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Introduction: The relationship between pituitary TSH and thyroid hormones is central to our understanding 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 and thyroid hormones. It should eventually benefit personalised clinical decision making.

Objective: In recognition of its primary role in pituitary-thyroid feedback, TSH determination has become a key parameter for clinical decision-making. This study examines the value of TSH as a measure of thyroid hormone homoeostasis under thyroxine (T(4)) therapy., Design and Methods: We have examined the interrelationships between free triiodothyronine (FT(3)), free T(4) (FT(4)) and pituitary TSH by means of i) a retrospective analysis of a large clinical sample comprising 1994 patients either untreated or on varying doses of l-T(4) and ii) independent mathematical simulation applying a model of thyroid homoeostasis, together with a sensitivity analysis., Results: Over a euthyroid to mildly hyperthyroid functional range, we found markedly different correlation slopes of log TSH vs FT(3) and FT(4) between untreated patients and l-T(4) groups. Total deiodinase activity (G(D)) was positively correlated with TSH in untreated subjects. However, G(D) was significantly altered and the correlation was lost under increasing l-T(4) doses. Ninety-five per cent confidence intervals for FT(3) and FT(4), when assessed in defined TSH concentration bands, differed significantly for l-T(4)-treated compared with untreated patients. Higher doses were often needed to restore FT(3) levels within its reference range. Sensitivity analysis revealed the influence of various structural parameters on pituitary TSH secretion including an important role of pituitary deiodinase type 2., Conclusion: The data reveal disjoints between FT(4)-TSH feedback and T(3) production that persist even when sufficient T(4) apparently restores euthyroidism. T(4) treatment displays a compensatory adaptation but does not completely re-enact normal euthyroid physiology. This invites a study of the clinical consequences of this disparity.

The fundamental models underlying hormonal physiological regulation and homeostasis remain poorly understood. We aimed to derive quantitative evidence regarding these models from the study of population data of balance points of different parameters and their respective controlling hormones. We studied the slopes of correlations between concentrations of circulating free thyroxine and thyrotropin, calcium and parathyroid hormone, hemoglobin and erythropoietin, and glucose and insulin in such population data, as well as the slopes of the limbs of various feedback loops estimated empirically and by reverse engineering of the population data. We used computer simulations to model the factors that influence the slopes derived from the population data, and then matched these simulations with the empirically derived slopes. Our simulations showed that changes to the population distribution of feedback loop limbs may alter the slopes of correlations within population data in specific ways. Non-random (interdependent) associations of the limbs of feedback loops may also have this effect, as well as producing discrepancies between the slopes of feedback limb loops determined experimentally and the same slopes determined by derivation from population data. Our corresponding empirical findings were consistent with the presence of such interdependence in the free thyroxine/thyrotropin, hemoglobin/erythropoietin, and glucose/insulin systems. The glucose/insulin data provided evidence consistent with increasing interdependence with age in childhood. Our findings therefore provide strong evidence that the interdependence of the limbs of feedback loops is a general feature of endocrine homeostatic regulation. This interdependence potentially bestows evolutionary homeostatic and regulatory advantages. [ABSTRACT FROM AUTHOR]

Endocrine regulation in the hypothalamic-pituitary-thyroid (HPT) axis is orchestrated by physiological circuits which integrate multiple internal and external influences. Essentially, it provides either of the two responses to overt biological challenges: to defend the homeostatic range of a target hormone or adapt it to changing environmental conditions. Under certain conditions, such flexibility may exceed the capability of a simple feedback control loop, rather requiring more intricate networks of communication between the system's components. A new minimal mathematical model, in the form of a parametrized nonlinear dynamical system, is here formulated as a proof-of-concept to elucidate the principles of the HPT axis regulation. In particular, it allows uncovering mechanisms for the homeostasis of the key biologically active hormone free triiodothyronine (FT3). One mechanism supports the preservation of FT3 homeostasis, whilst the other is responsible for the adaptation of the homeostatic state to a new level. Together these allow optimum resilience in stressful situations. Preservation of FT3 homeostasis, despite changes in FT4 and TSH levels, is found to be an achievable system goal by joining elements of top-down and bottom-up regulation in a cascade of targeted feedforward and feedback loops. Simultaneously, the model accounts for the combination of properties regarded as essential to endocrine regulation, namely sensitivity, the anticipation of an adverse event, robustness, and adaptation. The model therefore offers fundamental theoretical insights into the effective system control of the HPT axis. [ABSTRACT FROM AUTHOR]

Abstract: Background: Thyroid feedback regulation and equilibria between thyroid hormones differ in the presence or absence of a functioning thyroid remnant. Materials and Methods: This study examines the relationship between the sensitivity of TSH feedback and thyroid capacity in untreated patients with thyroid autoimmune disease (n = 86) and healthy controls (n = 271). Functional capacity was estimated at maximum TSH stimulation, and pituitary TSH response was FT4‐standardised with two established indices, the TSH index and the thyrotroph thyroid hormone resistance index. Results: The two indices correlated inversely with thyroid volume and functional thyroid capacity. Relationships were shifted upwards in patients with thyroid autoimmune disease. This positioned patients with thyroid autoimmune disease predominantly at the lower capacity range and upper part of TSH index. The relationship was modulated by serum FT3 concentrations, shifting 0.19 [95%CI: 0.12, 0.26] mIU/L per pmol FT3 increase. FT3 correlated with TSH index in total group ( τ = 0.09, P = 0.009) and both subgroups. FT3 levels were maintained despite a substantial capacity loss by progressively increasing conversion rates of T3 from T4, only collapsing at capacities below <1.5 pmol/s. Conclusion: Functional thyroid capacity and preferential T3 generation are essential elements in adjusting the sensitivity of hypothalamic‐pituitary‐thyroid feedback control and balancing system equilibria. This suggests that the indirect regulatory role of glandular T3 co‐secretion exceeds its quantitative contribution to the thyroid hormone pool. Implications for clinical practice extend to the diagnostic use of TSH in patients with impaired thyroid reserve. [ABSTRACT FROM AUTHOR]

Randomised controlled trials are deemed to be the strongest class of evidence in evidence-based medicine. Failure of trials to prove superiority of T3/T4 combination therapy over standard LT4 monotherapy has greatly influenced guidelines, while not resolving the ongoing debate. Novel studies have recently produced more evidence from the examination of homeostatic equilibria in humans and experimental treatment protocols in animals. This has exacerbated a serious disagreement with evidence from the clinical trials. We contrasted the weight of statistical evidence against strong physiological counterarguments. Revisiting this controversy, we identify areas of improvement for trial design related to validation and sensitivity of QoL instruments, patient selection, statistical power, collider stratification bias, and response heterogeneity to treatment. Given the high individuality expressed by thyroid hormones, their interrelationships, and shifted comfort zones, the response to LT4 treatment produces a statistical amalgamation bias (Simpson’s paradox), which has a key influence on interpretation. In addition to drug efficacy, as tested by RCTs, efficiency in clinical practice and safety profiles requires reevaluation. Accordingly, results from RCTs remain ambiguous and should therefore not prevail over physiologically based counterarguments. In giving more weight to other forms of valid evidence which contradict key assumptions of historic trials, current treatment options should remain open and rely on personalised biochemical treatment targets. Optimal treatment choices should be guided by strict requirements of organizations such as the FDA, demanding treatment effects to be estimated under actual conditions of use. Various improvements in design and analysis are recommended for future randomised controlled T3/T4 combination trials. [ABSTRACT FROM AUTHOR]