Skip to main content

Advertisement

SpringerLink
Log in

Relapse prediction in Graves´ disease: Towards mathematical modeling of clinical, immune and genetic markers

  • Published:
Reviews in Endocrine and Metabolic Disorders Aims and scope Submit manuscript

Abstract

Problem: Graves’ disease (GD) is an important and prevalent thyroid autoimmune disorder. Standard therapy for GD consists of antithyroid drugs (ATD) with treatment periods of around 12 months but relapse is frequent. Since predictors for relapse are difficult to identify the individual decision making for optimal treatment is often arbitrary. Methods: After reviewing the literature on this topic we summarize important factors involved in GD and with respect to their potential for relapse prediction from markers before and after treatment. This information was used to design a mathematical model integrating thyroid hormone parameters, thyroid size, antibody titers and a complex algorithm encompassing genetic predisposition, environmental exposures and current immune activity in order to arrive at a prognostic index for relapse risk after treatment. Conclusion: In the search for a tool to analyze and predict relapse in GD mathematical modeling is a promising approach. In analogy to mathematical modeling approaches in other diseases such as viral infections, we developed a differential equation model on the basis of published clinical trials in patients with GD. Although our model needs further evaluation to be applicable in a clinical context, it provides a perspective for an important contribution to a final statistical prediction model.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Notes

  1. „Empirical models are based on direct observation, measurement and extensive data records. Mechanistic models are based on an understanding of the behavior of a system’s components. For example, you can observe the change of the tides over many years, and construct an empirical model that allows you to predict when tides will occur, with no understanding of how the earth, moon and sun interact. You can also create a mathematical, mechanistic model that uses the laws of physics to predict tides.” [78]

References

  1. Brent GA. Clinical practice. Graves’ disease. N Engl J Med. 2008;358:2594–605.

    Article  CAS  PubMed  Google Scholar 

  2. Badenhoop K, Donner H, Braun J, Siegmund T, Rau H, Usadel KH. Genetic markers in diagnosis and prediction of relapse in Graves’ disease. Exp Clin Endocrinol Diabetes. 1996;104(Suppl):98–100.

    Article  PubMed  Google Scholar 

  3. Gillard P, Huurman V, Van der Auwera B, Decallonne B, Poppe K, Roep BO, et al. Graves hyperthyroidism after stopping immunosuppressive therapy in type 1 diabetic islet cell recipients with pretransplant TPO autoantibodies. Diabetes Care. 2009;32:1817–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Bartalena L, Burch HB, Burman KD, Kahaly GJ. A 2013 European survey of clinical practice patterns in the management of Graves’ disease. Clin Endocrinol. 2014. doi:10.1111/cen.12688.

    Google Scholar 

  5. Cooper DS. Antithyroid drugs. N Engl J Med. 2005;352:905–17.

    Article  CAS  PubMed  Google Scholar 

  6. Vitti P, Rago T, Chiovato L, Pallini S, Santini F, Fiore E, et al. Clinical features of patients with Graves’ disease undergoing remission after antithyroid drug treatment. Thyroid. 1997;7:369–75.

    Article  CAS  PubMed  Google Scholar 

  7. Ueda M, Inaba M, Kumeda Y, Nagasaki T, Hiura Y, Tahara H, et al. The significance of thyroid blood flow at the inferior thyroid artery as a predictor for early Graves’ disease relapse. Clin Endocrinol. 2005;63:657–62.

    Article  Google Scholar 

  8. Weetman AP. Graves’ disease. N Engl J Med. 2000;343:1236–48.

    Article  CAS  PubMed  Google Scholar 

  9. Brix TH, Kyvik KO, Christensen K, Hegedus L. Evidence for a major role of heredity in Graves’ disease: a population-based study of two Danish twin cohorts. J Clin Endocrinol Metab. 2001;86:930–4.

    CAS  PubMed  Google Scholar 

  10. Ringold D. A, Nicoloff JT, Kesler M, Davis H, Hamilton a, Mack T: further evidence for a strong genetic influence on the development of autoimmune thyroid disease: the California twin study. Thyroid. 2002;12:647–53.

    Article  PubMed  Google Scholar 

  11. Lee HJ, Li CW, Hammerstad SS, Stefan M, Tomer Y. Immunogenetics of autoimmune thyroid diseases: a comprehensive review. J Autoimmun. 2015;64:82–90.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Boelaert K, Newby PR, Simmonds MJ, Holder RL, Carr-Smith JD, Heward JM, et al. Prevalence and relative risk of other autoimmune diseases in subjects with autoimmune thyroid disease. Am J Med. 2010;123:183.e1–9.

