ArticlePloS one2017
The thyroid cancer policy model: A mathematical simulation model of papillary thyroid carcinoma in The U.S. population.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 8 citations in OpenAlex.
- A Scoping Review on Calibration Methods for Cancer Simulation Models.Medical decision making : an international journal of the Society for Medical Decision Making · 2025Article
- Making Choices: A Multi-institutional, Longitudinal Cohort Study Assessing Changes in Treatment Outcome Valuation for Low-risk Thyroid Cancer.Annals of surgery · 2025Article
- Modeling Thyroid Cancer Epidemiology in the United States Using Papillary Thyroid Carcinoma Microsimulation Model.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2024Article
- Article
- Mathematical models applied to thyroid cancer.Biophysical reviews · 2019Review
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundThyroid 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.
methodsHerein, 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.
resultsModel 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.
conclusionsThis 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.