Mathematical Modelling for Patient Selection in Proton Therapy

被引：13
作者：
Mee, T. [1 ,2 ,3 ]
Kirkby, N. F. [1 ,2 ,3 ]
Kirkby, K. J. [1 ,2 ,3 ]
机构：
[1] Univ Manchester, Fac Biol Med & Hlth, Sch Med Sci, Div Canc Sci, Manchester, Lancs, England
[2] Christie NHS Fdn Trust, Manchester, Lancs, England
[3] Univ Manchester, Manchester Acad Hlth Sci Ctr, NIHR Manchester Biomed Res Ctr, Manchester, Lancs, England
来源：
CLINICAL ONCOLOGY | 2018年 / 30卷 / 05期
基金：
英国工程与自然科学研究理事会;
关键词：
Discrete event simulation; mathematical modelling; NTCP; patient selection; proton therapy; DISCRETE-EVENT SIMULATION; TUBE-FEEDING DEPENDENCE; COST-EFFECTIVENESS; NORMAL TISSUE; RADIOTHERAPY UTILIZATION; PARTICLE RADIOTHERAPY; CLINICAL-OUTCOMES; RADIATION-THERAPY; MODALITY THERAPY; MALTHUS PROGRAM;
D O I：
10.1016/j.clon.2018.01.007
中图分类号：
R73 [肿瘤学];
学科分类号：
100214 ;
摘要：
Proton beam therapy (PBT) is still relatively new in cancer treatment and the clinical evidence base is relatively sparse. Mathematical modelling offers assistance when selecting patients for PBT and predicting the demand for service. Discrete event simulation, normal tissue complication probability, quality- adjusted life-years and Markov Chain models are all mathematical and statistical modelling techniques currently used but none is dominant. As new evidence and outcome data become available from PBT, comprehensive models will emerge that are less dependent on the specific technologies of radiotherapy planning and delivery. (C) 2018 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码：299 / 306
页数：8
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