Fast Track Treatment of Hypothyroidism with Levothyroxine: Reaching Homeostasis within Four Weeks.

With the current clinical method for the treatment of hypothyroidism the target for the optimum individual values for free thyroxine concentrations [FT4] and thyrotropine concentrations [TSH] of the specific patient are unknown. This situation leads to unnecessary long experimental medication administration that can take a period of sometimes one year. In this article a method will be described where hypothyroid patients are characterized with weekly measured FT4 and TSH concentrations during the first three weeks of synthetic thyroxine or levothyroxine (L-T4) treatment to predict their optimum [FT4] and belonging [TSH] endpoint for a euthyroid homeostatic state. The treatment with levothyroxine will start for all patients with a reference dose of 100 µg, which can be adjusted by the treating physician to a more safe and appropriate dose for the individual which is monitored with weekly thyroid function tests to observe the progress. After three weeks all characteristics of the patient can be inferred from the measured data. The final titration target together with the individual thyroxine half life can be calculated. With the known characteristics and the L-T4 titration target the clinician or treating physician has an instrument to reduce the experimental treatment burden for the patient from one year to a maximum of four weeks.

Personalized glucose-insulin model based on signal analysis.

Glucose plasma measurements for diabetes patients are generally presented as a glucose concentration-time profile with 15-60min time scale intervals. This limited resolution obscures detailed dynamic events of glucose appearance and metabolism. Measurement intervals of 15min or more could contribute to imperfections in present diabetes treatment. High resolution data from mixed meal tolerance tests (MMTT) for 24 type 1 and type 2 diabetes patients were used in our present modeling. We introduce a model based on the physiological properties of transport, storage and utilization. This logistic approach follows the principles of electrical network analysis and signal processing theory. The method mimics the physiological equivalent of the glucose homeostasis comprising the meal ingestion, absorption via the gastrointestinal tract (GIT) to the endocrine nexus between the liver, pancreatic alpha and beta cells. This model demystifies the metabolic 'black box' by enabling in silico simulations and fitting of individual responses to clinical data. Five-minute intervals MMTT data measured from diabetic subjects result in two independent model parameters that characterize the complete glucose system response at a personalized level. From the individual data measurements, we obtain a model which can be analyzed with a standard electrical network simulator for diagnostics and treatment optimization. The insulin dosing time scale can be accurately adjusted to match the individual requirements of characterized diabetic patients without the physical burden of treatment.

High Resolution Free Triiodothyronine-Thyrotropin (FT3-TSH) Responses to a Single Oral Dose of Liothyronine in Humans: Evidence of Distinct Inter-Individual Differences Unraveled Using an Electrical Network Model.

The effects of a single oral dose of liothyronine (L-T3) on thyroid stimulating hormone (TSH) and other related thyroid system parameters are partly understood despite therapeutic use of this hormone over many decades. We characterize individualized responses of the hypothalamus-pituitary-thyroid (HPT) axis and its related temporal hormonal profile using an electrical network model. Based on thyroid hormone responses from blood samples using a single 50 µg oral dose of liothyronine in healthy persons with a normal operating euthyroid feedback HPT system, we derived an equivalent electrical circuit model for the system's responses. The mathematical model was tested with a circuit simulator and validated with individualized clinical data. This signal processing technique makes the evaluation of bioequivalence and bioavailability of various preparations of liothyronine at an individualized level a feasible endeavor for clinical application.

Cost-Savings to Medicare From Pre-Medicare Colorectal Cancer Screening.

BACKGROUND: Many individuals have not received recommended colorectal cancer (CRC) screening before they become Medicare eligible at the age of 65. We aimed to estimate the long-term implications of increased CRC screening in the pre-Medicare population (50-64 y) on costs in the pre-Medicare and Medicare populations (65+ y). METHODS: We used 2 independently developed microsimulation models [Microsimulation Screening Analysis Colon (MISCAN) and Simulation Model of CRC (SimCRC)] to project CRC screening and treatment costs under 2 scenarios, starting in 2010: "current trends" (60% of the population up-to-date with screening recommendations) and "enhanced participation" (70% up-to-date). The population was scaled to the projected US population for each year between 2010 and 2060. Costs per year were derived by age group (50-64 and 65+ y). RESULTS: By 2060, the discounted cumulative total costs in the pre-Medicare population were $35.7 and $28.1 billion higher with enhanced screening participation, than in the current trends scenario ($252.1 billion with MISCAN and $239.5 billion with SimCRC, respectively). Because of CRC treatment savings with enhanced participation, cumulative costs in the Medicare population were $18.3 and $32.7 billion lower (current trends: $423.5 billion with MISCAN and $372.8 billion with SimCRC). Over the 50-year time horizon an estimated 60% (MISCAN) and 89% (SimCRC) of the increased screening costs could be offset by savings in Medicare CRC treatment costs. CONCLUSION: Increased CRC screening participation in the pre-Medicare population could reduce CRC incidence and mortality, whereas the additional screening costs can be largely offset by long-term Medicare treatment savings.

The homeostatic set point of the hypothalamus-pituitary-thyroid axis--maximum curvature theory for personalized euthyroid targets.

