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Robust and adaptive anticoagulant control

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  • Peter Avery
  • Quentin Clairon
  • Robin Henderson
  • C. James Taylor
  • Emma Wilson

Abstract

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.

Suggested Citation

  • Peter Avery & Quentin Clairon & Robin Henderson & C. James Taylor & Emma Wilson, 2020. "Robust and adaptive anticoagulant control," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(3), pages 503-524, June.
    • Handle: RePEc:bla:jorssc:v:69:y:2020:i:3:p:503-524
    DOI: 10.1111/rssc.12403
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    References listed on IDEAS

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    1. Robin Henderson & Phil Ansell & Deyadeen Alshibani, 2010. "Regret-Regression for Optimal Dynamic Treatment Regimes," Biometrics, The International Biometric Society, vol. 66(4), pages 1192-1201, December.
    2. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
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