IGHD

iGRO™ supports individualised GH treatment to children with idiopathic GH deficiency (IGHD) as soon as treatment starts.
It is a web-based tool 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 idiopathic GH deficiency (IGHD) and provides evidence-based guidance and justification for GH treatment decisions6.

iGRO™ prediction algorithms can explain 30-70%1-4 of variability in growth responses to GH treatment for children with IGHD.

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 prediction for a child with idiopathic growth hormone deficiency (IGHD) also requires:
 

  • Gestational age 2
  • Maximum GH peak - optional - 1-5

 

 

1 - Ranke MB., et al. Derivation and validation of a mathematical model for predicting the response to exogenous recombinant human growth hormone (GH) in prepubertal children with idiopathic GH deficiency. The Journal of Clinical Endocrinology and Metabolism (1999):1174–83.

2 - Ranke MB., et al. The mathematical model for total pubertal growth in idiopathic growth hormone (GH) deficiency suggests a moderate role of GH dose. The Journal of Clinical Endocrinology and Metabolism (2003):38.

3 - Ranke MB and Lindberg A. Prediction models for short children born short for gestational age and idiopathic short stature: KIGS analysis and review. BMC medical informatics and decision making (2011):423–32.

4 - Ranke MB., et al. Prediction of response to growth hormone treatment in short children born small for gestational age: Analysis of data from KIGS. Journal of Clinical Endocrinology and Metabolism (2003):125–31.

5 - Ranke MB., et al. Increased response but lower responsiveness to growth hormone (GH) in very young children (aged 0-3 years) with idiopathic GH deficiency: analysis of data from KIGS. Journal of Clinical Endocrinology and Metabolism (2005):1966–71.

6 - Loftus J, Lindberg A, Aydin F, et al. Journal of Pediatric Endocrinology and Metabolism (2017);30:1019–1026.