Derivation and validation of a mathematical model for predicting the response to exogenous recombinant human growth hormone (GH) in prepubertal children with idiopathic GH deficiency

Postmarkteting surveillance studies of recombinant human GH therapy, such a s the Rabi Pharmacia International Growth Study (KIGS; Pharmacia & Upjohn, Inc,, international Growth Database), have accumulated extensive data conce rning the characteristics and growth outcomes of children with various caus es of short stature. These data provide an opportunity to analyze the facto rs that determine responsiveness to GH and allow the development of disease -specific growth prediction models. We undertook a multiple regression anal ysis of height velocity (centimeter per yr) with various patient parameters of potential relevance using data from a cohort of 593 prepubertal childre n with idiopathic GH deficiency (GHD) from the KIGS database. Our aim was t o produce models that would have practical utility for predicting prepubert al growth during each of the first 4 yr of GH replacement therapy. These mo dels were validated by a prospective comparison of predicted and observed g rowth outcomes in an additional 3 cohorts of prepubertal children with idio pathic GHD: 237 additional KIGS patients, 29 patients from the Australian O ZGROW study, and 33 patients from Tubingen, Germany. The most influential v ariable for first year growth response was the natural log (ln) of the maxi mum GH response during provocation testing, which was inversely correlated with height velocity. The first year growth response was also inversely cor related with chronological age and height so score minus midparental height so score. First year growth was positively correlated with body weight SD score, weekly GH dose (ln), and birth weight SD score. Two first year model s were developed using these parameters, 1 including and 1 excluding the ma ximum GH response to provocative testing. The former model explained 61% of the response variability, with a SD of 1.46 cm; the latter model explained 45% of the variability, with a SD of 1.72 cm. The two models gave similar predictions, although the model excluding the maximum GH response to testin g tended to underpredict the growth response in patients with very low GH s ecretory capacity. For the second, third, and fourth year growth responses, 4 predictors were identified: height velocity during the previous year (po sitively correlated), body weight so score (positively correlnted) chronolo gical age (negatively correlated. and weekly GH dose tin, positively correl ated). The models far the second, third, and fourth year responses explaine d 40%, 37% and 30% of the variability, respectively, with SDS of 1.19, 1.05 , and 0.95 cm, respectively. When the models were applied prospectively to the other cohorts, there were no significant differences between observed a nd predicted responses in any of the cohorts in any year of treatment. The fourth year response model gave accurate prospective growth predictions for the fifth to the eighth prepubertal years of GH: treatment in a subset of 48 KIGS patients. Analyses of Studentized residuals provided further valida tion of the models. The parameters used in our models do not explain all of the variability in growth response, but they have a high degree of precisi on (low error sos). Moreover, the parameters used are robust and easily acc essible. These properties give the models' practical utility as growth pred iction tools. The availability of longitudinal, disease-specific models wil l be helpful in the future for enabling growth-promoting therapy to be plan ned at the outset, optimized for efficacy and economy, and individualized t o meet treatment goals based on realistic expectations.