Diagnostic concepts like “subclinical hypothyroidism” have become cognitive barriers to understanding the adaptations and dysfunctions of the aging hypothalamus-pituitary-thyroid (HPT) axis.
Thyroid diagnostic categories are usually based on whether TSH and FT4 are in range, above range, or below range, in relation to an age-blind reference range. These are convenient biochemical stereotypes.
These stereotypes have convinced many people that “thyroid function” is easily discerned by judging these two hormone levels by their separate reference intervals.
Fortunately, leading thyroid scientists are breaking down stereotypes. They are trying to show physicians that thresholds of dysfunction and health risk are not necessarily located at the reference limits of isolated TSH and FT4 hormone levels (Ling et al, 2018; Sheikh et al, 2018).
Age and many other clinical factors transform the “function” of the HPT axis, shifting the thresholds between euthyroidism and dysfunction and placing them within or outside of the reference ranges, as I’ve outlined in several recent posts reviewing the science:
- “Age bias may hide hypothyroidism under a normal TSH“
- “Pediatric and teenage TSH, FT4, and FT3 levels“
- “Age, sex and TSH-FT4-FT3 relationships: Advanced lessons”
In this article, I present and discuss the “four phenotypes” of the unstable aging HPT axis from Jennifer Mammen and colleagues’ 2017 publication.
A rare strength of Mammen’s study was that they examined changes in older adults’ hormone levels over many years. By including time as a variable and approaching the analysis longitudinally, this research group was capable of distinguishing between “stable” and “unstable” aging phenotypes.
They looked very carefully at the significant minority with “unstable” biochemistry. They discovered four different phenotypes of instability, two with rising TSH and two with falling TSH.
Mammen found that changes may go in four major directions away from the mean, not just toward hypo- or hyperthyroidism. Two of the transformations in advanced age involved apparent changes in pituitary function.
A major lesson from their work is that gradual departures from an age-specific mean or median and shifting TSH-FT4 hormone relationships are the key diagnostic signals that something is amiss, and health may be at risk.
Mammen’s work demonstrated that relative changes in TSH-FT4 relationships, even when FT4 is within the reference range, were associated with higher mortality rates. Changes toward primary hypothyroidism were associated with the highest hazard ratios.
As we age, and as we encounter other metabolic stressors, TSH-FT3-FT4 hormone relationships change. If pituitary TSH is rising or falling in the attempt to compensate for a mild thyroid dysfunction, is it failing or succeeding? Is the aging pituitary’s TSH secretion rising or falling because it’s misbehaving and causing a distortion in thyroid hormone levels?
The TSH category and FT4 category can’t answer these vital questions, but changes in hormone relationships and departures from age-based medians can help discern dysfunction and health risk.
The framework of Mammen’s 2017 study
In Mammen and team’s introduction, they questioned the presumption that the TSH upper reference limit accurately distinguishes between euthyroidism and hypothyroidism:
When the hypothalamic–pituitary–thyroid [HPT] axis is intact, TSH rises in response to thyroid hormone deficiency to increase thyroid hormone production.
However, higher TSH levels during aging may reflect changes other than primary thyroid gland failure.
For example, decreased TSH bioactivity would require greater TSH production to maintain stable thyroid hormone levels, with neutral metabolic effects.
Alternatively, decreased pituitary responsiveness to thyroid hormone would lead to both higher TSH and thyroid hormone levels with potential peripheral metabolic over-activation.
Additionally, changes in thyroid homeostasis might reflect appropriate adaptation to other morbidities, such as occurs with non-thyroidal illness—metabolic changes for which pharmacologic intervention has not been shown to be beneficial (8).(Mammen et al, 2017)
The opening premise about the “intact” HPT axis ought to be questioned by the end of this passage.
These paragraphs explain various changes to the HPT axis. They can sometimes be adaptive (“maintain stable thyroid hormone levels”) and sometimes maladaptive (“potential peripheral metabolic over-activation”).
- Where is the boundary between the “intact” and the “transformed” HPT axis?
- Why do they think the HPT axis remains “intact” during thyroid failure but only breaks down during pituitary and metabolic failure?
- How does one distinguish between an adaptive vs. maladaptive change in the HPT axis?
- Perhaps when two changes occur simultaneously, i.e. mild thyroid failure and mild pituitary failure, it compromises the ability of the HPT axis to adapt?
- When does a statistical association in a group with a certain characteristic, such as “elderly” or “normal TSH” fail to apply to an individual with that characteristic?
