I think diogenes might be well already aware of this - but is also likely to have a firm opinion.
That the authors of this letter feel it necessary to make this poke-in-your-eye obvious statement is a very sharp criticism:
we want to emphasize a critical fact that it is impossible for the TSH value of one particular individual to exert any influence on the free T4 of a totally different individual and vice versa because each person is a biologically separate entity.
Letter to the Editor: The Ultimate Proof of the Log-linear Nature of TSH-Free T4 Relationship by Intraindividual Analysis of a Large Population
Simon L. Goede Melvin Khee-Shing Leow
The Journal of Clinical Endocrinology & Metabolism, Volume 101, Issue 5, 1 May 2016, Pages L57–L58, doi.org/10.1210/jc.2016-1439
Published:
01 May 2016
We read this intriguing article by Rothacker et al (1) with great interest. They state, “When linear models are applied to individuals grouped according to median free T4, variation in slope and intercept across the free T4 domain indicate a nonlinear relationship between log TSH and free T4. Thus, a log-linear relationship between TSH and free T4 within individuals can be reconciled with a nonlog-linear relationship across the population.” However, this conclusion deserves further consideration.
First, whereas their statistical modeling is sound, such models of data are the result of statistical techniques on raw data to derive empirical mathematical functions, which balance goodness of fit and simplicity with maximum predictive accuracy. Yet fitting linear, cubic, quartic, quadratic, or error curves (2) on pooled data mixed with erroneous observations without any underlying theoretical framework or first physiological principles for justification is an approach often riddled with flaws.
Second, given the fundamental statistical tenet that accuracy increases with greater sample size, their statement “as the number of observations per individual increased, so did the proportion of individuals in whom the linear model achieved best fit” overwhelmingly supports the log TSH-free T4 relationship. Conversely, the fit of other nonlinear curves to those with fewer observations per individual inherently indicates poorer accuracy and reliability of those nonlinear models. We fully concur with the authors' remark that “the linear model is an adequate description of the intraindividual log TSH-free T4 relationship and that nonlinear alternatives do not provide significantly better fit.”
Third and finally, we want to emphasize a critical fact that it is impossible for the TSH value of one particular individual to exert any influence on the free T4 of a totally different individual and vice versa because each person is a biologically separate entity. The relationship of free T4 and TSH on a scatter plot can thus be interpreted meaningfully only within a given person but not to be deduced from a cluster of nebulous, noisy data pooled from a huge population of unrelated individuals.
From a scientific perspective, a realistic model representation should capture the true essence of a phenomenon and ideally reflect the laws, principles, theories, or mechanisms governing a relationship. Although statistical models are used in many fields within the life sciences, they are meaningless and untenable in the context of elucidating the rules governing endocrine networks such as the TSH-free T feedback loop. Endocrine interactions can be precisely defined only by studying individuals one at a time, a robust time-honored methodology from classical physiology that still remains valid in today's postgenomics era. Such research had elegantly established decades ago that the log TSH-free T4 relationship is indeed a linear one (3–5).
Disclosure Summary: The authors are coinventors on Singapore patent PCT/SG2013/000515.
References
1. Rothacker KM , Brown SJ , Hadlow NC , Wardrop R , Walsh JP . Reconciling the log-linear and non-log-linear nature of the TSH-free T4 relationship: intra-individual analysis of a large population . J Clin Endocrinol Metab . In press .
2. Hoermann R , Eckl W , Hoermann C , Larisch R . Complex relationship between free thyroxine and TSH in the regulation of thyroid function . Eur J Endocrinol . 2010 ;162 :1123 –1129 .
3. Fish LH , Schwartz HL , Cavanaugh J , Steffes MW , Bantle JP , Oppenheimer JH . Replacement dose, metabolism, and bioavailability of levothyroxine in the treatment of hypothyroidism: role of triiodothyronine in pituitary feedback in humans . N Engl J Med . 1987 ;316 :764 –770 .
4. Spencer CA , LoPresti JS , Patel A , et al. . Applications of a new chemiluminometric thyrotropin assay to subnormal measurement . J Clin Endocriol Metab . 1990 ;70 (2 ):453 –460
5. Meier CA , Maisey MN , Lowry A , Muller J , Smith MA . Interindividual differences in the pituitary-thyroid axis influence the interpretation of thyroid function tests . Clin Endocrinol (Oxf) . 1993 ;39 (1 ):101 –107 .
