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The thyroid cancer policy model: A mathematical simulation model of papillary thyroid carcinoma in The U.S. population
BACKGROUND: Thyroid cancer affects over ½ million people in the U.S. and the incidence of thyroid cancer has increased worldwide at a rate higher than any other cancer, while survival has remained largely unchanged. The aim of this research was to develop, calibrate and verify a mathematical disease...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5421766/ https://www.ncbi.nlm.nih.gov/pubmed/28481909 http://dx.doi.org/10.1371/journal.pone.0177068 |
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author | Lubitz, Carrie Ali, Ayman Zhan, Tiannan Heberle, Curtis White, Craig Ito, Yasuhiro Miyauchi, Akira Gazelle, G. Scott Kong, Chung Yin Hur, Chin |
author_facet | Lubitz, Carrie Ali, Ayman Zhan, Tiannan Heberle, Curtis White, Craig Ito, Yasuhiro Miyauchi, Akira Gazelle, G. Scott Kong, Chung Yin Hur, Chin |
author_sort | Lubitz, Carrie |
collection | PubMed |
description | BACKGROUND: Thyroid cancer affects over ½ million people in the U.S. and the incidence of thyroid cancer has increased worldwide at a rate higher than any other cancer, while survival has remained largely unchanged. The aim of this research was to develop, calibrate and verify a mathematical disease model to simulate the natural history of papillary thyroid cancer, which will serve as a platform to assess the effectiveness of clinical and cancer control interventions. METHODS: Herein, we modeled the natural pre-clinical course of both benign and malignant thyroid nodules with biologically relevant health states from normal to detected nodule. Using established calibration techniques, optimal parameter sets for tumor growth characteristics, development rate, and detection rate were used to fit Surveillance Epidemiology and End Results (SEER) incidence data and other calibration targets. RESULTS: Model outputs compared to calibration targets demonstrating sufficient calibration fit and model validation are presented including primary targets of SEER incidence data and size distribution at detection of malignancy. Additionally, we show the predicted underlying benign and malignant prevalence of nodules in the population, the probability of detection based on size of nodule, and estimates of growth over time in both benign and malignant nodules. CONCLUSIONS: This comprehensive model provides a dynamic platform employable for future comparative effectiveness research. Future model analyses will test and assess various clinical management strategies to improve patient outcomes related to thyroid cancer and optimize resource utilization for patients with thyroid nodules. |
format | Online Article Text |
id | pubmed-5421766 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-54217662017-05-14 The thyroid cancer policy model: A mathematical simulation model of papillary thyroid carcinoma in The U.S. population Lubitz, Carrie Ali, Ayman Zhan, Tiannan Heberle, Curtis White, Craig Ito, Yasuhiro Miyauchi, Akira Gazelle, G. Scott Kong, Chung Yin Hur, Chin PLoS One Research Article BACKGROUND: Thyroid cancer affects over ½ million people in the U.S. and the incidence of thyroid cancer has increased worldwide at a rate higher than any other cancer, while survival has remained largely unchanged. The aim of this research was to develop, calibrate and verify a mathematical disease model to simulate the natural history of papillary thyroid cancer, which will serve as a platform to assess the effectiveness of clinical and cancer control interventions. METHODS: Herein, we modeled the natural pre-clinical course of both benign and malignant thyroid nodules with biologically relevant health states from normal to detected nodule. Using established calibration techniques, optimal parameter sets for tumor growth characteristics, development rate, and detection rate were used to fit Surveillance Epidemiology and End Results (SEER) incidence data and other calibration targets. RESULTS: Model outputs compared to calibration targets demonstrating sufficient calibration fit and model validation are presented including primary targets of SEER incidence data and size distribution at detection of malignancy. Additionally, we show the predicted underlying benign and malignant prevalence of nodules in the population, the probability of detection based on size of nodule, and estimates of growth over time in both benign and malignant nodules. CONCLUSIONS: This comprehensive model provides a dynamic platform employable for future comparative effectiveness research. Future model analyses will test and assess various clinical management strategies to improve patient outcomes related to thyroid cancer and optimize resource utilization for patients with thyroid nodules. Public Library of Science 2017-05-08 /pmc/articles/PMC5421766/ /pubmed/28481909 http://dx.doi.org/10.1371/journal.pone.0177068 Text en © 2017 Lubitz et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Lubitz, Carrie Ali, Ayman Zhan, Tiannan Heberle, Curtis White, Craig Ito, Yasuhiro Miyauchi, Akira Gazelle, G. Scott Kong, Chung Yin Hur, Chin The thyroid cancer policy model: A mathematical simulation model of papillary thyroid carcinoma in The U.S. population |
title | The thyroid cancer policy model: A mathematical simulation model of papillary thyroid carcinoma in The U.S. population |
title_full | The thyroid cancer policy model: A mathematical simulation model of papillary thyroid carcinoma in The U.S. population |
title_fullStr | The thyroid cancer policy model: A mathematical simulation model of papillary thyroid carcinoma in The U.S. population |
title_full_unstemmed | The thyroid cancer policy model: A mathematical simulation model of papillary thyroid carcinoma in The U.S. population |
title_short | The thyroid cancer policy model: A mathematical simulation model of papillary thyroid carcinoma in The U.S. population |
title_sort | thyroid cancer policy model: a mathematical simulation model of papillary thyroid carcinoma in the u.s. population |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5421766/ https://www.ncbi.nlm.nih.gov/pubmed/28481909 http://dx.doi.org/10.1371/journal.pone.0177068 |
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