Comparison of Timed Automata with Discrete Event Simulation for Modeling of Biomarker-Based Treatment Decisions

An Illustration for Metastatic Castration-Resistant Prostate Cancer

Koen Degeling, Stefano Schivo, Niven Mehra, Hendrik Koffijberg, Rom Langerak, Johann S de Bono, Maarten J IJzerman

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

BACKGROUND: With the advent of personalized medicine, the field of health economic modeling is being challenged and the use of patient-level dynamic modeling techniques might be required.

OBJECTIVES: To illustrate the usability of two such techniques, timed automata (TA) and discrete event simulation (DES), for modeling personalized treatment decisions.

METHODS: An early health technology assessment on the use of circulating tumor cells, compared with prostate-specific antigen and bone scintigraphy, to inform treatment decisions in metastatic castration-resistant prostate cancer was performed. Both modeling techniques were assessed quantitatively, in terms of intermediate outcomes (e.g., overtreatment) and health economic outcomes (e.g., net monetary benefit). Qualitatively, among others, model structure, agent interactions, data management (i.e., importing and exporting data), and model transparency were assessed.

RESULTS: Both models yielded realistic and similar intermediate and health economic outcomes. Overtreatment was reduced by 6.99 and 7.02 weeks by applying circulating tumor cell as a response marker at a net monetary benefit of -€1033 and -€1104 for the TA model and the DES model, respectively. Software-specific differences were observed regarding data management features and the support for statistical distributions, which were considered better for the DES software. Regarding method-specific differences, interactions were modeled more straightforward using TA, benefiting from its compositional model structure.

CONCLUSIONS: Both techniques prove suitable for modeling personalized treatment decisions, although DES would be preferred given the current software-specific limitations of TA. When these limitations are resolved, TA would be an interesting modeling alternative if interactions are key or its compositional structure is useful to manage multi-agent complex problems.

Original languageEnglish
Pages (from-to)1411-1419
Number of pages9
JournalValue in Health
Volume20
Issue number10
DOIs
Publication statusPublished - Dec 2017

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Castration
Circulating Neoplastic Cells
Prostatic Neoplasms
Software
Biomarkers
Economics
Health
Statistical Distributions
Biomedical Technology Assessment
Precision Medicine
Prostate-Specific Antigen
Radionuclide Imaging
Therapeutics
Bone and Bones
Medical Overuse

Keywords

  • Biomarkers, Tumor/metabolism
  • Clinical Decision-Making
  • Computer Simulation
  • Decision Support Techniques
  • Humans
  • Male
  • Models, Economic
  • Precision Medicine/methods
  • Prostate-Specific Antigen/metabolism
  • Prostatic Neoplasms, Castration-Resistant/pathology
  • Radionuclide Imaging/methods
  • Technology Assessment, Biomedical/methods
  • Time Factors

Cite this

Degeling, Koen ; Schivo, Stefano ; Mehra, Niven ; Koffijberg, Hendrik ; Langerak, Rom ; de Bono, Johann S ; IJzerman, Maarten J. / Comparison of Timed Automata with Discrete Event Simulation for Modeling of Biomarker-Based Treatment Decisions : An Illustration for Metastatic Castration-Resistant Prostate Cancer. In: Value in Health. 2017 ; Vol. 20, No. 10. pp. 1411-1419.
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title = "Comparison of Timed Automata with Discrete Event Simulation for Modeling of Biomarker-Based Treatment Decisions: An Illustration for Metastatic Castration-Resistant Prostate Cancer",
abstract = "BACKGROUND: With the advent of personalized medicine, the field of health economic modeling is being challenged and the use of patient-level dynamic modeling techniques might be required.OBJECTIVES: To illustrate the usability of two such techniques, timed automata (TA) and discrete event simulation (DES), for modeling personalized treatment decisions.METHODS: An early health technology assessment on the use of circulating tumor cells, compared with prostate-specific antigen and bone scintigraphy, to inform treatment decisions in metastatic castration-resistant prostate cancer was performed. Both modeling techniques were assessed quantitatively, in terms of intermediate outcomes (e.g., overtreatment) and health economic outcomes (e.g., net monetary benefit). Qualitatively, among others, model structure, agent interactions, data management (i.e., importing and exporting data), and model transparency were assessed.RESULTS: Both models yielded realistic and similar intermediate and health economic outcomes. Overtreatment was reduced by 6.99 and 7.02 weeks by applying circulating tumor cell as a response marker at a net monetary benefit of -€1033 and -€1104 for the TA model and the DES model, respectively. Software-specific differences were observed regarding data management features and the support for statistical distributions, which were considered better for the DES software. Regarding method-specific differences, interactions were modeled more straightforward using TA, benefiting from its compositional model structure.CONCLUSIONS: Both techniques prove suitable for modeling personalized treatment decisions, although DES would be preferred given the current software-specific limitations of TA. When these limitations are resolved, TA would be an interesting modeling alternative if interactions are key or its compositional structure is useful to manage multi-agent complex problems.",
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author = "Koen Degeling and Stefano Schivo and Niven Mehra and Hendrik Koffijberg and Rom Langerak and {de Bono}, {Johann S} and IJzerman, {Maarten J}",
year = "2017",
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Comparison of Timed Automata with Discrete Event Simulation for Modeling of Biomarker-Based Treatment Decisions : An Illustration for Metastatic Castration-Resistant Prostate Cancer. / Degeling, Koen; Schivo, Stefano; Mehra, Niven; Koffijberg, Hendrik; Langerak, Rom; de Bono, Johann S; IJzerman, Maarten J.

