hrp0086rfc14.5 | Growth : Mechanisms | ESPE2016

Gene Expression Profiling of Children with GH Deficiency (GHD) Prior to Treatment with Recombinant Human Growth Hormone (r-hGH) is Associated with Growth Response Over Five Years of Therapy

Stevens Adam , Murray Philip , Koledova Ekaterina , Chatelain Pierre , Clayton Peter

Background: The relationship of pre-treatment gene expression (GE) to long-term growth response in GHD is unknown. Prediction of long-term response to r-hGH therapy would allow better decision making about start and maintenance doses and hence cost:benefit.Objective and hypotheses: To assess the relationship of baseline GE to response to r-hGH over 5 years of therapy in GHD children.Method: Pre-pubertal children with GHD (n</em...

hrp0094fc9.2 | Growth Hormone and IGFs | ESPE2021

A simple model with height and age at start of treatment with recombinant human growth hormone can accurately predict future growth in children with growth disorders

van Dommelen Paula , Arnaud Lilian , Masne Quentin Le , Koledova Ekaterina ,

Background: A growth prediction model would not only allow patients with growth disorders the opportunity to see the expected effect of their recombinant human growth hormone (r hGH) treatment, but also support healthcare professionals to individualise treatment to optimise growth outcomes.Aim: To develop a growth prediction model in children with growth disorders.Patients and Methods: Height and c...

hrp0097p1-290 | GH and IGFs | ESPE2023

Optimal injection device settings to achieve high adherence to growth hormone treatment in patients with growth disorders

van Dommelen Paula , Arnaud Lilian , Zucchiatti Chantal , Koledova Ekaterina

Background: Treatment for growth disorders requires daily injections of recombinant human growth hormone (r-hGH) over multiple years, and automated devices may help in this regard. The ability to adjust injection device settings, which are pre-set as default unless changed by healthcare professionals, may improve patient comfort and needle anxiety and thereby improve adherence.Aim: To study the association between inject...

hrp0095p1-519 | Growth and Syndromes | ESPE2022

Learning outcomes of a MOOC supporting healthcare professionals in treating patients with growth disorders

Dimitri Paul , Fernandez-Luque Luis , Koledova Ekaterina , Malwade Shwetambara , Abdul Shabbir Syed

Background: There is a need to increase digital health literacy in paediatric endocrinology due to the rapid emergence of digital technologies. Massive open online courses (MOOC) provide an opportunity to rapidly increase digital health capabilities at scale, as previously demonstrated in diabetes.1 To our knowledge, there are no comparable examples in the field of growth hormone deficiency.Aim: This study evaluates the ...

hrp0095p2-149 | GH and IGFs | ESPE2022

Advancing personalised medicine for growth hormone delivery: mixed-methods participatory study of a next generation, smart auto-injector device

I Labarta José , Rivera-Romero Octavio , Fernández-Luque Luis , Keiser Matthew , Koledova Ekaterina

Background: Treatment of growth hormone deficiency (GHD) requires daily injections over multiple years. Novel technologies facilitate this by automating the injection process – thereby adding comfort and reducing anxiety. An always-connected device, enabled by mobile technologies, also facilitates the collection of injection data such that adherence information is available to healthcare professionals (HCPs) in real-time. In developing new solutions, it ...

hrp0089p1-p158 | GH &amp; IGFs P1 | ESPE2018

Patients and Caregivers Perspectives on a Mobile App that Tracks Adherence and Outcomes in Children with Growth Disorders Treated with Recombinant Human Growth Hormone (r-hGH)

McNally Mark , Long Frank , Poskitt Henry , Cancela Jorge , Koledova Ekaterina , Castro Javier Sanchez

Healthcare professionals (HCPs) receive adherence information on patient Saizen® recombinant human growth hormone (r-hGH) treatment via data wirelessly transferred from the easypodTM electromechanical delivery device to the web-based eHealth platform easypodTM connect. In order to empower patients and caregivers with this information and to provide educational tools, the growlinkTM mobile app is being ...

hrp0084p1-83 | Growth Hormone | ESPE2015

Genetic Markers Contribute to the PREDICTION of Response to GH in Severe but not Mild GH Deficiency

Stevens Adam , Murray Philip , Wojcik Jerome , Raelson John , Koledova Ekaterina , Chatelain Pierre , Clayton Peter

Background: Single nucleotide polymorphisms (SNPs) associated with the response to GH therapy have previously been identified in growth hormone deficient (GHD) children in the PREDICT long-term follow-up (LTFU) study (NCT00699855).Objective and hypotheses: To assess the effect of GHD severity on the predictive value of genetic markers of growth response.Method: We used pre-pubertal GHD children (peak GH <10 μg/l) from the ...

hrp0084p2-394 | GH &amp; IGF | ESPE2015

Gene Expression Profiles in GH Deficient Children Relate Peak GH Levels to Circadian Clock, Chromatin Remodelling, and WNT Signalling Pathways

Murray Philip , Stevens Adam , DeLeonibus Chiara , Koledova Ekaterina , Chatelain Pierre , Clayton Peter

Background: GH deficiency (GHD) is classically defined on the basis of a cut-off applied to the peak GH level during stimulation tests; a process with recognised limitations. Identifying the functional role of genes whose expression is associated with pGH may help with our understanding and classification of GHD.Objective and hypotheses: Identify patterns of gene expression (GE) related to pGH and to describe the function, and regulation of these genes.<...

hrp0084p2-418 | GH &amp; IGF | ESPE2015

Random Forest Classification Predicts Response to Recombinant GH in GH Deficient Children Using Baseline Clinical Parameters and Genetic Markers

Stevens Adam , Murray Philip , Wojcik Jerome , Raelson John , Koledova Ekaterina , Chatelain Pierre , Clayton Peter

Background: Prediction of response to recombinant GH (r-GH) is currently based on regression modelling. This approach generates a prediction equation which can be applied to data from an individual child. However this method can underestimate the effect of inter-dependent variables. Random forest classification (RFC) is an alternative prediction method based on decision trees that is not sensitive to the relationships between variables.Objective and hypo...

hrp0084p3-963 | GH &amp; IGF | ESPE2015

The Easypod™ Connect Observational Study: Comparison of Results from Interim Analyses

Davies Peter , Nicolino Marc , Norgren Svante , Stoyanov George , Koledova Ekaterina , VanderMeulen John

Background: The Easypod Connect Observational Study (ECOS) observational study follows children with GHD, SGA and Turner syndrome receiving r-hGH therapy for up to 5 years, with interim analyses each year. The easypod electromechanical auto-injector device enables accurate, real-world digital records of patients’ adherence to rhGH to be collected for evaluation.Objective and hypotheses: The primary objective of ECOS is to evaluate the level of adher...