ArticleJournal of the Endocrine Society2022
A Novel Method for Adult Height Prediction in Children With Idiopathic Short Stature Derived From a German-Dutch Cohort.
Article in Journal of the Endocrine Society, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Fermented oyster extract promotes height growth in children with mild short stature: a randomized, double-blind, placebo-controlled trial.Nutrition research and practice · 2026Article
- Near-Adult Height Outcomes in Patients Treated With rhIGF-1 for Severe Growth Failure: Real-World IGFD Registry Data.The Journal of clinical endocrinology and metabolism · 2026Observational
- Automated bone age assessment in rare pediatric growth disorders: a comparative study using Deeplasia.Frontiers in endocrinology · 2026Article
- A Growth Prediction Model from Mid-Puberty to Near Adult Height in Adolescents with Idiopathic Isolated Growth Hormone Deficiency Treated with Growth Hormone.Hormone research in paediatrics · 2025Article
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Authors and funding
8 authors.
Funding
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Abstract
Context: Prediction of adult height (AH) is important in clinical management of short children. The conventional methods of Bayley-Pinneau (BP) or Roche-Wainer-Thissen (RWT) have limitations. Objective: We aimed to develop a set of algorithms for AH prediction in patients with idiopathic short stature (ISS) which are specific for combinations of predicting variables. Methods: Demographic and auxologic data were collected in childhood (1980s) and at AH (1990s). Data were collected by Dutch and German referral centers for pediatric endocrinology. A total of 292 subjects with ISS (219 male, 73 female) were enrolled. The population was randomly split into modeling (n = 235) and validation (n = 57) cohorts. Linear multi-regression analysis was performed with predicted AH (PAH) as response variable and combinations of chronological age (CA), baseline height, parental heights, relative bone age (BA/CA), birth weight, and sex as exploratory variables. Results: Ten models including different exploratory variables were selected with adjusted Conclusion: This set of 10 multi-regression algorithms, developed specifically for children with ISS, provides a flexible tool for AH prediction with better accuracy than the conventional methods.
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