In: Value in Health, Vol. 20, No. 10, 12.2017, p. 1411-1419.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Comparison of Timed Automata with Discrete Event Simulation for Modeling of Biomarker-Based Treatment Decisions

T2 - An Illustration for Metastatic Castration-Resistant Prostate Cancer

AU - Degeling, Koen

AU - Schivo, Stefano

AU - Mehra, Niven

AU - Koffijberg, Hendrik

AU - Langerak, Rom

AU - de Bono, Johann S

AU - IJzerman, Maarten J

PY - 2017/12

Y1 - 2017/12

N2 - BACKGROUND: With the advent of personalized medicine, the field of health economic modeling is being challenged and the use of patient-level dynamic modeling techniques might be required.OBJECTIVES: To illustrate the usability of two such techniques, timed automata (TA) and discrete event simulation (DES), for modeling personalized treatment decisions.METHODS: An early health technology assessment on the use of circulating tumor cells, compared with prostate-specific antigen and bone scintigraphy, to inform treatment decisions in metastatic castration-resistant prostate cancer was performed. Both modeling techniques were assessed quantitatively, in terms of intermediate outcomes (e.g., overtreatment) and health economic outcomes (e.g., net monetary benefit). Qualitatively, among others, model structure, agent interactions, data management (i.e., importing and exporting data), and model transparency were assessed.RESULTS: Both models yielded realistic and similar intermediate and health economic outcomes. Overtreatment was reduced by 6.99 and 7.02 weeks by applying circulating tumor cell as a response marker at a net monetary benefit of -€1033 and -€1104 for the TA model and the DES model, respectively. Software-specific differences were observed regarding data management features and the support for statistical distributions, which were considered better for the DES software. Regarding method-specific differences, interactions were modeled more straightforward using TA, benefiting from its compositional model structure.CONCLUSIONS: Both techniques prove suitable for modeling personalized treatment decisions, although DES would be preferred given the current software-specific limitations of TA. When these limitations are resolved, TA would be an interesting modeling alternative if interactions are key or its compositional structure is useful to manage multi-agent complex problems.

AB - BACKGROUND: With the advent of personalized medicine, the field of health economic modeling is being challenged and the use of patient-level dynamic modeling techniques might be required.OBJECTIVES: To illustrate the usability of two such techniques, timed automata (TA) and discrete event simulation (DES), for modeling personalized treatment decisions.METHODS: An early health technology assessment on the use of circulating tumor cells, compared with prostate-specific antigen and bone scintigraphy, to inform treatment decisions in metastatic castration-resistant prostate cancer was performed. Both modeling techniques were assessed quantitatively, in terms of intermediate outcomes (e.g., overtreatment) and health economic outcomes (e.g., net monetary benefit). Qualitatively, among others, model structure, agent interactions, data management (i.e., importing and exporting data), and model transparency were assessed.RESULTS: Both models yielded realistic and similar intermediate and health economic outcomes. Overtreatment was reduced by 6.99 and 7.02 weeks by applying circulating tumor cell as a response marker at a net monetary benefit of -€1033 and -€1104 for the TA model and the DES model, respectively. Software-specific differences were observed regarding data management features and the support for statistical distributions, which were considered better for the DES software. Regarding method-specific differences, interactions were modeled more straightforward using TA, benefiting from its compositional model structure.CONCLUSIONS: Both techniques prove suitable for modeling personalized treatment decisions, although DES would be preferred given the current software-specific limitations of TA. When these limitations are resolved, TA would be an interesting modeling alternative if interactions are key or its compositional structure is useful to manage multi-agent complex problems.

KW - Biomarkers, Tumor/metabolism

KW - Clinical Decision-Making

KW - Computer Simulation

KW - Decision Support Techniques

KW - Humans

KW - Male

KW - Models, Economic

KW - Precision Medicine/methods

KW - Prostate-Specific Antigen/metabolism

KW - Prostatic Neoplasms, Castration-Resistant/pathology

KW - Radionuclide Imaging/methods

KW - Technology Assessment, Biomedical/methods

KW - Time Factors

U2 - 10.1016/j.jval.2017.05.024

DO - 10.1016/j.jval.2017.05.024

M3 - Article

VL - 20

SP - 1411

EP - 1419

JO - Value in Health

JF - Value in Health

SN - 1098-3015

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ER -