A new and accurate prediction model for growth response to growth hormone treatment in children with growth hormone deficiency
Male
Bone Development
Time Factors
Adolescent
Human Growth Hormone
Infant
Growth
Models, Biological
Body Height
03 medical and health sciences
Insulin-Like Growth Factor Binding Protein 3
0302 clinical medicine
Child, Preschool
Humans
Regression Analysis
Female
Longitudinal Studies
Prospective Studies
Amino Acids
Bone Resorption
Insulin-Like Growth Factor I
Child
DOI:
10.1530/eje.0.1440013
Publication Date:
2005-01-24T21:34:41Z
AUTHORS (8)
ABSTRACT
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.
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