Keep these questions in mind throughout the discussion, because these are the questions raised by the claim in their title: “Unstable thyroid function in older adults is caused by alterations in both thyroid and pituitary physiology and is associated with increased mortality.”
Mammen’s methods and population
The American research group used a research database called the Baltimore Longitudinal Study of Aging (BLSA) to examine associations between TSH, FT4 and FT3 and survival.
These data were derived from a subset of relatively healthy 640 individuals that had at least three visits with hormone measurements to enable longitudinal study.
- The average follow-up time for an individual was 7.7 years.
- Participants had at least three TSH and FT4 measurement pairs. 474 of these patients also had FT3 measurements as well.
- They were not taking any medications known to interfere with the HPT axis (thyroid hormone preparations, antithyroid medications, oral glucocorticoids within three months, lithium, estrogenic compounds, anti-estrogenic therapies, amiodarone, carbamazepine, phenobarbital, or phenytoin).
- Between 4-5% of the population had their data excluded after they began thyroid hormone therapy.
- Thyroid antibodies were not tested.
Therefore, the study included people with chronic non-thyroidal illnesses such as heart, liver, or kidney diseases, and people with diabetes who dosed metformin, a drug known to reduce TSH in certain clinical circumstances. It also included people with thyroid antibodies that are known to distort TSH relationships with thyroid hormones.
Therefore, these findings should not be misapplied to people on thyroid therapy, or people dosing certain drugs, or people with antibodies that are known to distort TSH-FT4 relationships.
Mammen and team are correct to point out that their methods also do not prove cause-effect hypotheses, although they can be interpreted within a “plausible” framework of causation:
“It is critical to recognize that the association observed with changes in TSH and survival is not a causal demonstration that the change in thyroid function itself is underlying increased risk.
It is plausible and perhaps even likely that in some participants, TSH changes reflect the development of underlying comorbidities, in parallel with non-thyroidal illness, which could drive the association with reduced survival.”(Mammen et al, 2017)
The second sentence of this passage demonstrates that the interpretation of the findings requires an understanding of thyroid physiology and molecular biology that suggests possible explanatory cause-effect relationships.
The researchers drew on their understanding of “nonthyroidal illness syndrome” (NTIS), which is known to cause distortions in TSH secretion rates. In particular,
- During the acute and chronic phases of NTIS, TSH may be prevented from rising, and may even fall concurrent with severe TT3 and FT3 reductions and eventual FT4 reductions.
- During the recovery phase of NTIS (if recovery occurs), TSH often rises high to support the replenishment of depleted T3, but if this occurs, it may either succeed or fail.
- (see Van den Berghe, 2014, Langouche et al, 2019; Braithwaite, 2015)
Mammen’s 2017 findings
Stable vs. unstable HPT axis
The most common state by far is “stable” pituitary and thyroid biochemistry, as demonstrated in the graphs below.
The box-and-whisker graphs demonstrate that the majority of individuals’ TSH and FT4 remained stable, but the FT3 mean (bars in the middle of boxes) gradually fell to a small degree as the initial age rose higher.
When all four “unstable” phenotypes were merged into one data set with the “stable” subjects’ data, Mammen and colleagues discovered the same pattern found in other studies. With increasing age, there was a mildly rising TSH, fairly constant FT4, and mildly falling FT3.
It was ethical of Mammen and colleagues to include the whiskers and dots representing outliers. This is something most researchers omit for the sake of a visually cleaner graph that focuses on medians.
Some people’s pituitary, metabolic, and/or thyroid function is unstable (“thyroid function” is a too narrow phrase to describe all the changes in the HPT axis, as shown below).
The researchers highlight the significance of the error bars and dots outside the interquartile range boxes:
“the magnitude of the change in thyroid function is highly variable, and the variability is significantly greater in the oldest age group (p < 0.001 using Bartlett’s test for equal variance).”(Mammen et al, 2017)
The degree of variability increases with age. Therefore, a stereotype of “stable” aging would fail to see the increasing human diversity and the increasing departure from one’s baseline levels.
However, the graphs have three shortcomings that make interpretation difficult:
- They give no comparison to the hormone levels of the general population,
- One cannot tell where the means are located within a reference range, and
- The different scales on the Y axes make it look like these hormones varied to an equal degree, but that is not true, either in absolute or relative terms.
