Reference intervals in the diagnosis of thyroid dysfunction: treating patients not numbers

Jonklaas, Jacqueline; Razvi, Salman

doi:10.1016/s2213-8587(18)30371-1

Cited by 70 publications

(73 citation statements)

References 111 publications

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“…1,36 Static assumptions in thyroid health may not hold for conditions of glandular stress. 3,38,40 Larger studies are needed to confirm and extend our findings towards a potential future clinical utility of such models, possibly app-based. In healthy subjects, T4-T3 conversion in extra-thyroidal organs is generally accepted as the main T3 source, the thyroidal contribution amounting to approx.…”

Section: Discussionmentioning

confidence: 66%

“…35 Our findings portray a more flexible view of the hypothalamic-pituitary-thyroid regulation, compared to the classical feedback model. 3,[38][39][40] Unlike univariate statistical range considerations for single parameters, set points, as modelled here, are fundamentally more well-founded and may be more suitable for individualised decision-making. This includes the relative importance of various contributions to the circulating T3 pool.…”

Section: Discussionmentioning

confidence: 99%

“…19,23 This is characteristic of a healthy individual, displaying far less variation, compared to the much wider reference ranges of the population's TSH and thyroid hormone concentrations. 3,[38][39][40] Unlike univariate statistical range considerations for single parameters, set points, as modelled here, are fundamentally more well-founded and may be more suitable for individualised decision-making. 3,38,40 Larger studies are needed to confirm and extend our findings towards a potential future clinical utility of such models, possibly app-based.…”

Section: Discussionmentioning

confidence: 99%

“…2 Conversely, the laboratory constellation of a TSH measurement above its reference range, accompanying an FT4 concentration still within its reference range, has been designated subclinical hypothyroidism. [2][3][4] Consequently, the process of clinical decision-making has been dominated by measuring TSH and FT4, the determination of the biologically more active thyroid hormone triiodothyronine (T3) being relegated to an insignificant role. [2][3][4] Consequently, the process of clinical decision-making has been dominated by measuring TSH and FT4, the determination of the biologically more active thyroid hormone triiodothyronine (T3) being relegated to an insignificant role.…”

Section: Introductionmentioning

confidence: 99%

“…2 Subclinical hypothyroidism is generally regarded as a thyroid disease, although the transition from the euthyroid to the hypothyroid state is poorly defined, resulting in a schism between guideline-based diagnostic criteria and therapeutic recommendations. [2][3][4] Consequently, the process of clinical decision-making has been dominated by measuring TSH and FT4, the determination of the biologically more active thyroid hormone triiodothyronine (T3) being relegated to an insignificant role. This view stemmed from a physiological understanding of thyroid hormone transporters actively importing or exporting T4 and T3, deiodinating enzymes converting T4 into the biologically more active metabolite T3 and thyroid hormone receptors binding to nuclear DNA, thereby exerting a plethora of genomic T3 actions.…”

Section: Introductionmentioning

confidence: 99%

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Triiodothyronine secretion in early thyroid failure: The adaptive response of central feedforward control

Hoermann

Pekker

Midgley

et al. 2020

Eur J Clin Investigation

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Background: Defined by thyroid-pituitary feedback control, clinical diagnosis of hypothyroidism and hyperthyroidism has become synonymous with TSH measurement. We combined in silico analysis and in vivo data to explore the central influences on thyroidal T3 production. Materials & methods:A system of five coupled first-order nonlinear parameterised ordinary differential equations (ODEs) is used to model the feedback control of TSH and TRH by thyroid hormones together with the feedforward control of thyroidal T3 secretion and enzymatic T4-T3 conversion. Dependencies of the stable equilibrium solutions of this ODE system, that is the homeostasis of the underlying physiological process, on the system parameters were investigated whether they accounted for clinical observations. Results: During the modelled transition to hypothyroidism, central control imposed an increasing influence in maintaining serum FT3 levels, compared to peripheral conversion efficiency. Numerical continuation analysis revealed dependencies of T3 production on different elements of TSH feedforward control. While T4-T3 conversion provided the main T3 source in euthyroidism, this was overtaken by increasing glandular T3 secretion when thyroid reserve declined. The computational results were in good agreement with data from untreated patients with autoimmune thyroiditis. Conclusions: Dependencies revealed in the expression of control differ in thyroid health and disease, using a physiologically based mathematical model of combined feedback-feedforward control of the hypothalamic-pituitary-thyroid regulation.Strong T3-protective mechanisms of the control system emerge with declining thyroid function, when glandular T3 secretion becomes increasingly influential over conversion efficiency. This has wide-ranging implications for the utility of TSH in clinical decision-making. K E Y W O R D Sautoimmune thyroiditis, mathematical model, personalised medicine, set point, subclinical hypothyroidism, T3 secretion

