Dolan LA, Weinstein SL, Dobbs MB, Flynn JMJ, Green DW, Halsey MF, Hresko MT, Krengel WF, Mehlman CT, Milbrandt TA, Newton PO, Price N, Sanders JO, Schmitz ML, Schwend RM, Shah SA, Song K, Talwalkar V. BrAIST-Calc: Prediction of Individualized Benefit From Bracing for Adolescent Idiopathic Scoliosis.
Spine (Phila Pa 1976) 2024;
49:147-156. [PMID:
37994691 PMCID:
PMC10841822 DOI:
10.1097/brs.0000000000004879]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 11/13/2023] [Indexed: 11/24/2023]
Abstract
STUDY DESIGN
Prospective multicenter study data were used for model derivation and externally validated using retrospective cohort data.
OBJECTIVE
Derive and validate a prognostic model of benefit from bracing for adolescent idiopathic scoliosis (AIS).
SUMMARY OF BACKGROUND DATA
The Bracing in Adolescent Idiopathic Scoliosis Trial (BrAIST) demonstrated the superiority of bracing over observation to prevent curve progression to the surgical threshold; 42% of untreated subjects had a good outcome, and 28% progressed to the surgical threshold despite bracing, likely due to poor adherence. To avoid over-treatment and to promote patient goal setting and adherence, bracing decisions (who and how much) should be based on physician and patient discussions informed by individual-level data from high-quality predictive models.
MATERIALS AND METHODS
Logistic regression was used to predict curve progression to <45° at skeletal maturity (good prognosis) in 269 BrAIST subjects who were observed or braced. Predictors included age, sex, body mass index, Risser stage, Cobb angle, curve pattern, and treatment characteristics (hours of brace wear and in-brace correction). Internal and external validity were evaluated using jackknifed samples of the BrAIST data set and an independent cohort (n=299) through estimates of discrimination and calibration.
RESULTS
The final model included age, sex, body mass index, Risser stage, Cobb angle, and hours of brace wear per day. The model demonstrated strong discrimination ( c -statistics 0.83-0.87) and calibration in all data sets. Classifying patients as low risk (high probability of a good prognosis) at the probability cut point of 70% resulted in a specificity of 92% and a positive predictive value of 89%.
CONCLUSION
This externally validated model can be used by clinicians and families to make informed, individualized decisions about when and how much to brace to avoid progression to surgery. If widely adopted, this model could decrease overbracing of AIS, improve adherence, and, most importantly, decrease the likelihood of spinal fusion in this population.
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