Evidence map›Paper›PMID 41480193›Full record

ArticleJournal of the Endocrine Society2026

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

Huahong Wu, Yaqin Zhang, Chengdong Yu, Yang Li, Wen Shu, Tao Li, Guimin Huang, Dongqing Hou, Fangfang Chen, Junting Liu and 2 more

Abstract read
In one paragraph

Article in Journal of the Endocrine Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Huahong WuDepartment of Growth and Development, Capital Center for Children's Health, Capital Medical University, Capital Institute of Pediatrics, Beijing 100020, China.ORCID https://orcid.org/0000-0001-6979-2980
Yaqin ZhangDepartment of Growth and Development, Capital Center for Children's Health, Capital Medical University, Capital Institute of Pediatrics, Beijing 100020, China.
Chengdong YuDepartment of Growth and Development, Capital Center for Children's Health, Capital Medical University, Capital Institute of Pediatrics, Beijing 100020, China.
Yang LiDepartment of Endocrinology, Genetics and Metabolism, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100020, China.
Wen ShuDepartment of Growth and Development, Capital Center for Children's Health, Capital Medical University, Capital Institute of Pediatrics, Beijing 100020, China.
Tao LiChild Health Big Data Research Center, Capital Center for Children's Health, Capital Medical University, Capital Institute of Pediatrics, Beijing 100020, China.
Guimin HuangChild Health Big Data Research Center, Capital Center for Children's Health, Capital Medical University, Capital Institute of Pediatrics, Beijing 100020, China.
Dongqing HouChild Health Big Data Research Center, Capital Center for Children's Health, Capital Medical University, Capital Institute of Pediatrics, Beijing 100020, China.
Fangfang ChenDepartment of Epidemiology, Capital Center for Children's Health, Capital Medical University, Capital Institute of Pediatrics, Beijing 100020, China.
Junting LiuChild Health Big Data Research Center, Capital Center for Children's Health, Capital Medical University, Capital Institute of Pediatrics, Beijing 100020, China.
Shaoli LiChild Health Big Data Research Center, Capital Center for Children's Health, Capital Medical University, Capital Institute of Pediatrics, Beijing 100020, China.
Xin'nan ZongDepartment of Growth and Development, Capital Center for Children's Health, Capital Medical University, Capital Institute of Pediatrics, Beijing 100020, China.ORCID https://orcid.org/0000-0002-9465-9230

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

integrated modelkey bone gradepredict adult heightpubertal stage

Identifiers

PMID41480193
PMCPMC12754412

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.