Implications of a data-driven approach to treatment with growth hormone in children with growth hormone deficiency and Turner syndrome

Abstract

Background: Response to growth hormone (GH) therapy may vary between individual patients. Therefore the use of GH in children should be closely monitored to avoid over, under, or ineffective treatment regimens. The treatment response can be evaluated using growth prediction models. In an effort to improve the accuracy of these prediction models, Ranke et al. (J Clin Endocrinol Metab 95(3):1229-37) proposed a novel 'data-driven' approach based on a quantitative analysis of a large cohort of patients from the Pfizer International Growth Database (KIGS) treated with Genotropin (human growth hormone). This model allows physicians to predict and evaluate the level of growth response and responsiveness for their patients so they can adapt treatment accordingly. By comparing the actually observed and the predicted growth response the ability of an individual to respond to GH (responsiveness) can be estimated and further treatment can be adapted accordingly

Objective: To determine the potential population level reduction in the amount of GH used and impact on height outcome of using this data-driven approach to guide treatment decisions, compared to conventional, 'experience-based' GH treatment in prepubertal patients with growth hormone deficiency (GHD) or Turner syndrome (TS).

Methods: A model was developed to study the height outcome and the total amount of GH used in the presence or absence of data-driven treatment decisions. The proportion of patients for whom height outcome could be improved or GH use could be reduced (i.e. for low compliance, high or low responder) was estimated using the KIGS cohort. The analysis assumed that this segmentation allows physicians to tailor dosage to the individual patient's needs or even to discontinue therapy when it is not effective. The analysis used a 4-year time horizon, with Germany as an example country, but results are extendable to other countries. Only the total amount of GH used was included, and effects were defined as the height outcome after 4 years.

Results: The analysis estimated that an evidence-driven approach may reduce the total amount of GH utilized by 7.0 % over 4 years for the treatment of short stature in prepubertal patients with GHD and TS in Germany. Despite the reduction in drug use the average growth outcomes remained unaffected with the new treatment approach. Univariate and probabilistic sensitivity analyses showed that the results are robust.

Conclusions: Our analysis showed that using a data-driven approach to guide treatment decisions for children with GHD or TS is estimated to result in efficiencies in the amount of GH used, without reducing the average growth in the population.

Fig. 1

Patient segmentation based on response and index of responsiveness

Fig. 2

First-year outcomes for each patient segment in the KIGS database. High high response, Avg average response, NC suspected non-compliance, LR low response, HV height velocity in the first year of treatment

Fig. 3

Probabilistic sensitivity analysis: scatterplot of difference in GH use and height outcome after 4 years of treatment with a data-driven approach

Fig. 4

Tornado diagram of eight most influential parameters on incremental GH use and effects