ESPE Abstracts

Background: Prediction models demonstrate potential in predicting growth in patients receiving recombinant human growth hormone (r-hGH) for growth disorders. However, considerable information from patients is needed to calculate a predicted growth curve. The curve matching technique only requires height data. This technique identifies growth curves that are similar (matched) among real-world patients within a database. The growth curves of these ‘matched...

Poor adherence to long-term growth hormone (GH) treatment can lead to suboptimal clinical outcomes. The easypod™ connect eHealth platform enables healthcare professionals to obtain an accurate picture of real-world adherence by allowing patients to transmit adherence data to a database. Our aims were to assess adherence to r-hGH (Saizen, Merck KGaA, Darmstadt, Germany) treatment with the easypod connect platform in children from treatment start to 48 months and to investi...

The easypod™ electromechanical injection in combination with the easypod Connect platform electronically records and transmits, in real time, accurate, objective records of the date, time and dose injected for patients receiving Growth Hormone (GH) for growth disorders, limiting the risk of misreporting and allowing physicians to accurately monitor patient behavior.The aim was to study individual patterns of adherence from start treatment up to 24 m...

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...

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...

Background: For early identification of patients requiring adherence support, objective, real-time adherence data are needed. The easypod™ electromechanical injection device, in combination with the easypod™ connect ecosystem, electronically records and transmits, in real time, accurate records of the date, time and dose injected for patients receiving recombinant human growth hormone (r-hGH) to treat growth disorders. Healthcare professionals can us...

Background: Monitoring adherence to growth hormone (GH) treatment is important, because poor adherence can lead to suboptimal clinical outcomes. The easypod™ electromechanical injection device in combination with the web-based easypod™ connect platform electronically records and transmits accurate, objective records of the date, time and dose injected of patients receiving GH with growth disorders, allowing physicians to accurately monitor patients&#...

Background: Digital health solutions, such as the Growzen™ buddy smartphone application (app), can facilitate adherence to recombinant human growth hormone (r-hGH) treatment for patients with growth disorders. The app alerts patients when it’s time for an injection and allows patients and their caregivers to self-monitor growth, to build a routine and improve adherence. The app also contains educational resources to empower patients to be active in...

Background: Numerous studies have highlighted the importance of measuring and achieving optimal adherence to growth hormone treatment in patients with growth disorders. However, there is still a paucity of research on how treatment adherence can be improved in patients with suboptimal adherence.Aim: To classify the causes of suboptimal adherence and collaborate with patients and caregivers to improve adherence.<p cla...

Background: Several criteria for growth response to growth hormone (GH) therapy have been developed. These include height velocity (HV), height standard deviation score (HSDS), ΔHV, and ΔHSDS. Other parameters considered as predictors of growth response include age at start, weight SDS, GH dose, and target height SDS. Among these, the two most important parameters to predict future height before treatment start are HSDS and age.<p class="abstex...