Therefore, I offer the following aids to interpretation:
How do these values compare to the general population of mixed age groups? Mammen and colleagues gave reference ranges in a supplementary data file. Since ranges changed over the years, for calculation purposes I chose the ranges that corresponded most closely with those by Jonklaas and colleagues (in pmol/L, in parentheses) who used the same Vista Siemens immunoassay platform:
- FT4 0.76–1.46 ng/dL (9.7–18.9 pmol/L)
- FT3 1.8–4.2 pg/mL (2.76–6.45 pmol/L)
Where are the means located within the hormone’s general population reference interval? There is no perfect method of translating results between assay platforms. Nevertheless, “percent of reference interval width” gives an approximation. Mammen’s baseline mean values in the graph above correspond to these percentages of reference range, using the ranges above:
- TSH 2.6 mIU/L = 61.1% of reference width.
- FT4 0.97 ng/dL = 29.6% of reference width.
- FT3 3.01 pg/mL = 50.8% of reference width.
The FT4 is low-normal, but the mean FT3 is by no means “low” or “low-normal” in this population.
Which hormones in Mammen’s graphs underwent the greatest relative changes away from the median or mean?
Since TSH has a strongly skewed population distribution with relatively low medians between 1.5 and 1.6 mIU/L (Ganslmeier et al, 2013), the median (50th percentile) is more useful than the mean.
Fortunately, Mammen and team provided a TSH graph with absolute levels and medians, in the “supplementary data” to their 2017 article.
Mammen and colleagues explained that in the large dataset of 1,294 individuals, the baseline mean (not median) TSH levels changed for each age group:
- 2.4 mIU/L in those <60 years old (n = 464)
- 2.6 mIU/L in those 60–69 years old (n = 291),
- 2.7 mIU/L in those 70–79 years old (n = 327),
- 3.2 mIU/L in those >79 years old (n = 206).
The larger group’s mean FT4 remained the same:
- 0.98 ng/dL mean in the youngest age group
- 0.99 ng/dL mean in the oldest age groups
In contrast, the larger group’s mean fT3 and age had a significant negative correlation (p < 0.01):
- 3.2 pg/mL mean in the youngest age group
- 2.9 pg/mL mean in the oldest age groups
They said “Restricting the analyses to the phenotyping cohort yielded essentially identical results” for FT3 and FT4.
In their phenotyping subset of 640 people, one can quantify the relative changes as a percentage of the analyte’s reference width:
- TSH +/- 1.0 mIU/L change = +/- 27.8% of the reference range
- FT4 +/- 0.05 ng/dL change = +/- 7% of the reference range
- FT3 +/- 0.2 pg/mL change = +/- 8.3% of the reference range
If there is a half-visible dot for FT3 at -0.4 from the mean in the >80 group, and if their group’s mean was 2.9, that outlier’s FT3 level was at 2.5 pg/mL, still 34% of reference range.
Therefore, in their subset population of 640 people, 474 of whom had FT3 data, there is a lack of evidence of “nonthyroidal illness syndrome” (NTIS). This syndrome classically presents with a significantly reduced FT3:FT4 ratio with FT3 levels in the very low-normal to low range (Warner & Beckett, 2010).
NTIS is known to elevate mortality rates. Despite the apparent absence, mildness, or low prevalence of NTIS in this population, the “unstable” phenotypes within the reference range were associated with higher mortality rates.
The four unstable phenotypes
Mammen and colleagues were able to identify four “unstable” phenotypes of TSH-FT4 shifts in aging:
- A: Rising TSH, Falling FT4 (toward primary hypothyroidism)
- B: Rising TSH, Rising FT4 (toward pituitary TSH hypersecretion or resistance to thyroid hormone)
- C: Falling TSH, Falling FT4 (toward pituitary TSH hyposecretion or central hypothyroidism)
- D: Falling TSH, Rising FT4 (toward primary hyperthyroidism)
They explain that in these four “unstable” phenotypes either the thyroid or the pituitary could experience altered function:
“Increasing or decreasing fT4 with a negatively correlated change in TSH would suggest thyroid gland disease,
while positively correlated TSH and fT4 changes would reﬂect altered hypothalamic–pituitary (central) alterations.”(Mammen et al, 2017)
Mammen’s team provided separate graphs for each phenotype:
In addition, their team provided a single graph with four quadrants. I have added color and arrows to highlight the direction of changes in their graph below.