    Article  Google Scholar 

  13. Orgiazzi J, Madec A-M. Reduction of the risk of relapse after withdrawal of medical therapy for Graves’ disease. Thyroid. 2002;12:849–53.

    Article  CAS  PubMed  Google Scholar 

  14. Tagami T, Hagiwara H, Kimura T, Usui T, Shimatsu A, Naruse M. The incidence of gestational hyperthyroidism and postpartum thyroiditis in treated patients with Graves’ disease. Thyroid. 2007;17:767–72.

    Article  CAS  PubMed  Google Scholar 

  15. Jubault V, Penfornis A, Schillo F, Hoen B, Izembart M, Timsit J, et al. Sequential occurrence of thyroid autoantibodies and Graves’ disease after immune restoration in severely immunocompromised human immnunodeficiency virus-1-infected patients. J Clin Endocrinol Metab. 2000;85:4254–7.

    CAS  PubMed  Google Scholar 

  16. Bagnasco M, Bossert I, Pesce G. Stress and autoimmune thyroid diseases. Neuroimmunomodulation. 2006;13:309–17.

    Article  CAS  PubMed  Google Scholar 

  17. Wang J, Lv S, Chen G, Gao C, He J, Zhong H, et al. Meta-analysis of the association between vitamin D and autoimmune thyroid disease. Nutrients. 2015;7:2485–98.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Kurylowicz A, Ramos-Lopez E, Bednarczuk T, Badenhoop K. Vitamin D-binding protein (DBP) gene polymorphism is associated with Graves’ disease and the vitamin D status in a polish population study. Exp Clin Endocrinol Diabetes. 2006;114:329–35.

    Article  CAS  PubMed  Google Scholar 

  19. Corapcioglu D, Tonyukuk V, Kiyan M, Yilmaz AE, Emral R, Kamel N, et al. Relationship between thyroid autoimmunity and Yersinia enterocolitica antibodies. Thyroid. 2002;12:613–7.

    Article  PubMed  Google Scholar 

  20. Bassi V, Marino G, Iengo A, Fattoruso O, Santinelli C. Autoimmune thyroid diseases and helicobacter pylori: the correlation is present only in Graves’s disease. World J Gastroenterol. 2012;18:1093–7.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Antonelli A, Ferri C, Fallahi P, Ferrari SM, Ghinoi A, Rotondi M, et al. Thyroid disorders in chronic hepatitis C virus infection. Thyroid. 2006;16:563–72.

    Article  PubMed  Google Scholar 

  22. Weetman AP, McGregor AM. Autoimmune thyroid disease: further developments in our understanding. Endocr Rev. 1994;15:788–830.

    CAS  PubMed  Google Scholar 

  23. Aleksić A, Aleksić Z, Stojanović M. TSH receptor antibodies for confirming the diagnosis and prediction of remission duration, in newly diagnosed Graves’ disease patients. Hell J Nucl Med. 2009;12:146–50.

    PubMed  Google Scholar 

  24. Antonelli A, Ferrari SM, Corrado A, Di Domenicantonio A, Fallahi P. Autoimmune thyroid disorders. Autoimmun Rev. 2015;14:174–80.

    Article  CAS  PubMed  Google Scholar 

  25. Yu H, Farahani P. Thyroid stimulating hormone suppression post-therapy in patients with Graves’ disease: a systematic review of pathophysiology and clinical data. Clin Invest Med. 2015;38:E31–44.

    Article  CAS  PubMed  Google Scholar 

  26. Neumann S, Place RF, Krieger CC, Gershengorn MC. Future prospects for the treatment of Graves’ hyperthyroidism and eye disease. Horm Metab Res. 2015;47:789–96.

    Article  CAS  PubMed  Google Scholar 

  27. Marinò M, Latrofa F, Menconi F, Chiovato L, Vitti P. An update on the medical treatment of Graves’ hyperthyroidism. J Endocrinol Investig. 2014;37:1041–8.

    Article  Google Scholar 

  28. Wilson R, McKillop JH, Pearson C. Burnett a K, Thomson J a: differential immunosuppressive action of carbimazole and propylthiouracil. Clin Exp Immunol. 1988;73:312–5.

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Volpé R. The immunomodulatory effects of anti-thyroid drugs are mediated via actions on thyroid cells, affecting thyrocyte-immunocyte signalling: a review. Curr Pharm Des. 2001;7:451–60.

