Work

Clinically Optimized Adult Height Prediction From Key Bone and Pubertal Stages: Prospective Validation to Adult Height

Year: 2025

Type: article

Abstract: Context: Accurate adult height prediction remains a challenge in pediatric endocrinology. Traditional bone age (BA) based methods are time-consuming, software-dependent, and unreliable, while ignoring the critical effect of pubertal progression on growth potential. Objective: In this work we aimed to develop a clinically optimized model for adult height prediction by replacing traditional BA with key bone grades to quantify growth potential, integrating pubertal stages to account for pubertal-stage growth variations, and establishing a direct mapping between "key bone grades + pubertal stage" and height growth potential. Methods: A cross-sectional study was conducted in Beijing (2022-2023). We performed Tanner-Whitehouse 3/radius-ulna-short bone grading and pubertal staging including prepuberty, on puberty, and completing puberty. Spearman analysis identified key bone combinations most associated with BA and height. An integrated model combining bone grades and pubertal stage was developed and validated in an independent cohort followed to adult height. Results: Key Spearman correlation revealed strong correlations of the radius, ulna and metacarpal I grading with BA (ρ = 0.94-0.96), with bone combinations (ρ = 0.98-0.99) outperforming any single bones. Three types of bone combinations (radius + ulna, radius + metacarpal I, and radius + ulna + metacarpal I) integrating with pubertal stages demonstrated approximately equivalent predictive performance for adult height prediction. Considering bone representativeness and feasibility, we prefer to propose the radius + metacarpal I combination with puberty stages as the clinically optimized model for adult height prediction. Independent validation cohort confirmed superior accuracy of the proposed model vs traditional BA-based methods: Mean prediction error was reduced from 0.71 cm to 0.02 cm, while the proportion of predictions error of 3 cm or less increased from 66.9% to 73.5%. Conclusion: The integrated bone-puberty model significantly improves prediction accuracy by incorporating skeletal maturity and pubertal dynamics. Its streamlined 2-bone protocol offers a practical tool for growth monitoring and clinical decision-making.

Source: Journal of the Endocrine Society

DOI: 10.1210/jendso/bvaf201