Height Prediction in Idiopathic Short Stature

Werner F Blum, Michael B Ranke, Eberhard Keller, Alexandra Keller, Sandra Barth, Christiaan de Bruin, Stefan A Wudy, Jan M Wit
Journal of the Endocrine Society, Volume 6, Issue 7, July 2022, bvac074
https://doi.org/10.1210/jendso/bvac074

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 R² ranging from 0.84 to 0.78 and prediction errors from 3.16 to 3.68 cm. Applied to the validation cohort, mean residuals (PAH minus observed AH) ranged from −0.29 to −0.82 cm, while the conventional methods showed some overprediction (BP: +0.53 cm; RWT: +1.33 cm; projected AH: +3.81 cm). There was no significant trend of residuals with PAH or any exploratory variables, in contrast to BP and projected AH.

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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