Notice that these phenotoypes are not based on TSH and FT4 reference intervals but on rising and falling TSH-FT4 relationships compared to each individual’s first measurement.
The midpoint of the two axes, at 0.00, is where the individual’s first TSH/FT4 test was. The distance of the dot from the center is the amount the hormone relationship changed “per year.”
The people with stability in both hormone levels, irrespective of their hormone levels, are represented by the dots in the center of the graph.
These relative changes in FT4 can be significant even though they appear to be small-scale compared to the reference interval. A change of FT4 +/- 0.5 ng/dL constitutes +/- 8% of the reference interval width, but a 5% absolute change in hormone level.
In fact, there are more than 4 phenotypes of instability here. There are eight, but Mammen and team chose to simplify.
- Unstable phenotypes A, B, C, and D move in “X-shaped” directions away from the center. They involve TWO hormones changing simultaneously.
- Unstable phenotypes E, F, G, and H (not discussed by Mammen and colleagues) move in “+ shaped” directions, following one of the axis lines away from the center. They involve only ONE hormone changing (either the FT4 or the TSH) while the other hormone level remained stable.
This graphic highlights the malleability of the HPT axis.
These distinctive phenotypes cannot be seen in population-wide studies because they disappear when grouped with the larger number of people whose thyroid and pituitary function was stable. They can only be seen by following individuals over many years to discover and compare small subgroups.
The evidence contradicts the widespread belief that TSH-FT4 relationships are “inverse log-linear” — as one hormone changes, the other hormone must change within the parameters predicted by a mathematical model.
If the HPT axis were truly defined by inverse log-linear TSH-FT4 relationships, then the unstable phenotypes would be aligned with a straight trendline from the upper left quadrant down to the lower right quadrant. Instead, there is a scatter away from the center, even in the quadrants that represent thyroid gland dysfunction. TSH cannot always predict FT4 or vice versa when the two levels are within or close to their reference ranges.
This analysis should make anyone ask deeper questions about stereotypical category-based diagnoses. If the TSH is mildly high, mildly low, or normal, and FT4 is “normal,” then,
- Where are these hormones going?
- How far away from the population medians are they?
- Is the FT4 falling and TSH rising over time? or is the opposite movement occurring?
- Are the two hormones rising or falling in parallel?
- Is this a stable situation or are the hormone levels and relationships slowly or rapidly changing?
Associations between unstable phenotypes and mortality
The “unstable” groups were associated with increased risk of death even when the analysis was controlled for age, sex, ethnicity, and smoking status. Here are the adjusted hazard ratios for the four phenotypes:
- A: HR 9.6. Rising TSH, Falling FT4 (toward primary hypothyroidism)
- B: HR 3.3. Rising TSH, Rising FT4 (toward pituitary TSH hypersecretion or resistance to thyroid hormone)
- C: HR 3.8. Falling TSH, Falling FT4 (toward pituitary TSH hyposecretion or central hypothyroidism)
- D: HR 6.4. Falling TSH, Rising FT4 (toward primary hyperthyroidism)
Therefore primary hypothyroidism appeared to be the most dangerous phenotype, associated with 9.6x higher mortality rates.
The least dangerous phenotype was associated with rising TSH and rising FT4.
Why did they say the TSH rose? due to “survival bias.” But this may be misinterpreted to mean that a high TSH confers survival.
Stop the myth that a rising TSH benefits all elderly people!
Their discussion pointed out that “a survival bias may explain the observed higher TSH in older populations.” But here they were ONLY talking about the majority of the elderly with “stable thyroid function” and stable TSH:
- Those who entered the study aged 70-79 had a mean baseline TSH at 2.8 mIU/L and their cohort kept the same mean TSH for an average of 8.2 years of follow-up.
- Those who entered the study aged >80 had a mean baseline TSH at 3.2 mIU/L and their cohort kept the same mean TSH for an average of 4.9 years of follow-up.
In contrast, there is no survival bias for people whose TSH rises while FT4 changes, or whose TSH falls while FT4 changes.
Therefore the “high TSH” category does not act on its own to grant this “survival bias.” It must cooperate with a healthy-enough thyroid gland and thyroid hormone metabolism to grant survival. TSH is only a benefit to survival if one’s age-appropriate TSH successfully provides a person with enough FT3 and FT4.
This is why it was so shocking and unethical when the American Thyroid Association guidelines for the treatment of hypothyroidism suggested that hypothyroid senior citizens on thyroid therapy should probably have an elevated TSH (Jonklaas et al, 2014).
