A patient-specific treatment model for Graves’ hyperthyroidism

Abstract

BackgroundGraves’ is disease an autoimmune disorder of the thyroid gland causedby circulating anti-thyroid receptor antibodies (TRAb) in the serum. TRAb mimics the action of thyroid stimulating hormone (TSH) and stimulates the thyroid hormone receptor (TSHR), which results in hyperthyroidism (overactive thyroid gland) and goiter. Methimazole (MMI) is used for hyperthyroidism treatment for patients with Graves’ disease.MethodsWe have developed a model using a system of ordinary differential equations for hyperthyroidism treatment with MMI. The model has four state variables, namely concentration of MMI (in mg/L), concentration of free thyroxine - FT4 (in pg/mL), and concentration of TRAb (in U/mL) and the functional size of the thyroid gland (in mL) with thirteen parameters. With a treatment parameter, we simulate the time-course of patients’ progression from hyperthyroidism to euthyroidism (normal condition). We validated the model predictions with data from four patients.ResultsWhen there is no MMI treatment, there is a unique asymptotically stable hyperthyroid state. After the initiation of MMI treatment, the hyperthyroid state moves towards subclinical hyperthyroidism and then euthyroidism.ConclusionWe can use the model to describe or test and predict patient treatment schedules. More specifically, we can fit the model to individual patients’ data including loading and maintenance doses and describe the mechanism, hyperthyroidism→euthyroidism. The model can be used to predict when to discontinue the treatment based on FT4 levels within the physiological range, which in turn help maintain the remittance of euthyroidism and avoid relapses of hyperthyroidism. Basically, the model can guide with decision-making on oral intake of MMI based on FT4 levels.Electronic supplementary materialThe online version of this article (doi:10.1186/s12976-017-0073-6) contains supplementary material, which is available to authorized users.

Assessment of a Takagi–Sugeno-Kang fuzzy model assembly for examination of polyphasic loglinear allometry

“…Likewise, detected break point in Zostera marina could be interpreted as a threshold beyond which plant assigns to leaves a relatively greater amount of tissue to resist damage and separation from shoots induced by drag forces. This implies different scaling parameters among small and large leaves (Echavarría-Heras et al, 2019a;Echavarría-Heras et al, 2018b;Echavarria-Heras et al, 2019b). Similarly, a detected break point in Metrosideros polymorpha may suggest different allometric scaling depending on tree size.…”

“…Allometric examination here mainly relied on a primary data set exhibiting curvature in geometrical space. This composes 10,412 measurements of Zostera marina (Eelgrass) leaf biomasses y and corresponding leaf areas x as reported in Echavarría-Heras et al (2019a) and Echavarría-Heras et al (2018b). For comparison, we also considered data reported in Mascaro et al (2011) comprising 30 Biomass-Diameter at Breast Height measurements on Metrosideros polymorpha.…”

A Mathematical Model of Thyroid Disease Response to Radiotherapy

“…That study did not consider the evolution of Tg or TgAb. Pandiyan et al [25] presented a mathematical model of response to methimazole therapy for Graves' disease, which includes many of the compartments discussed above, and models the evolution of TSH, T4 and T3 hormones, as well as other antibodies relevant for Graves' hyperthyroidism, but not Tg nor TgAb. Other mathematical models of Graves' disease relapse after antithyroid drugs [26] or RAI [27] have been also presented.…”

Disease Emergence in Multi-Patch Stochastic Epidemic Models with Demographic and Seasonal Variability

“… 2014 ; Jin and Lin 2018 ; McLennan-Smith and Mercer 2014 ; Mitchell and Kribs 2017 ; Posny and Wang 2014 ; Schwartz and Smith 1983 ; Suparit et al. 2018 ; Vaidya and Wahl 2015 ; Wang et al. 2012 ; Wang and Zhao 2017a , b ; Zhang and Zhao 2007 ; Wolf et al.…”