    Article  PubMed  Google Scholar 

  30. Gubbels Bupp MR. Sex, the aging immune system, and chronic disease. Cell Immunol. 2015;294:102–10.

    Article  CAS  PubMed  Google Scholar 

  31. Sopori M. 21 review: effects of cigarette smoke on the immune system. Nat Rev Immunol. 2002;2:372–7.

    Article  CAS  PubMed  Google Scholar 

  32. Vestergaard P. Smoking and thyroid disorders--a meta-analysis. Eur J Endocrinol. 2002;146:153–61.

    Article  CAS  PubMed  Google Scholar 

  33. Mohlin E, Filipsson Nyström H, Eliasson M. Long-term prognosis after medical treatment of Graves’ disease in a northern Swedish population 2000-2010. Eur J Endocrinol. 2014;170:419–27.

    Article  CAS  PubMed  Google Scholar 

  34. Kamath C, Adlan MA, Premawardhana LD. The role of thyrotrophin receptor antibody assays in Graves’ disease. J Thyroid Res. 2012;2012:525936.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Parkes GC, Whelan K, Lindsay JO. Smoking in inflammatory bowel disease: Impact on disease course and insights into the aetiology of its effect. J Crohn’s Colitis. 2014;8:717–25.

    Article  Google Scholar 

  36. Guerra LN, Ríos De Molina MDC, Miler EA, Moiguer S, Karner M, Burdman JA. Antioxidants and methimazole in the treatment of Graves’ disease: effect on urinary malondialdehyde levels. Clin Chim Acta. 2005;352:115–20.

    Article  CAS  PubMed  Google Scholar 

  37. Drutel A, Archambeaud F, Caron P. Selenium and the thyroid gland: more good news for clinicians. Clin Endocrinol. 2013;78:155–64.

    Article  CAS  Google Scholar 

  38. Laurberg P, Jørgensen T, Perrild H, Ovesen L, Knudsen N, Pedersen IB, et al. The Danish investigation on iodine intake and thyroid disease, DanThyr: status and perspectives. Eur J Endocrinol. 2006;155:219–28.

    Article  CAS  PubMed  Google Scholar 

  39. Vos XG, Endert E, Zwinderman K, Tijssen JGP, Wiersinga WM. Predicting the risk of recurrence before the start of antithyroid drug therapy in patients with Graves’ hyperthyroidism. J Clin Endocrinol Metab. 2016;10:1–10.

    Google Scholar 

  40. Dauksiene D, Dauksa A, Mickuviene N. Independent pretreatment predictors of Graves’ disease outcome. Med. 2013;49:427–34.

    Google Scholar 

  41. Törring O, Tallstedt L, Wallin G, Lundell G, Ljunggren JG, Taube A, et al. Graves’ hyperthyroidism: treatment with antithyroid drugs, surgery, or radioiodine--a prospective, randomized study. Thyroid study group. J Clin Endocrinol Metab. 1996;81:2986–93.

    PubMed  Google Scholar 

  42. Wang P-W, Chen I-Y, Juo S-HH, Hsi E, Liu R-T, Hsieh C-J. Genotype and phenotype predictors of relapse of Graves’ disease after antithyroid drug withdrawal. Eur Thyroid J. 2013;1:251–8.

    PubMed  Google Scholar 

  43. Eckstein AK, Lax H, Lösch C, Glowacka D, Plicht M, Mann K, et al. Patients with severe Graves’ ophthalmopathy have a higher risk of relapsing hyperthyroidism and are unlikely to remain in remission. Clin Endocrinol. 2007;67:607–12.

    Google Scholar 

  44. Schleusener H, Schwander J, Fischer C, Holle R, Holl G, Badenhoop K, et al. Prospective multicentre study on the prediction of relapse after antithyroid drug treatment in patients with Graves’ disease. Acta Endocrinol. 1989;120:689–701.

    CAS  PubMed  Google Scholar 

  45. Michelangeli V, Poon C, Taft J, Newnham H, Topliss D, Colman P. The prognostic value of thyrotropin receptor antibody measurement in the early stages of treatment of Graves’ disease with antithyroid drugs. Thyroid. 1998;8:119–24.

    Article  CAS  PubMed  Google Scholar 

  46. Hoermann R, Quadbeck B, Roggenbuck U, Szabolcs I, Pfeilschifter J, Meng W, et al. Relapse of Graves’ disease after successful outcome of antithyroid drug therapy: results of a prospective randomized study on the use of levothyroxine. Thyroid. 2002;12:1119–28.

