Prediction of response to growth hormone treatment in short children born small for gestational age: analysis of data from KIGS (Pharmacia International Growth Database).

A model was developed that allows physicians to individualize GH treatment in children born short for gestational age (SGA) who fail to show spontaneous catch-up growth. Data from children (n = 613) in a large pharmacoepidemiological survey, the KIGS (Pharmacia International Growth Database), or who had participated in clinical trials were used to develop the model. Another group of similar children (n = 68) from KIGS was used for validation. In the first year of GH treatment, the growth response correlated positively with GH dose, weight at the start of GH treatment, and midparental height SD score and negatively with age at treatment start. Using this model, 52% of the variability of the growth response could be explained, with a mean error SD of 1.3 cm. GH dose was the most important response predictor (35% of variability), followed by age at treatment start. The second year growth response was best predicted by a three-parameter model (height velocity in yr 1 of treatment, age at start of treatment, and GH dose), which accounted for 34% of the variability, with an error SD of 1.1 cm. The first year response to GH treatment was the most important predictor of the second year response, accounting for 29% of the variability. No statistically significant differences between the predicted and observed growth responses were found when the models were applied to the validation groups. In conclusion, using simple variables, we have developed a model that can be used in clinical practice to adjust the GH dose to achieve the desired growth response in patients born SGA. Furthermore, this model can be used to provide patients with a realistic expectation of treatment and may help to identify compliance problems or other underlying causes of treatment failure.