Optimized Replacement T4 and T4+T3 Dosing in Male and Female Hypothyroid Patients With Different BMIs Using a Personalized Mechanistic Model of Thyroid Hormone Regulation Dynamics

Model-Informed Precision Dosing Using Machine Learning for Levothyroxine in General Practice: Development, Validation and Clinical Simulation Trial

Levothyroxine is one of the most prescribed drugs in the western world. Dosing is challenging due to high-interindividual differences in effective dosage and the narrow therapeutic window. Model-informed precision dosing (MIPD) using machine learning could assist general practitioners (GPs), but no such models exist for primary care. Furthermore, introduction of decision-support algorithms in healthcare is limited due to the substantial gap between developers and clinicians' perspectives. We report the development, validation, and a clinical simulation trial of the first MIPD application for primary care. Stable maintenance dosage of levothyroxine was the model target. The multiclass model generates predictions for individual patients, for different dosing classes. Random forest was trained and tested on a national primary care database (n = 19,004) with a final weighted AUC across dosing options of 0.71, even in subclinical hypothyroidism. TSH, fT4, weight, and age were most predictive. To assess the safety, feasibility, and clinical impact of MIPD for levothyroxine, we performed clinical simulation studies in GPs and compared MIPD to traditional prescription. Fifty-one GPs selected starting dosages for 20 primary hypothyroidism cases without and then with MIPD 2 weeks later. Overdosage and underdosage were defined as higher and lower than 12.5 μg relative to stable maintenance dosage. MIPD decreased overdosage in number (30.5 to 23.9%, P < 0.01) and magnitude (median 50 to 37.5 μg, P < 0.01) and increased optimal starting dosages (18.3 to 30.2%, P < 0.01). GPs considered lab results more often with MIPD and most would use the model frequently. This study demonstrates the clinical relevance, safety, and effectiveness of MIPD for levothyroxine in primary care.

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.

Restoration of euthyroidism with levothyroxine: implications of etiology of hypothyroidism and the degree of residual endogenous thyroid function

There are many thyroid-related factors that combine with non-thyroid-related factors in order to affect the patient response to treatment of hypothyroidism, in terms of their satisfaction with therapy. Some of the thyroid-derived factors include the etiology of the hypothyroidism and the amount of residual thyroid function that the patient retains. These two factors may be intertwined and affected by a third influence, the presence of thyroid peroxidase antibodies. The downstream consequences of the interactions between these three factors may influence both free thyroxine and free triiodothyronine levels, TSH concentrations, and various thyroid biomarkers. Evidence of the widespread importance of thyroid hormones can be inferred from the multiple genes that are regulated, with their regulation affecting multiple serum biomarkers. Thyroid biomarkers may extend from various well-known serum markers such as lipids and sex hormone-binding globulin to serum levels of thyroid hormone metabolites. Moreover, the interplay between thyroid hormones and biomarkers and their relative ratios may be different depending on the hypothyroidism etiology and degree of residual thyroid function. The ultimate significance of these relationships and their effect on determining patient-reported outcomes, quality of life, and patient satisfaction is, as yet, poorly understood. However, identification of better biomarkers of thyroid function would advance the field. These biomarkers could be studied and correlated with patient-reported outcomes in future prospective studies comparing the impact of various thyroid hormone therapies.