Comparison of two prediction models in a clinical setting to predict growth in prepubertal children on recombinant growth hormone

Abstract

Objective

Prediction models that calculate the growth response in children on recombinant growth hormone (GH) have shown to be helpful tools in deciding who should start treatment, as identifying GH deficiency can be a challenge. The aim of the study is to compare two prediction models; the KIGS (Pfizer International Growth Study) prediction models which are more accessible and the Gothenburg model which has previously been clinically validated.

Design

All prepubertal patients who commenced GH treatment at Queen Silvia Children's Hospital in Gothenburg during a 13-year-period were candidates for the study. Children were excluded if suspected syndrome, malignant disease, chronic disease, or poor adherence to treatment were found. The KIGS model and the Gothenburg model were used to make predictions. Data was obtained from medical charts for the period from birth to the end of the first year of treatment. The predicted height outcome was compared against observed.

Results

The study included 123 prepubertal children (76 males). The average age at treatment start and standard deviation (SD) was 5.7 (1.8) years. Correlation analyses were performed between predicted growth by both the Gothenburg and KIGS models versus the first year observed growth response showing strong correlations of r = 0.990 and r = 0.991 respectively with studentized residuals of 0.10 (0.81) for the Gothenburg model and 0.03 (0.96) for the KIGS model.

Conclusion

We found that both the Gothenburg model and the KIGS model are equivalent when applying to our clinical cohort. Both models are very precise, hence it is encouraged to use either based on accessibility for the clinic.