Turner Syndrome

iGRO™ supports individualised GH treatment to children with Turner syndrome (TS) as soon as treatment starts.
It is a web-based medical device designed to be used in clinical practice — to predict how much a child may grow in the first and subsequent years of GH therapy.

It can be used to calculate growth predictions for children with Turner syndrome (TS) and provides evidence-based guidance and justification for GH treatment decisions.

iGRO™ prediction algorithms can explain 30–68%1 of variability in growth responses to GH treatment for girls with Turner syndrome.

iGRO™ requires standard data that is routinely collected during clinic visits:

  • Birth date
  • Gender
  • Primary diagnosis
  • Birth weight
  • Parents’ heights
  • Height
  • Weight
  • Treatment start date
  • GH dose.

Growth predictions for girls with Turner syndrome (TS) also require:

  • Oxandrolone treatment status 2
  • Number of injections per week 2

 

 

1- Ranke, Michael B., et al. "Prediction of long-term response to recombinant human growth hormone in Turner syndrome: development and validation of mathematical models." The Journal of Clinical Endocrinology & Metabolism 85.11 (2000): 4212-4218; Ranke, Michael B., Anders Lindberg, and KIGS International Board. "Observed and predicted total pubertal growth during treatment with growth hormone in adolescents with idiopathic growth hormone deficiency, Turner syndrome, short stature, born small for gestational age and idiopathic short stature: KIGS analysis and review." Hormone research in paediatrics 75.6 (2011): 423-432.

2- Ranke, Michael B., et al. "Accurate long-term prediction of height during the first four years of growth hormone treatment in prepubertal children with growth hormone deficiency or Turner Syndrome." Hormone research in pædiatrics 78.1 (2012): 8-17; Ranke, Michael B., et al. "Prediction of long-term response to recombinant human growth hormone in Turner syndrome: development and validation of mathematical models." The Journal of Clinical Endocrinology & Metabolism 85.11 (2000): 4212-4218.