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Discrepancy Rates Between Skeletal Maturity Assessment Systems in Adolescent Idiopathic Scoliosis: A Systematic
Bo Xiang Bryan Neo1, Jeremie Shun Hong Choo1, Hee-Kit Wong2
1Yong Loo Lin School of Medicine, National University of Singapore.
Background:
Accurate assessment of skeletal maturity is critical in the management of adolescent idiopathic scoliosis (AIS), as growth potential strongly predicts curve progression risk and guides intervention timing. However, discordance between commonly used skeletal maturity classification systems may lead to suboptimal decision-making.
Methods:
A systematic review and meta-analysis were performed in accordance with PRISMA guidelines. PubMed, Scopus, Embase, Cochrane Library, and Web of Science were searched from inception to August 31, 2025. Studies comparing 2 or more skeletal maturity classification systems in AIS were included. Discrepancy was defined as a disagreement in maturity classification (mature vs. immature) at the same clinical time point. Random-effects meta-analyses of proportions were performed to estimate pooled discrepancy rates.
Results:
Thirteen studies met the inclusion criteria, with 9 included in meta-analyses. For the Risser versus Sanders maturity scale (SMS), discrepancies occurred in 2 patterns: Risser-immature/SMS-mature (4.0%, 95% CI: 2.0%-5.9%) and Risser-mature/SMS-immature (12.5%, 95% CI: 7.4%-17.6%), yielding an overall discrepancy rate of 16.1% (95% CI: 11.6%-21.1%). For Risser versus cervical vertebral maturation (CVM), overall discrepancy was 25.0% (95% CI: 20.4%-29.7%), predominantly driven by Risser-mature/CVM-immature classifications (24.3%, 95% CI: 19.7%-28.9%). Single-study comparisons involving alternative systems demonstrated substantial variability in discrepancy rates.
Conclusions:
Substantial discordance exists among skeletal maturity assessment systems in AIS, with Risser staging frequently overestimating skeletal maturity. Limited evidence suggests that SMS and CVM show closer alignment with clinical growth parameters and may more closely approximate remaining growth potential. A multimodal approach incorporating more granular maturity indices may improve treatment timing and clinical outcomes.
Level Of Evidence:
Level III.
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