A prediction model could foresee adequate height response in children eligible for growth hormone treatment

Area of Science:

• Pediatric Endocrinology
• Growth Hormone Therapy
• Biometric Prediction Models

Background:

• Accurate prediction of treatment response is crucial for optimizing growth hormone (GH) therapy in children.
• The Gothenburg prediction model was developed to identify individuals likely to benefit from GH treatment.

Purpose of the Study:

• To validate the clinical utility of the Gothenburg prediction model for identifying children who will benefit from growth hormone (GH) treatment.
• To assess the model's accuracy in predicting first-year height gain in prepubertal children with GH deficiency.

Main Methods:

• Retrospective analysis of 121 prepubertal children with GH deficiency treated between 2004-2016.
• Comparison of observed first-year height gain with predictions from the Gothenburg model using a GH dose of 33 μg/kg/day.
• Evaluation of the model's performance in identifying responders versus non-responders.

Main Results:

• The model correctly identified 98% (119/121) of patients achieving ≥0.5 SDS height gain.
• The model showed a tendency to underestimate low predictions and overestimate high predictions.
• Residual standard deviation was 0.31 SDS, indicating prediction accuracy.

Conclusions:

• The validated Gothenburg prediction model can be effectively used in clinical practice.
• This model aids in avoiding unnecessary growth hormone treatment for children with predicted poor outcomes.
• Clinical implementation of validated prediction models improves therapeutic decision-making in pediatric growth disorders.