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Updated: May 10, 2026

Comparative Analysis of Human Growth Hormone in Serum Using SPRi, Nano-SPRi and ELISA Assays
Published on: January 7, 2016
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.
Abstract:
The goal of growth hormone (GH) treatment in a short child is to attain a fast catch-up growth toward the target height (TH) standard deviation score (SDS), followed by a maintenance phase, a proper pubertal height gain, and an adult height close to TH. The short-term response variable of GH treatment, first-year height velocity (HV) (cm/year or change in height SDS), can either be compared with GH response charts for diagnosis, age and gender, or with predicted HV based on prediction models. Three types of prediction models have been described: the Kabi International Growth Hormone Study models, the Gothenburg models and the Cologne model. With these models, 50-80% of the variance could be explained. When used prospectively, individualized dosing reduces the variation in growth response in comparison with a fixed dose per body weight. Insulin-like growth factor-I-based dose titration also led to a decrease in the variation. It is uncertain whether adding biochemical, genetic or proteomic markers may improve the accuracy of the prediction. Prediction models may lead to a more evidence-based approach to determine the GH dose regimen and may reduce the drug costs for GH treatment. There is a need for user-friendly software programs to make prediction models easily available in the clinic.
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