BACKGROUND: Despite rendering serum free thyroxine (FT4) and thyrotropin (TSH) within the normal population ranges broadly defined as euthyroidism, many patients being treated for hyperthyroidism and hypothyroidism persistently experience subnormal well-being discordant from their pre-disease healthy euthyroid state. This suggests that intra-individual physiological optimal ranges are narrower than laboratory-quoted normal ranges and implies the existence of a homeostatic set point encoded in the hypothalamic-pituitary-thyroid (HPT) axis that is unique to every individual. METHODS: We have previously shown that the dose-response characteristic of the hypothalamic-pituitary (HP) unit to circulating thyroid hormone levels follows a negative exponential curve. This led to the discovery that the normal reference intervals of TSH and FT4 fall within the 'knee' region of this curve where the maximum curvature of the exponential HP characteristic occurs. Based on this observation, we develop the theoretical framework localizing the position of euthyroid homeostasis over the point of maximum curvature of the HP characteristic. RESULTS: The euthyroid set points of patients with primary hypothyroidism and hyperthyroidism can be readily derived from their calculated HP curve parameters using the parsimonious mathematical model above. It can be shown that every individual has a euthyroid set point that is unique and often different from other individuals. CONCLUSIONS: In this treatise, we provide evidence supporting a set point-based approach in tailoring euthyroid targets. Rendering FT4 and TSH within the laboratory normal ranges can be clinically suboptimal if these hormone levels are distant from the individualized euthyroid homeostatic set point. This mathematical technique permits the euthyroid set point to be realistically computed using an algorithm readily implementable for computer-aided calculations to facilitate precise targeted dosing of patients in this modern era of personalized medicine.

Hypothalamus-pituitary-thyroid feedback control: implications of mathematical modeling and consequences for thyrotropin (TSH) and free thyroxine (FT4) reference ranges.

The components of thyrotropic feedback control are well established in mainstream physiology and endocrinology, but their relation to the whole system's integrated behavior remains only partly understood. Most modeling research seeks to derive a generalized model for universal application across all individuals. We show how parameterizable models, based on the principles of control theory, tailored to the individual, can fill these gaps. We develop a system network describing the closed-loop behavior of the hypothalamus-pituitary (HP)-thyroid interaction and the set point targeted by the control system at equilibrium. The stability of this system is defined by using loop gain conditions. Defined points of homeostasis of the hypothalamus-pituitary-thyroid (HPT) feedback loop found at the intersections of the HP and thyroid transfer functions at the boundaries of normal reference ranges were evaluated by loop gain calculations. At equilibrium, the feedback control approaches a point defined in both dimensions by a [TSH]-[FT4] coordinate for which the loop gain is greater than unity. This model describes the emergence of homeostasis of the HPT axis from characteristic curves of HP and thyroid, thus supporting the validity of the translation between physiological knowledge and clinical reference ranges.

A novel minimal mathematical model of the hypothalamus-pituitary-thyroid axis validated for individualized clinical applications.

The hypothalamus-pituitary-thyroid (HPT) axis represents a complex, non-linear thyroid hormone system in vertebrates governed by numerous variables. The common modeling approach until now aims at a comprehensive inclusion of all known physiological influences. In contrast, we develop a parsimonious mathematical model that integrates the hypothalamus-pituitary (HP) complex as an endocrinologic unit based on a parameterized negative exponential function between free thyroxine (FT4) as stimulus and thyrotropin (thyroid stimulating hormone, TSH) as response. Model validation with clinical data obtained from geographically different hospitals revealed a goodness-of-fit largely ranging between 90% < R² < 99%, each HP characteristic curve being uniquely defined for each individual akin to a fingerprint. Specifically, the HP model represents the afferent feedback limb of the HPT axis while the efferent limb is mathematically depicted by TSH input to the thyroid gland which responds by secreting T4 as its chief output. The complete HPT axis thus forms a closed loop system with negative feedback resulting in an equilibrium state or homeostasis under defined conditions illustrated by the intersection of the HP and thyroid response characteristics. In this treatise, we demonstrate how this mathematical approach facilitates homeostatic set points computation for personalized dosing of thyroid medications of patients to individualized euthyroid states.

General error analysis in the relationship between free thyroxine and thyrotropin and its clinical relevance.

BACKGROUND: This treatise investigates error sources in measurements applicable to the hypothalamus-pituitary-thyroid (HPT) system of analysis for homeostatic set point computation. The hypothalamus-pituitary transfer characteristic (HP curve) describes the relationship between plasma free thyroxine [FT4] and thyrotropin [TSH]. OBJECTIVE: We define the origin, types, causes, and effects of errors that are commonly encountered in TFT measurements and examine how we can interpret these to construct a reliable HP function for set point establishment. DESIGN AND METHODS: The error sources in the clinical measurement procedures are identified and analyzed in relation to the constructed HP model. RESULTS: The main sources of measurement and interpretation uncertainties are (1) diurnal variations in [TSH], (2) TFT measurement variations influenced by timing of thyroid medications, (3) error sensitivity in ranges of [TSH] and [FT4] (laboratory assay dependent), (4) rounding/truncation of decimals in [FT4] which in turn amplify curve fitting errors in the [TSH] domain in the lower [FT4] range, (5) memory effects (rate-independent hysteresis effect). CONCLUSIONS: When the main uncertainties in thyroid function tests (TFT) are identified and analyzed, we can find the most acceptable model space with which we can construct the best HP function and the related set point area.