MAP also showed the narrowest inter-quartile range of PE. In addition, regardless of MAP method, including historical TDM data further in the past will increase prediction errors.Conclusions
The proposed adaptive MAP method outperforms standard MAP in predictive performance and may be considered for improvement of model-based dose optimization. The inclusion of historical data beyond either one day (standard MAP and weighted MAP) or two days (adaptive MAP) reduces predictive performance.中文翻译:
优化重症监护患者万古霉素浓度贝叶斯预测的预测性能。