Rights statement: This is the peer reviewed version of the following article:Avery, P., Clairon, Q., Henderson, R., James Taylor, C. and Wilson, E. (2020), Robust and adaptive anticoagulant control. J. R. Stat. Soc. C. doi:10.1111/rssc.12403 which has been published in final form at https://rss.onlinelibrary.wiley.com/doi/10.1111/rssc.12403 This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.
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Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
| <mark>Journal publication date</mark> | 1/06/2020 |
|---|---|
| <mark>Journal</mark> | Journal of the Royal Statistical Society: Series C (Applied Statistics) |
| Issue number | 3 |
| Volume | 69 |
| Number of pages | 22 |
| Pages (from-to) | 503-524 |
| Publication Status | Published |
| Early online date | 15/03/20 |
| <mark>Original language</mark> | English |
We consider a control theory approach to adaptive dose allocation of anticoagulants, based on an analysis of records of 152 patients on long-term warfarin treatment. We consider a selection of statistical models for the relationship between the dose of drug and subsequent blood clotting speed, measured through the international normalized ratio. Our main focus is on subsequent use of the model in guiding the choice of the next dose adaptively as patient-specific information accrues. We compare a naive long-term approach with a proportional-integral-plus method, with parameters estimated by either linear quadratic optimization or by stochastic resource allocation. We demonstrate advantages of the control approaches in comparison with a naive approach in simulations and through calculation of robust stability margins for the observed data.