We have a new paper out as below, discussing the relationships between TSH, FT4 and FT3 and the need to use all parameters in determining best treatment for those of thyroid hormone supplementation. It is available freely to download if required. We're trying to get a modelling programme that would automatically home in on the best "set point" for a patient based on at the moment FT4 and TSH values. FT3 is being included by a future refinement. This would allow a sound assessment of the treatment needed to achieve the best outcome.
Advances in applied homeostatic modelling of the relationship between thyrotropin and free thyroxine
doi.org/10.1371/journal.pon...
Rudolf Hoermann, John Edward Maurice Midgley, Rolf Larisch, Johannes Wolfgang Christian Dietrich
Abstract
Introduction
The relationship between pituitary TSH and thyroid hormones is central to our understand- ing of thyroid physiology and thyroid function testing. Here, we generated distribution patterns by using validated tools of thyroid modelling.
Methods
We simulated patterns of individual set points under various conditions, based on a homeostatic model of thyroid feedback control. These were compared with observed data points derived from clinical trials.
Results
A random mix of individual set points was reconstructed by simulative modelling with defined structural parameters. The pattern displayed by the cluster of hypothetical points resembled that observed in a natural control group. Moderate variation of the TSH-FT4 gradient over the functional range introduced further flexibility, implementing a scenario of adaptive set points. Such a scenario may be a realistic possibility for instance in treatment where relationships and equilibria between thyroid parameters are altered by various influences such as LT4 dose and conversion efficiency.
Conclusions
We validated a physiologically based homeostatic model that permits simulative reconstruction of individual set points. This produced a pattern resembling the observed data under various conditions. Applied modelling, although still experimental at this stage, shows a potential to aid our physiological understanding of the interplay between TSH decision making.