They even made this recommendation admittedly based on no clinical trials of the safety or efficacy of thyroid therapy in the elderly with a high TSH. This mistake of jumping to conclusions based on theory, without evidence, reveals the field’s tendency to blindly adopt the biochemistry of healthy populations as a guide to therapy in thyroid-disabled populations.
An elevated TSH helps some UNtreated seniors’ thyroid glands work harder to maintain their healthy FT4 and FT3 levels. But how is an elevated TSH supposed to help someone who relies more on thyroid hormone medication than a TSH-responsive thyroid? Can a higher TSH stimulate their thyroid hormone tablets to produce more FT4 or FT3? Of course not.
Frequency of unstable phenotpyes
The entire population was selected for its overall good health, so it is unsurprising that only a small minority experienced instability in their HPT axis.
“Only 9.5% of those <60 years old are characterized as having changing thyroid function by this definition compared to 32% of those >80 years old.”(Mammen et al, 2017)
Three of the four phenotypes had approximately equal frequency in this population:
- The phenotypes A (30 subjects, 4.6%) and B (21 subjects, 3.2%) both have a rising TSH, and type B is a pituitary alteration.
- The phenotypes C (29 subjects, 4.5%) and D (32 subjects, 5%) both have a falling TSH, and type C is a pituitary alteration.
In Mammen’s 2017 study, hypothyroidism caused by a failing pituitary or central hypothyroidism (29 people) occurred at the same rate as a failing thyroid or primary hypothyroidism (30 people).
However, the phenotypes were differently associated with aging:
- Phenotypes A and D involving thyroid gland dysfunction were associated with increasing age, hinting at age-related thyroid gland hypoactivity.
- Phenotype B, Rising TSH/ Rising fT4, also significantly increased among the oldest age group, hinting at age-related reduced TSH bioactivity, and/or reduced pituitary sensitivity to thyroid hormone in some.
- However, the phenotype C (central hypothyroidism) was not associated with age. Instead, it was strongly associated with smoking within the past 10 years. This is good to know. It highlights that pituitary failure can happen at any time, including old age. It may also be correlated with exposure to toxic endocrine disruptors like those found in cigarette smoke.
Regression to the mean was not universal.
The “spontaneous normalization of TSH” is a common concept in studies of subclinical hypothyroidism. If a high TSH frequently falls into the normal range over time without treatment, it is often used to imply that hypothyroidism is transient or nonexistent. The concept is related to regression to the mean.
“Regression to the mean is a statistical phenomenon that can make natural variation in repeated data look like real change. It happens when unusually large or small measurements tend to be followed by measurements that are closer to the mean.”(Barnett et al, 2005)
Unlike Mammen’s team, others who have discussed spontaneous TSH normalization have entirely ignore the precise movements of TSH and FT4 levels and focus only on categorizing FT4 as high, normal or low (for example, Meyerovitch et al, 2007). Such scholars had no interest in understanding hormone relationships or even health risk.
Mammen and team discovered that phenotype A (primary hypothyroidism) in which the FT4 fell while the TSH rose was the only pattern not associated with a baseline TSH regressing toward the mean.
All the other three phenotypes returned to the mean, even phenotype D, hyperthyroidism. All other phenotypes could be predicted to regress based on their initial TSH or FT4. The primary hypothyroid phenotype was not predictable by its baseline TSH and FT4.
If the TSH was once in the “subclinical” zone and then “normalized” by itself, was the fall in TSH due to phenotype C, pituitary failure? It’s wise to check the FT4 and FT3 to be sure TSH normalized for a good reason, without causing an HPT axis breakdown.
This is why the direction of FT4 instability is important to discern. Thyroid hypofunction is often permanent and increasingly worsens over time. In contrast, the most frequent causes of endogenous hyperthyroidism either fluctuate with TSH-receptor antibody titres or the life cycle of a T3-secreting thyroid nodule and iodine intake.
The behavior of FT3 in the four phenotypes
Notice in the graphs that in phenotype A, FT3 mildly rises while FT4 falls, as a compensatory mechanism to minimize the harm of hypothyroidism.
In fact, the only phenotype in which TSH and FT3 do not rise or fall in parallel is D, hyperthyroidism. This is because TSH-receptor signaling is no longer under the control of TSH hormone. Endogenous hyperthyroidism is characterized by TSH-independent thyroid hyperfunction.
