• Nonlinear correlation of thyrotropin levels with peripheral levothyroxine levels. [ Time Frame: Data of individual patients are obtained one work day after consultation (to allow for laboratory investigations). Model comparison will take place immediately after the inclusion of the 100th patient. ] [ Designated as safety issue: No ]

  Nonlinear modeling of the pituitary response with different models (logarithmic, polynomial, non-competitive divisive inhibition). Selection of one out of different possible mathematical models that suffices an optimal combination of

  • best nonlinear fit (minimal p-value),
  • minimal entropy (as expressed by minimal values for Akaike information criterion, Bayesian information criterion and Hannan-Quinn information criterion) and
  • best compatibility with biochemical mechanisms.
  
  

• Parameters of feedback inhibition. [ Time Frame: Data of individual patients are obtained one work day after consultation (to allow for laboratory investigations). Parameter estimation will take place immediately after the inclusion of the 100th patient. ] [ Designated as safety issue: No ]
  Extraction of structural parameters out of the model that has been selected (see primary outcome measure)
  
  

Control of thyroid hormone homeostasis is essential for function and development of the organism and hence for individual health. It is therefore not surprising that the thyroid's function is controlled by a complex, multi-loop feedback control system.

Today, the central component of the thyrotropic feedback control system is still poorly understood on a physiological level. Therefore, in mathematical models different functional relations describing the feedback-inhibition of thyrotropin incretion by thyroid hormones have been suggested [Danziger and Elmergreen 1956, Roston 1959, Norwich and Reiter 1965, DiStefano and Stear 1968, DiStefano 1969, Saratchandran et al. 1973, Li et al. 1995, Dietrich et al. 2004, Degon et al. 2008, Jonklaas and Soldin 2008, Hörmann et al. 2010]. Most of these models fail in delivering biochemical explanations for the functional interrelations they postulate.

Nevertheless, some clinical applications of these models have been developed, although their diagnostical potential is usually rather limited [Yagi et al. 1997, Pohlenz et al. 1999, Jostel et al. 2009].

Assuming that the pituitary's response to peripheral thyroid hormones is determined by active transmembrane thyroxine transport mechanisms [Dietrich et al. 2008], intracellular deiodination of thyroxine (T4), binding of resulting triiodothyronine (T3) to iodothyronine receptors and, finally, their inhibiting effect on mRNA expression, translation and release of TRH, a novel, physiologically motivated model has been developed that is based on compartment-analytical approaches, Michaelis-Menten kinetics and non competitive divisive inhibition [Dietrich et al 2004]. However, this model has not been sufficiently evaluated in a clinical context.

It is the aim of the NOMOTHETICOS study to deliver new systems-level insights into the pituitary's thyrotropic function. This unicentric cross-sectional study compares different models of feedback-inhibition by means of modern statistical methods like nonlinear regression and Akaike information criterion. Structural parameters are obtained in vivo from open-loop analysis in patients with disconnected feedback in equilibrium.

These parameters can serve as theoretical basis for possible future trials developing advanced diagnostical evaluation methods of thyrotropic pituitary function.