    Article  CAS  PubMed  Google Scholar 

  47. Morshed SA, Davies TF. Graves’ disease mechanisms: the role of stimulating, blocking, and cleavage region TSH receptor antibodies. Horm Metab Res. 2015;47:727–34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Barbesino G, Tomer Y. Clinical review: clinical utility of TSH receptor antibodies. J Clin Endocrinol Metab. 2013;98:2247–55.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Davies TF, Ando T, Lin R-Y, Tomer Y, Latif R. Thyrotropin receptor-associated diseases: from adenomata to Graves disease. J Clin Invest. 2005;115:1972–83.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Liu X, Qiang W, Liu X, Liu L, Liu S, Gao A, et al.: A 6-year follow-up of a randomized prospective trial comparing methimazole treatment with or without exogenous L-thyroxine in Chinese patients with Graves ’ Disease 2014;564–567.

  51. Anagnostis P, Adamidou F, Polyzos SA, Katergari S, Karathanasi E, Zouli C, et al. Predictors of long-term remission in patients with Graves’ disease: a single center experience. Endocrine. 2013;44:448–53.

    Article  CAS  PubMed  Google Scholar 

  52. Abraham P, Avenell A, McGeoch SC, Clark LF, Bevan JS. Antithyroid drug regimen for treating Graves’ hyperthyroidism. Cochrane Database Syst Rev. 2010;1:1.

    Google Scholar 

  53. Maugendre D, Gatel A, Campion L, Massart C, Guilhem I, Lorcy Y, et al. Antithyroid drugs and Graves’ disease--prospective randomized assessment of long-term treatment. Clin Endocrinol. 1999;50:127–32.

    Article  CAS  Google Scholar 

  54. Benker G, Reinwein D, Kahaly G, Tegler L, Alexander WD, Fassbinder J, et al. Is there a methimazole dose effect on remission rate in Graves’ disease? Results from a long-term prospective study. The European multicentre trial Group of the Treatment of hyperthyroidism with antithyroid drugs. Clin Endocrinol. 1998;49:451–7.

    Article  CAS  Google Scholar 

  55. Reinwein D, Benker G, Lazarus JH, Alexander WD. A prospective randomized trial of antithyroid drug dose in Graves’ disease therapy. European multicenter study group on antithyroid drug treatment. J Clin Endocrinol Metab. 1993;76:1516–21.

    CAS  PubMed  Google Scholar 

  56. Vang T, Miletic AV, Bottini N, Mustelin T. Protein tyrosine phosphatase PTPN22 in human autoimmunity. Autoimmunity. 2007;40:453–61.

    Article  CAS  PubMed  Google Scholar 

  57. Vita R, Lapa D, Trimarchi F, Benvenga S. Stress triggers the onset and the recurrences of hyperthyroidism in patients with Graves’ disease. Endocrine. 2015;48:254–63.

    Article  CAS  PubMed  Google Scholar 

  58. Mizokami T, Wu Li A, El-Kaissi S, Wall JR. Stress and thyroid autoimmunity. Thyroid. 2004;14:1047–55.

    Article  CAS  PubMed  Google Scholar 

  59. Benvenga S. Benzodiazepine and remission of Graves’ disease. Thyroid. 1996;6:659–60.

    Article  CAS  PubMed  Google Scholar 

  60. Vita R, Lapa D, Vita G, Trimarchi F, Benvenga S. A patient with stress-related onset and exacerbations of Graves disease. Nat Clin Pract Endocrinol Metab. 2009;5:55–61.

    Article  CAS  PubMed  Google Scholar 

  61. Rotondi M, Cappelli C, Pirali B, Pirola I, Magri F, Fonte R, et al. The effect of pregnancy on subsequent relapse from Graves’ disease after a successful course of antithyroid drug therapy. J Clin Endocrinol Metab. 2008;93:3985–8.

    Article  CAS  PubMed  Google Scholar 

  62. Smye SW, Clayton RH. Mathematical modelling for the new millenium: medicine by numbers. Med Eng Phys. 2002;24:565–74.

    Article  PubMed  Google Scholar 

  63. Canini L, Perelson AS. Viral kinetic modeling: state of the art. J Pharmacokinet Pharmacodyn. 2014;41:431–43.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Danziger, Elmergreen. Mathematical Theory of Periodic Relapsing Catatonia. Bull Math Biophys. 1954;16:15–21.

