A new predictive tool called GrowCast helps clinicians forecast growth hormone therapy responses in children with idiopathic short stature. Developed by researchers at Chungnam National University and published in Value in Health, the retrospective study analyzed 91 prepubertal Korean children to transition treatment toward personalized medicine.
Decoding Growth Hormone Trajectories in Idiopathic Short Stature
Idiopathic short stature (ISS) describes children whose height sits substantially below the expected range for their age and sex without any identifiable medical cause. Recombinant growth hormone (GH) therapy, specifically utilizing somatropin administered subcutaneously six to seven times per week, is frequently prescribed to support growth. However, patient responses vary widely across pediatric populations. While some children experience meaningful catch-up growth, others show more limited improvement, leaving clinicians and families struggling to anticipate treatment benefits and set realistic expectations.
To overcome this clinical hurdle, researchers led by Professor Jung-woo Chae evaluated changes in height percentile over time rather than relying on height gain in centimeters alone. This methodology captures height changes relative to peers of the same age and sex, offering a clinically intuitive measure of catch-up growth. The single-center study reviewed medical records of 41 boys and 50 girls who received recombinant human GH between July 2020 and December 2023, tracking cumulative exposure alongside baseline demographics and laboratory markers.
Clinical Insights from the Gompertz Nonlinear Mixed-Effects Model
Investigators incorporated cumulative GH exposure into a Gompertz nonlinear mixed-effects model to characterize individual growth trajectories. Over a mean treatment period of 619 days, the mean height percentile increased from a baseline of 1.26 to 9.16 at follow-up. The statistical model estimated a total growth-response parameter of approximately 17.2 percentile points, though individual patient responses varied considerably. Professor Chae highlighted that greater predicted responses were linked to three baseline factors: a higher body mass index (BMI), lower levels of insulin-like growth factor-binding protein 3 (IGFBP-3), and a shorter paternal height, with BMI showing the most powerful correlation.
Two-year simulations further illustrated how predicted outcomes diverge according to patient profile and GH-exposure regimen. The predicted median height percentiles varied from 4.0% for lower-response profiles to 31.0% for higher-response profiles. These findings emphasize the clinical value of assessing individual biological characteristics before initiating long-term hormone therapies.
Translating Predictive Analytics into Clinical Discussions
Building upon the longitudinal model, the research team created GrowCast, a web-based platform that generates individualized predicted height and percentile trajectories. The application utilizes patient age, sex, height, weight, paternal height, IGFBP-3 level, and GH dose to model potential outcomes. According to Professor Chae, the platform enables clinicians to compare modeled treatment scenarios and communicate potential growth trajectories effectively with patients and their families. Nevertheless, the study authors emphasize that GrowCast is currently designed to support clinical discussions and treatment planning rather than serve as a validated dosing-prescription tool. Larger prospective, multicenter studies remain essential before the platform sees routine clinical implementation.
References
- Cho, H., et al. (2026). Longitudinal Modeling and Simulation of Growth Hormone Efficacy in Children With Idiopathic Short Stature. Value in Health. DOI: 10.1016/j.jval.2026.05.006
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