Patient-Tailored Levothyroxine Dosage with Pharmacokinetic/Pharmacodynamic Modeling: A Novel Approach After Total Thyroidectomy

Abstract

Background: After seven decades of levothyroxine (LT4) replacement therapy, dosage adjustment still takes several months. We have developed a decision aid tool (DAT) that models LT4 pharmacometrics and enables patient-tailored dosage. The aim of this was to speed up dosage adjustments for patients after total thyroidectomy. Methods: The DAT computer program was developed with a group of 46 patients post-thyroidectomy, and it was then applied in a prospective randomized multicenter validation trial in 145 unselected patients admitted for total thyroidectomy for goiter, differentiated thyroid cancer, or thyrotoxicosis. The LT4 dosage was adjusted after only two weeks, with or without application of the DAT, which calculated individual free thyroxine (fT4) targets based on four repeated measurements of fT4 and thyrotropin (TSH) levels. The individual TSH target was either <0.1, 0.1–0.5, or 0.5–2.0 mIU/L, depending on the diagnosis. Initial postoperative LT4 dosage was determined according to clinical routine without using algorithms. A simplified DAT with a population-based fT4 target was used for thyrotoxic patients who often went into surgery after prolonged TSH suppression. Subsequent LT4 adjustments were carried out every six weeks until target TSH was achieved. Results: When clinicians were guided by the DAT, 40% of patients with goiter and 59% of patients with cancer satisfied the narrow TSH targets eight weeks after surgery, as compared with only 0% and 19% of the controls, respectively. The TSH was within the normal range in 80% of DAT/goiter patients eight weeks after surgery as compared with 19% of controls. The DAT shortened the average dosage adjustment period by 58 days in the goiter group and 40 days in the cancer group. For thyrotoxic patients, application of the simplified DAT did not improve the dosage adjustment. Conclusions: Application of the DAT in combination with early postoperative TSH and fT4 monitoring offers a fast approach to LT4 dosage after total thyroidectomy for patients with goiter or differentiated thyroid cancer. Estimation of individual TSH-fT4 dynamics was crucial for the model to work, as removal of this feature in the applied model for thyrotoxic patients also removed the benefit of the DAT.

Redefinition of Successful Treatment of Patients With Hypothyroidism. Is TSH the Best Biomarker of Euthyroidism?

“…Despite the publication of the data indicating the superiority of thyroid hormone levels over TSH levels there have been ongoing publications relying on TSH levels and the concept of subclinical hypothyroidism ( 84 , 85 ). Some of these projects may well have commenced prior to the availability of this new data and thus relied on the dominant teachings of the time.…”

Optimal Hormone Replacement Therapy in Hypothyroidism - A Model Predictive Control Approach

“…For a generic hypothyroid patient, the daily dosages can directly be adopted from the simulation results of the MPC. In contrast to (18), the MPC does not only compute an optimal steady-state dosage but also optimal dosages regarding the transient phase of the therapy.…”

“…In Figures 2, 3, one can see that the steady-state hormone concentrations are reached within the first week of the start of the therapy. Therefore, if the resulting thyroid hormone replacement strategy does not yield to the desired outcome, one can adapt the dosage(s) already after one or two weeks, as it is also suggested in (18). It is not necessary that the adaptation is made after 4-6 weeks, as it is currently recommended (1).…”

“…Recently, a clinical trial evaluated the treatment outcome of thyroidectomized patients when the responsible physician is supported by a decision aid tool (18). This tool is based on an individualized TSH-T 4 relationship and a simple dynamic model for the course of free T 4 (FT 4 ).…”

Sample-based observability of linear discrete-time systems

“…Consider, for example, the case of biomedical applications, where taking blood samples from a patient for testing cannot be performed too often. This is, e.g., an issue when determining certain hormone concentrations from blood samples in order to detect disorders of the hypothalamic-pituitary-thyroid axis [1] and to devise suitable medication dosages, compare, e.g., [2]. To apply state-feedback control techniques for such systems, suitable state estimators need to recover the internal state by using only this limited output information.…”