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ObjectivesGraves' disease (GD) with onset in childhood or adolescence is a rare disease (ORPHA:525731). Current pharmacotherapeutic approaches use antithyroid drugs, such as carbimazole, as monotherapy or in combination with thyroxine hormone substitutes, such as levothyroxine, as block-and-replace therapy to normalize thyroid function and improve patients' quality of life. However, in the context of fluctuating disease activity, especially during puberty, a considerable proportion of pediatric patients with GD is suffering from thyroid hormone concentrations outside the therapeutic reference ranges. Our main goal was to develop a clinically practical pharmacometrics computer model that characterizes and predicts individual disease activity in children with various severity of GD under pharmacotherapy.MethodsRetrospectively collected clinical data from children and adolescents with GD under up to two years of treatment at four different pediatric hospitals in Switzerland were analyzed. Development of the pharmacometrics computer model is based on the non-linear mixed effects approach accounting for inter-individual variability and incorporating individual patient characteristics. Disease severity groups were defined based on free thyroxine (FT4) measurements at diagnosis.ResultsData from 44 children with GD (75% female, median age 11 years, 62% receiving monotherapy) were analyzed. FT4 measurements were collected in 13, 15, and 16 pediatric patients with mild, moderate, or severe GD, with a median FT4 at diagnosis of 59.9 pmol/l (IQR 48.4, 76.8), and a total of 494 FT4 measurements during a median follow-up of 1.89 years (IQR 1.69, 1.97). We observed no notable difference between severity groups in terms of patient characteristics, daily carbimazole starting doses, and patient years. The final pharmacometrics computer model was developed based on FT4 measurements and on carbimazole or on carbimazole and levothyroxine doses involving two clinically relevant covariate effects: age at diagnosis and disease severity.DiscussionWe present a tailored pharmacometrics computer model that is able to describe individual FT4 dynamics under both, carbimazole monotherapy and carbimazole/levothyroxine block-and-replace therapy accounting for inter-individual disease progression and treatment response in children and adolescents with GD. Such clinically practical and predictive computer model has the potential to facilitate and enhance personalized pharmacotherapy in pediatric GD, reducing over- and underdosing and avoiding negative short- and long-term consequences. Prospective randomized validation trials are warranted to further validate and fine-tune computer-supported personalized dosing in pediatric GD and other rare pediatric diseases.

BackgroundJuvenile idiopathic arthritis (JIA) is one of the most common pediatric inflammatory rheumatic diseases (PiRDs). Uncontrolled disease activity is associated with decreased quality of life and chronic morbidity. Biologic disease-modifying antirheumatic drugs (bDMARDs) and Janus kinase inhibitors (JAKi) have considerably improved clinical outcomes. For optimized patient care, understanding the efficacy-safety profile of biologics in subgroups of JIA is crucial. This systematic review based on published randomized controlled trials (RCTs) aims to assess efficacy and safety data for bDMARDs and JAKi with various JIA subgroups after 3 months of treatment.MethodsData for American College of Rheumatology (ACR) pediatric (Pedi) 30, 50, and/or 70 responses after 3 months of treatment were selected from RCTs investigating bDMARDs or JAKi in JIA according to predefined inclusion/exclusion criteria. Treatment and control arms were compared by calculating risk ratios (RRs) with 95% confidence intervals (CIs), and proportions of overall, serious adverse events (AEs) and infections were analyzed. Forest plots were generated to summarize efficacy and safety endpoints across studies, JIA subgroups, and type of biologics.ResultsTwenty-eight out of 41 PiRD RCTs investigated bDMARD or JAKi treatments in JIA. 9 parallel RCTs reported ACR Pedi 30, 50, and/or 70 responses 3 months after treatment initiation. All treatment arms showed improved ACR Pedi responses over controls. RRs ranged from 1.05 to 3.73 in ACR Pedi 30, from 1.20 to 7.90 in ACR Pedi 50, and from 1.19 to 8.73 in ACR Pedi 70. An enhanced effect for ACR Pedi 70 was observed with infliximab combined with methotrexate in PJIA vs. methotrexate monotherapy. A slightly higher risk of gastrointestinal AEs and infections was observed with treatment arms compared to placebo or methotrexate monotherapy.ConclusionInvestigated bDMARDs and JAKi showed superior treatment responses compared to controls after 3 months of treatment, which were more pronounced in ACR Pedi 50 and 70 than in ACR Pedi 30. Higher susceptibility to infections associated with bDMARDs or JAKi vs. control arms must be weighed against efficacious treatment of the underlying disease and prevention of disease-related damage. Additional RCTs are warranted to further inform development and utilization of biologics in JIA.

Additional file 1.

Additional file 1: Supplementary data S1. Search terms. Supplementary data S2. Review protocol. Supplemetary data S3. Outcome/Endpoint inclusion criteria for literature search.

L-Thyroxine (L-T4) is the treatment of choice of congenital hypothyroidism (CH). Longitudinal measurements of free T4 (FT4) serum concentrations were collected over the first two years of life with oral L-T4 treatment in infants with CH. Purpose of this study was to develop an integrated mathematical model to characterize the kinetics of exogenous L-Thyroxine (L-T4) after multiple dosing in infants with CH, and the dynamics of residual endogenous FT4 synthesis under treatment in the context of severe, moderate and mild disease. A total of 200 FT4 concentrations from 30 patients were available for analysis. At start of treatment, mean (standard deviation [SD]) postnatal age and weight of the population were 11 (8) days and 3.9 (1.3) kg. Mean (SD) pretreatment FT4 concentration was 11.3 (7.4) pmol/L. Measured FT4 concentrations were modelled as sum of residual endogenous FT4 and exogenously administered FT4 (L-T4). The integrated mathematical model consists of an absorption compartment for the exogenous FT4 administration, and a central compartment for measured FT4 with linear elimination. Hence, for residual endogenous and exogenous FT4 the same elimination rate constant was assumed. For the residual endogenous synthesis, different approaches were tested: a constant production and typical time-dependent production functions. FT4 data were analyzed using nonlinear mixed-effects modeling. The integrated mathematical model with a time-dependent non-linear Emax function describing a decreasing residual endogenous FT4 synthesis for increasing time provided the best data fit in terms of Akaike value and various goodness-of-fit plots. This is in line with the expected progressive suppression of the thyroid stimulating hormone by the exogenous FT4, and the subsequent decrease of residual FT4 endogenous synthesis. The developed mathematical model allows simulation of FT4 pharmacokinetic profiles for different disease severities and different dosing regimens.

Timing of complete data and samples, by timepoint and location. Table S2. Complete and correct data and samples when timing as a correctness factor is neglected (i.e. all data collected within one calendar day are correct). Table S3. Caregiver feasibility questionnaire. Table S4. Main difficulties experienced by caregivers during conduct of study. (PDF 205Â kb)

Proportion of complete and correct data and samples by patient and location. (PDF 8Â kb)

Proportion of complete and correct data and samples by location and day. (PDF 6Â kb)

Proportion of complete and correct data and samples by patient and location. (PDF 8Â kb)

Development of mobile application. (PDF 74Â kb)

Proportion of complete and correct data and samples by location and day. (PDF 6Â kb)

Timing of complete data and samples, by timepoint and location. Table S2. Complete and correct data and samples when timing as a correctness factor is neglected (i.e. all data collected within one calendar day are correct). Table S3. Caregiver feasibility questionnaire. Table S4. Main difficulties experienced by caregivers during conduct of study. (PDF 205Â kb)