A New and Accurate Prediction Model for Growth Response to Growth Hormone Treatment in Children with Growth Hormone Deficiency

Objective: To identify parameters which predict individual growth response to recombinant human GH (rhGH) therapy and to combine these parameters in a prediction model.

Design: Fifty-eight prepubertal patients with GH deficiency (17 females) participated in this prospective multicenter trial with 1 year of follow-up.

Methods: Auxological measurements, parameters of GH status and markers of bone metabolism were measured at baseline and at 1, 3 and 6 months after the start of rhGH treatment. Correlations with height velocity during the first 12 months of treatment (HV+12) were calculated. Prediction models were derived by multiple regression analysis.

Results: The model which best predicted HV+12 combined the following parameters: pretreatment bone age retardation as a fraction of chronological age, pretreatment serum levels of IGF-I, urinary levels of deoxypyridinoline (a marker of bone resorption) after 1 month of treatment and height velocity after 3 months of treatment. This model explained 89% of the variation in HV+12 with a standard deviation of the residuals of 0.93 cm/year. Defining successful rhGH therapy as a doubling of pretreatment height velocity, the model had a specificity of 90% and a sensitivity of 100% in predicting therapeutic success.

Conclusions: This model is an accurate and practicable tool to predict growth response in GH-deficient children. It may help to optimize rhGH therapy by individual dose adjustment and contribute to improved overall outcomes.