Background: Recombinant human insulin-like growth factor 1 (rhIGF-I) has been approved as an orphan drug for the treatment of growth failure in children and adolescents with severe primary IGF-I deficiency (SPIGFD) with little pharmacokinetic data available. Therefore, sequential measurements of serum IGF-I, glucose, potassium, insulin and cortisol were performed in patients treated with rhIGF-I to evaluate their significance in safety and efficacy. Methods: Repetitive blood samples were taken after meals before and 30, 60, 120, 180 and 360 min after rhIGF-I injections in two male patients with Laron syndrome at times of dose adjustments. Results: Maximal IGF-I concentrations were observed 2 h after injections (495 ng/mL) and concentrations were still higher 6 h after injections than at baseline (303 ng/mL vs. 137 ng/mL). Thirteen percent of all and 33% of maximum IGF-I concentrations were greater than +2 standard deviation score (SDS) calculated for bone age (BA) (IGF-I SDS BA) rather than chronological age (CA) as BA was significantly delayed to CA by 3.2 years (p=0.0007). Height velocities correlated with individual maximum IGF-I SDS BA (=0.735; p<0.0001). Serum insulin, cortisol and glucose did not correlate with IGF-I concentrations, but serum potassium showed a negative correlation (=0.364; p<0.0001) with IGF-I concentrations. Conclusions: Sequential measurements of serum IGF-I, glucose and potassium in patients with Laron syndrome may aid in optimizing and individualizing rhIGF-I treatment. IGF-I concentrations should be referenced according to BA which better reflects the biological age. The inverse correlation of IGF-I and serum potassium concentrations after injections of rhIGF-I has not been reported before and warrants further consideration.
The journal of pediatric endocrinology and metabolism Berlin [u.a.] : de Gruyter, 1985 31(2018), 8, Seite 895-902 Online-Ressource
von David Capper ; David T. W. Jones ; Daniel Schrimpf ; Dominik Sturm ; Christian Kölsche ; Felix Sahm ; David Reuss ; Annekathrin Kratz ; Annika K. Wefers ; Kristin Huang ; Kristian Wilfried Pajtler ; Leonille Schweizer ; Damian Stichel ; Florian Selt ; Hendrik Witt ; Till Milde ; Olaf Witt ; Wolfram Scheurlen ; Christoph Geisenberger ; Stefanie Brehmer ; Marcel Seiz-Rosenhagen ; Daniel Hänggi ; Andreas Kulozik ; Axel Benner ; Martin Bendszus ; Jürgen Debus ; Michael Platten ; Andreas Unterberg ; Wolfgang Wick ; Marcel Kool ; Christel Herold-Mende ; Andreas von Deimling ; Stefan Pfister ; Hermann L. Müller
Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging—with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology.
Nature <London> London [u.a.] : Nature Publ. Group, 1869 555(2018), 7697, Seite 469-474 Online-Ressource
Basic research and clinical aspects of adamantinomatous craniopharyngioma Cham : Springer, 2017 (2017), Seite 179-214 1 Online-Ressource (XII, 220 Seiten)