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Section: Discussionmentioning

confidence: 66%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Triiodothyronine secretion in early thyroid failure: The adaptive response of central feedforward control

Hoermann

Pekker

Midgley

et al. 2020

Eur J Clin Investigation

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A U‐shaped association between serum albumin with total triiodothyronine in adults

Zhang

Xie

2022

Clinical Laboratory Analysis

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Background Thyroid dysfunction is a common thyroid disorder in our life and its symptoms are non‐specific, therefore the diagnosis of thyroid dysfunction is important for patients. Albumin (ALB) can carry thyroid hormones to their sites of action as a way to achieve rapid delivery of thyroid hormones to the tissues. The purpose of this study was to investigate the relationship between serum ALB levels and total triiodothyronine (TT3) in adults. Methods Data from the 2007–2012 National Health and Nutrition Examination Survey (NHANES) were used to examine the association between ALB and TT3 using multivariate logistic regression models. Fitting smoothed curves and generalized weighted models were also used. Results The analysis included a total of 7933 participants that we found an independent positive relationship between ALB and TT3 among participants [0.006 (0.003, 0.009)]. In men, there was a significant positive correlation between ALB and TT3, whereas in women ALB and TT3 suggested a significant negative correlation. Moreover, our study revealed that the independent association between the levels of ALB and TT3 was significant in Non‐Hispanic White, but not in Non‐Hispanic Black. Notably, we found a U‐shaped association between ALB and serum TT3 in total participants (inflection point for ALB: 41 g/L) and females after adjusted covariates (inflection point for ALB: 46 g/L). Conclusions We found a U‐shaped relationship between serum ALB and TT3 with infection point at 41 g/L for ALB, which may provide a reference for future screening in adults with thyroid dysfunction.

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Modeling conditional reference regions: Application to glycemic markers

Lado-Baleato

Roca‐Pardiñas

Cadarso‐Suárez

et al. 2021

Statistics in Medicine

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Many clinical decisions are taken based on the results of continuous diagnostic tests. Usually, only the results of one single test is taken into consideration, the interpretation of which requires a reference range for the healthy population. However, the use of two different tests, can be necessary in the diagnosis of certain diseases. This obliges a bivariate reference region be available for their interpretation. It should also be remembered that reference regions may depend on patient variables (eg, age and sex) independent of the suspected disease. However, few proposals have been made regarding the statistical modeling of such reference regions, and those put forward have always assumed a Gaussian distribution, which can be rather restrictive. The present work describes a new statistical method that allows such reference regions to be estimated with no insistence on the results being normally distributed. The proposed method is based on a bivariate location‐scale model that provides probabilistic regions covering a specific percentage of the bivariate data, dependent on certain covariates. The reference region is estimated nonparametrically and the nonlinear effects of continuous covariates via polynomial kernel smoothers in additive models. The bivariate model is estimated using a backfitting algorithm, and the optimal smoothing parameters of the kernel smoothers selected by cross‐validation. The model performed satisfactorily in simulation studies under the assumption of non‐Gaussian conditions. Finally, the proposed methodology was found to be useful in estimating a reference region for two continuous diagnostic tests for diabetes (fasting plasma glucose and glycated hemoglobin), taking into account the age of the patient.

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Reference intervals in the diagnosis of thyroid dysfunction: treating patients not numbers

Cited by 70 publications

References 111 publications

Triiodothyronine secretion in early thyroid failure: The adaptive response of central feedforward control

Triiodothyronine secretion in early thyroid failure: The adaptive response of central feedforward control

A U‐shaped association between serum albumin with total triiodothyronine in adults

Modeling conditional reference regions: Application to glycemic markers

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