The fundamental physiology shown here is that FT3 is enhanced by a rise of TSH receptor signaling in healthy thyroid gland tissue, even if T4 secretion rates are falling.
- Long ago, research by Salvatore and team in 1996 revealed that intrathyroidal T4-T3 conversion is enhanced by TSH receptor signaling.
- Cellular-level research by Citterio et al in 2017 demonstrated that T3 de novo synthesis in the thyroid is preferentially enhanced by TSH-receptor signaling.
- Berberich and team in 2018 called this the “TSH-T3 shunt” within the thyroid gland, and it was further demonstrated in the findings by Hoermann et al, 2020, which showed how the FT3 is maintained or mildly rises in early mild hypothyroidism.
- According to Beukhof et al’s 2018 examination of TSH injections in people with total thyroidectomies, as TSH rises, it cannot enhance circulating T3 when there is no thyroid tissue.
Consider the omission of FT3 from these models.
Despite the interesting behavior of FT3 in graphs, they explain why FT3 was omitted from models:
“Because of the smaller population with fT3 values and a lack of correlation between fT4 and fT3, including fT3 in the phenotyping definitions prevented meaningful analysis of predictive variables and survival.”(Mammen et al, 2017)
Therefore, they admit that their research insights are compromised by the lower rate of FT3 testing in their sample population, a problem that is exacerbated by penny-pinching policies that prevent FT3 testing in most cases.
It is so unfortunate that FT3 is undervalued by health care administrators. Human biology “defends” circulating T3 hormone (Abdalla & Bianco, 2014), while health care systems do not.
Sufficient supply of the free fraction of T3 hormone is essential to health because only the ~0.3% free fraction of T3 is carried into cells by active transmembrane transporters. Within cells, T3 derived from circulating FT3 complements tissue-specific and cell-specific rates of intracellular T4-T3 conversion.
In fact, some cell types do not possess any enzymes that can convert T4 to T3. Certain vital cells, such as neuronal cells, depend utterly on FT3 for the bulk of their nuclear thyroid hormone signaling (Bianco et al, 2019).
Next, it is insightful that Mammon found “the lack of correlation between FT4 and FT3” within the reference range of untreated individuals, a pattern which others had already confirmed (Hoermann et al, 2013). This lack of correlation is based on physiology because the two hormones are regulated semi-independently:
- FT4 changes mainly derive from thyroid function/dysfunction, while
- FT3 changes derive from thyroid function and thyroid hormone metabolism.
The dual derivation of FT3 illustrates that FT3 is so important to physiology that it must have a backup system for its supply. This is also a hint as to why HPT axis “adaptation” may fail when more than one T3-defense system fails, even mildly, at the same time.
This is the main reason why subclinical TSH-FT4-based diagnoses cannot strongly predict health outcomes in individuals, even though they still have mild statistical significance.
- As a result of FT3 being partly dependent on metabolic function, one cannot use a TSH and FT4 level to predict a FT3 level.
- As a result of every cell’s T3 signaling being dependent on circulating FT3 to some degree, one cannot use a FT3-blind model to predict T3 sufficiency in cells throughout the body.
A better inclusion of FT3 is gained by using the FT3:FT4 ratio as a variable, as was done by Strich (2016) in their analysis of hormone relationships in aging (See “Age, sex and TSH-FT4-FT3 relationships: Advanced lessons“).
Fortunately, this landmark study in 2017 paved the way for Mammen’s more recent work under the name of a different first author (Abbey et al, 2022), which examines FT3:FT4 and FT4 thresholds for adaptive response versus maladaptive hypothyroidism in aging.
A return to the questions raised by the study’s premises
Q: Where is the boundary between the “intact” and the “transformed” HPT axis?
- There is no reason why pituitary flexibility / transformation should not be an inherent feature of the intact HPT axis, because TSH rises in advanced age while FT4 medians remain stable.
Q: Why do they imply that the HPT axis remains “intact” during thyroid failure but only breaks down during pituitary and metabolic failure?
- There is no reason why one should think that the HPT axis is always “intact” when primary hypothyroidism exists.
- What they seem to imply is that pituitary negative feedback function is intact. “Those with alterations in primary thyroid gland function demonstrated intact negative feedback.”
- But the negative feedback of thyroid hormone on TSH secretion does not define the entire HPT axis, which is the mistaken logic in this sentence: “When the hypothalamic–pituitary–thyroid [HPT] axis is intact, TSH rises in response to thyroid hormone deficiency to increase thyroid hormone production.”