    Article  Google Scholar 

  65. Danziger, Elmergreen. The thyroid-pituitary homeostatic mechanism. Bull Math Biophys. 1956;18:1–13.

    Article  Google Scholar 

  66. Rashevsky N. Mathematical theory of biological periodicities: formulation of the n-body case. Bull Math Biophys. 1968;30:735–49.

    Article  CAS  PubMed  Google Scholar 

  67. Norwich K, Raymond R. Homeostatic control of the thyroxin concentration expressed by a set of linear differential equations. Bull Math Biophys. 1965;27:133–44.

    Article  CAS  PubMed  Google Scholar 

  68. DiStefano J, Stear E. Neuroendocrine control of thyroid secretion in living systems: a feedback control system model. Bull Math Biophys. 1968;30:8–26.

    Google Scholar 

  69. Hatakeyama T, Yagi H. Computer simulation for hormones related to primary Thyropathy. Biol Cybern. 1985;52:259–66.

    Article  CAS  PubMed  Google Scholar 

  70. Liu Y, Liu B, Xie J, Liu YX. A new mathematical model of hypothalamo-pituitary-thyroid axis. Math Comput Model. 1994;19:81–90.

    Article  Google Scholar 

  71. Degon M, Chipkin SR, Hollot CV, Zoeller RT, Chait Y. A computational model of the human thyroid. Math Biosci. 2008;212:22–53.

    Article  CAS  PubMed  Google Scholar 

  72. Hoermann R, Eckl W, Hoermann C, Larisch R. Complex relationship between free thyroxine and TSH in the regulation of thyroid function. Eur J Endocrinol. 2010;162:1123–9.

    Article  CAS  PubMed  Google Scholar 

  73. Pandiyan B, Merrill SJ, Benvenga S. A patient-specific model of the negative-feedback control of the hypothalamus-pituitary-thyroid (HPT) axis in autoimmune (Hashimoto’s) thyroiditis. Math Med Biol. 2014;31:226–58.

    Article  PubMed  Google Scholar 

  74. Silver N, Good CD, Barker GJ, MacManus DG, Thompson AJ, Moseley IF, et al. Sensitivity of contrast enhanced MRI in multiple sclerosis. Brain. 1997;120:1149–61.

    Article  PubMed  Google Scholar 

  75. Velez de Mendizabal N, Hutmacher MM, Troconiz IF, Goni J, Villoslada P, Bagnato F, et al. Predicting relapsing-remitting dynamics in multiple sclerosis using discrete distribution models: a population approach. PLoS One. 2013;8. doi:10.1371/journal.pone.0073361.

  76. Goede SL. Leow MK-SS, Smit JWA, Klein HH, Dietrich JW: hypothalamus-pituitary-thyroid feedback control: implications of mathematical modeling and consequences for thyrotropin (TSH) and free thyroxine (FT4) reference ranges. Bull Math Biol. 2014;76:1270–87.

    Article  CAS  PubMed  Google Scholar 

  77. Nyström HF, Jansson S, Berg G. Incidence rate and clinical features of hyperthyroidism in a long-term iodine sufficient area of Sweden (Gothenburg) 2003-2005. Clin Endocrinol. 2013;78:768–76.

    Article  Google Scholar 

  78. Sarokin D: What is a mechanistic Model? [Internet] [cited 2016 Aug 9];Available from: http://smallbusiness.chron.com/mechanistic-model-12706.html.

Download references

Author information

Authors and Affiliations

  1. Institute of Biostatistics and Mathematical Modeling – Department of Medicine, Goethe University Frankfurt, Theodor-Stern-Kai 7, Frankfurt am Main, 60590, Germany

    Christoph Langenstein & Eva Herrmann

  2. Department of Medicine 1 – Division of Endocrinology & Diabetes, Goethe University Hospital Frankfurt, Frankfurt am Main, Germany

    Diana Schork & Klaus Badenhoop

Authors
  1. Christoph Langenstein
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Diana Schork
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Klaus Badenhoop
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Eva Herrmann
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Christoph Langenstein.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Langenstein, C., Schork, D., Badenhoop, K. et al. Relapse prediction in Graves´ disease: Towards mathematical modeling of clinical, immune and genetic markers. Rev Endocr Metab Disord 17, 571–581 (2016). https://doi.org/10.1007/s11154-016-9386-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11154-016-9386-8

Keywords

Search

Navigation