DOI: 10.1097/brs.0000000000005780 ISSN: 0362-2436

Estimated Three-Dimensional Thoracic Kyphosis Supplements Radiographic Bone Age in Predicting Adolescent Idiopathic Scoliosis Curve Progression

Lane McCoy, Neset Tang, Brian A. Kelly, Kirsten Brouillet, Scott J. Luhmann
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Study Design.

Retrospective cohort study.

Objective.

To evaluate whether estimated 3-dimensional thoracic kyphosis (e3DTK) adds predictive value to radiographic bone age in identifying adolescent idiopathic scoliosis (AIS) patients at risk for curve progression.

Summary of Background Data.

Accurate prediction of curve progression in AIS remains challenging. Radiographic bone age is commonly used for risk stratification; however, three-dimensional spinal morphology may better reflect biomechanical factors influencing progression.

Methods.

AIS patients were retrospectively identified at a single tertiary pediatric center. Progression was defined as a ≥6° increase in Cobb angle or progression to ≥50°. e3DTK was estimated from standard radiographs using a validated equation. Predictive performance was assessed using ROC analysis, DeLong testing, and likelihood ratio comparisons. Patients were additionally stratified by Sanders score and e3DTK risk category to evaluate subgroup progression rates.

Results.

A total of 126 patients were included (79.4% female; 109 braced). e3DTK (r=0.25, P =0.005) and Sanders score (r=−0.33, P <0.001) were both correlated with curve magnitude change. Sanders score demonstrated strong predictive performance (AUC=0.80). Adding e3DTK to Sanders did not improve model performance (AUC=0.69; P =0.15). e3DTK alone showed good discrimination for progression (AUC=0.89) with an optimal threshold of 22.7°. However, this did not outperform Sanders-based prediction or improve combined models. Stratified analyses showed higher progression rates in high-risk e3DTK groups across Sanders stages ( P =0.022), suggesting within-stratum risk differentiation.

Conclusion.

e3DTK is associated with AIS curve progression and demonstrates discriminatory ability in univariate analysis; however, it does not improve predictive performance beyond Sanders skeletal maturity staging. While it may help characterize risk heterogeneity within maturity strata, its role appears complementary rather than independently additive in AIS progression prediction.

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