- The fundamental presumption is that primary hypothyroidism always exists in isolation from a pituitary and metabolic failure, and this presumption was not questioned by the study but was reinforced by it.
Q: How does one distinguish between an adaptive vs. maladaptive change in the HPT axis?
- Thresholds between euthyroidism and risk-associated HPT axis dysfunctions are not located at the limits of the TSH reference range, nor at the limits of the FT4 reference range.
- The study did not establish quantitative thresholds, only described risk associations with four directions of HPT axis alteration.
- The unstable phenotypes likely increase in severity as TSH loses control over thyroidal secretion, as TSH and FT4 depart from their age-specific medians, and as FT3 levels become inappropriate as a supplement to the FT4 supply and T4-T3 conversion rate.
- True hypothyroidism in the elderly is characterized by a rising TSH and a falling FT4, in contrast with a rising TSH concurrent with a rising or stable FT4.
- Movements toward hypothyroidism carry the highest hazard ratio.
- Hypothyroidism cannot be predicted by baseline TSH or FT4 hormone levels.
- Hypothyroidism will not spontaneously normalize itself by regressing toward the mean.
A: Perhaps when two changes occur simultaneously, i.e. mild thyroid failure and mild pituitary failure, it compromises the ability of the HPT axis to adapt?
- Yes, it’s likely. A person with concurrent mild thyroid failure plus mild pituitary failure, or mild thyroid failure plus the metabolic dysregulation of nonthyroidal illness, will fare worse than one who suffers only one HPT axis dysfunction.
- On the other hand, a disorder of pituitary TSH hyposecretion may be counterbalanced by mild thyroid hypersecretion or autonomy.
- Few will notice two concurrent disorders because diagnostic models, even Mammen’s, tend to treat each disorder in isolation from the other.
Q: When does a statistical association in a group with a certain characteristic, such as “elderly” or “normal TSH” fail to apply to an individual with that characteristic?
- One should not believe that the HPT axis is inherently stable in aging. The 4 phenotypes of unstable HPT axis function constituted 17.3% of the 640 participants.
- One should not believe that a normal TSH is always euthyroid and healthy. Unstable phenotypes may be buried within the normal reference range.
- One should not believe that “spontaneous normalization” of TSH is always a return to euthyroidism, for the same reason.
- One should not believe that pituitary failure is rare as people say it is. Mammen found the rate of mild subclinical central hypothyroidism/ pituitary failure was 3.2% within this otherwise healthy population and it carried a hazard ratio of 3.8 compared to seniors with stable thyroid function. Most physicians and scientists are not trained to expect pituitary failure or recognize its existence in data sets.
- Pituitary failure is not necessarily a distinctive feature of aging, because it did not occur at a higher frequency as participants aged.
It is so unfortunate for seniors with unstable thyroid function that the HPT axis is vulnerable to so many medical misinterpretations.
Hiding underneath a high or “normal” TSH in an elderly individual may be an unexpected profile of Free T3 (FT3) and Free T4 (FT4) concentrations that may or may not be associated with increased risk.
If three people have the same TSH level of 5.00 mIU/L — a 12-year-old child, a 30-year old man, and an 85 year old female, their thyroid hormone levels and relationships are likely to be very different, even if they are “euthyroid.” Which one is hypothyroid? Don’t expect their TSH to answer the question, nor the categorical position of FT4 in or out of its range.
Medical faith in an age-blind, sex-blind, FT3-blind model of the HPT axis leads to both false-positive and false negative diagnoses (Sheikh et al, 2018; Ling et al, 2018).
Therefore, it’s time to put away childish blind faith in the power of two hormones’ reference intervals to define thyroid hormone status.
It’s time for physicians and scientists to break down their cognitive barriers by exploring the science of thyroid hormone relationships, including the FT3:FT4 ratio, which Mammen did not examine in this study.
No matter how cheap and convenient it is to screen TSH and then test FT4 only if TSH falls outside of an age-blind range, that system is relying on incorrect presumptions from the 1990s that require revision.
It is neither cheaper nor more convenient for an undiagnosed, untreated, or maltreated elderly person’s HPT axis to worsen their non-thyroidal health disorders. It likely costs the health care system more money until they die an early death, leaving their families and communities without their wisdom, joy, and service.
References for all articles cited in the “analyzing normal lab results” series are in a separate post.