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A stochastic model for the normal tissue complication probability (NTCP) and applications
Stockholm University, Faculty of Science, Department of Mathematics.
2016 (English)In: Mathematical Medicine and Biology, ISSN 1477-8599, E-ISSN 1477-8602Article in journal (Refereed) Epub ahead of print
Abstract [en]

The normal tissue complication probability (NTCP) is a measure for the estimated side effects of a given radiation treatment schedule. Here we use a stochastic logistic birth–death process to define an organ-specific and patient-specific NTCP. We emphasize an asymptotic simplification which relates the NTCP to the solution of a logistic differential equation. This framework is based on simple modelling assumptions and it prepares a framework for the use of the NTCP model in clinical practice. As example, we consider side effects of prostate cancer brachytherapy such as increase in urinal frequency, urinal retention and acute rectal dysfunction.

Place, publisher, year, edition, pages
2016.
Keyword [en]
normal tissue complication, probability logistic birth death process, tumour control probability, radiation treatment, side effects, TCP, NTCP, brachytherapy, prostate cancer
National Category
Mathematics
Identifiers
URN: urn:nbn:se:su:diva-137846DOI: 10.1093/imammb/dqw013OAI: oai:DiVA.org:su-137846DiVA: diva2:1064616
Available from: 2017-01-12 Created: 2017-01-12 Last updated: 2017-06-16
In thesis
1. Dynamic Modelling of Communicable and Non-Communicable Diseases
Open this publication in new window or tab >>Dynamic Modelling of Communicable and Non-Communicable Diseases
2017 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis consists of two papers dealing with the stochastic dynamic modelling of one communicable and one non-communicable disease respectively. In the first paper we derive a patient- and organ-specific measure for the estimated negative side effects of radiotherapy using a stochastic logistic birth-death process. We find that the region of a maximum tolerable radiation dose can be approximated by an asymptotic simplification  and illustrate our findings on brachytherapy for prostate cancer. The second paper is concerned with the stochastic dynamic modelling of infectious disease spread in a large population to explain routine rotavirus surveillance data.  More specifically, we show that a partially observed dynamical system which includes structural variability in the transmission rates but which is simple with respect to disease progression is able to explain the available incidence data. A careful mathematical analysis addresses parameter identifiability and a model-based estimate for the basic reproduction number $R_0$ is given. As inference method we use iterated filtering which is implemented in the \texttt{R} package \texttt{pomp}, available from the comprehensive R archive network (CRAN).

Place, publisher, year, edition, pages
Department of Mathematics, Stockholm University, 2017
National Category
Mathematics
Identifiers
urn:nbn:se:su:diva-137860 (URN)
Presentation
2017-02-02, 22, House 5, Department of Mathematics, Stockholm, 13:15 (English)
Opponent
Supervisors
Available from: 2017-01-12 Created: 2017-01-12 Last updated: 2017-03-03Bibliographically approved

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