Growth Prediction Model for Prepubertal Children With Idiopathic Growth Hormone Deficiency: An Analysis of LG Growth Study Data.

Background: Growth hormone (GH) treatment is effective in restoring normal growth in children with GH deficiency (GHD). However, individual responses to GH treatment vary, necessitating predictive models to estimate growth outcomes. This study aimed to develop and validate a predictive model for GH treatment response during the first 2 years in patients with idiopathic GHD using the LG growth study (LGS) database.

Methods: This observational study included 669 prepubertal patients with idiopathic GHD from the LGS registry who received GH treatment for at least 2 years. Clinical and laboratory data were collected at baseline and every 6 months thereafter. Stepwise multivariate regression analysis was performed to develop prediction models for the treatment period.

Results: The mean age of patients with GDH was 6.0 ± 1.8 years. Height standard deviation score (SDS) significantly increased from -2.50 ± 0.71 to -1.66 ± 0.71 in the first year and -1.35 ± 0.71 in the second year. The first-year growth velocity was 9.06 ± 1.51 cm, decreasing to 7.42 ± 1.37 cm in the second year. The prediction models incorporated variables such as age, birth weight, bone age, initial height SDS, body mass index SDS, mid-parental height, GH dose and first year of height after GH treatment, explaining 76.9% and 84.1% of the variability in height SDS changes in the first and second years, respectively.

Conclusions: GH treatment significantly improves height outcomes in prepubertal children with GHD. The developed predictive models demonstrated accuracy, facilitating personalized GH therapy. Future research should focus on refining these models and exploring the long-term effects of GH treatment in pubertal patients.

Trial Registration: ClinicalTrials.gov identifier: NCT01604395.