Robust response-guided dosing

被引：2

作者：

Sinha, Saumya ^{[1
]}

Kotas, Jakob ^{[1
]}

Ghate, Archis ^{[2
]}

机构：

[1] Univ Washington, Dept Appl Math, Seattle, WA 98195 USA

[2] Univ Washington, Ind & Syst Engn, Box 352650, Seattle, WA 98195 USA

来源：

OPERATIONS RESEARCH LETTERS | 2016年 / 44卷 / 03期

基金：

美国国家科学基金会;

关键词：

Stochastic dose-response; Robust Markov decision processes; Medical treatment planning;

D O I：

10.1016/j.orl.2016.03.012

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

In response-guided dosing (RGD), doses are adapted to the uncertain progression of each patient's disease condition. A stochastic dynamic program was recently developed for RGD. We study its robust counterpart, where the dose response, distribution belongs to an uncertainty set. For interval uncertainty sets, we prove that it is optimal to administer higher doses in worsening disease. When a certain scaling of a nominal distribution describes the interval, optimal doses also increase in the scaling parameter. Theory is illustrated via numerical results. (C) 2016 Elsevier B.V. All rights reserved.

引用

页码：394 / 399

页数：6

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