Personalized approach to growth hormone treatment: clinical use of growth prediction models

J M Wit1, M B Ranke, K Albertsson-Wikland

  • 1Department of Pediatrics, Leiden University Medical Center, NL-2300 Leiden, The Netherlands. J.M.Wit@lumc.nl

Insights

Growth hormone (GH) treatment aims for optimal height in children. Prediction models improve growth response accuracy and can personalize GH dosing for better outcomes.

Area of Science:

  • Pediatrics
  • Endocrinology
  • Growth Medicine

Background:

  • Growth hormone (GH) treatment is crucial for achieving target height (TH) in short children.
  • Assessing treatment response involves evaluating first-year height velocity (HV) against established charts or prediction models.

Purpose of the Study:

  • To review prediction models for growth hormone (GH) treatment response in children.
  • To explore methods for optimizing GH dosing and improving growth outcomes.

Main Methods:

  • Analysis of existing prediction models: Kabi International, Gothenburg, and Cologne models.
  • Evaluation of individualized dosing and insulin-like growth factor-I (IGF-I) based titration.
  • Discussion on potential improvements using biochemical, genetic, or proteomic markers.

Main Results:

  • Prediction models explain 50-80% of growth response variance.
  • Individualized dosing and IGF-I titration reduce growth response variation.
  • The predictive accuracy of additional markers remains uncertain.

Conclusions:

  • Prediction models offer an evidence-based approach for determining GH dosage regimens.
  • Optimized dosing can potentially reduce GH treatment costs.
  • User-friendly software is needed to facilitate clinical application of prediction models.

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