Lori A Dolan1, Stuart L Weinstein2, Mark F Abel3, Patrick P Bosch4, Matthew B Dobbs5, Tyler O Farber2, Matthew F Halsey6, M Timothy Hresko7, Walter F Krengel8, Charles T Mehlman9, James O Sanders10, Richard M Schwend11, Suken A Shah12, Kushagra Verma13. 1. Department of Orthopaedics and Rehabilitation, University of Iowa, 01048 JPP, 200 Hawkins Drive, Iowa City, IA 52242, USA. Electronic address: lori-dolan@uiowa.edu. 2. University of Iowa, 200 Hawkins Drive, Iowa City, IA 52242, USA. 3. University of Virginia Children's Hospital, 2270 Ivy Road, Charlottesville, VA 22903, USA. 4. UPMC Children's Hospital of Pittsburgh, 4401 Penn Ave, Pittsburgh, PA 15224, USA. 5. Washington University Orthopaedics in St. Louis, 1 Children's Place, St. Louis, MO 63110, USA. 6. Oregon Health & Science University, 3181 S.W. Sam Jackson Park Rd, Portland, OR 97239-3098, USA. 7. Boston Children's Hospital, 300 Longwood Ave, Boston, MA 02115, USA. 8. Seattle Children's Hospital, 4800 Sand Point Way NE, Seattle, WA 98105, USA. 9. Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave, Cincinnati, OH 45229, USA. 10. University of North Carolina at Chapel Hill, 130 Mason Farm Road, Chapel Hill, NC 27599, USA. 11. Children's Mercy Kansas City, 2401 Gillham Rd, Kansas City, MO 64108, USA. 12. Nemours/Alfred I. DuPont Hospital for Children, 1600 Rockland Rd, Wilmington, DE 19803, USA. 13. 3851 Katella Avenue, Suite 255, Los Alamitos, CA 90720, USA.
Abstract
STUDY DESIGN: Prognostic study and validation using prospective clinical trial data. OBJECTIVE: To derive and validate a model predicting curve progression to ≥45° before skeletal maturity in untreated patients with adolescent idiopathic scoliosis (AIS). SUMMARY OF BACKGROUND DATA: Studies have linked the natural history of AIS with characteristics such as sex, skeletal maturity, curve magnitude, and pattern. The Simplified Skeletal Maturity Scoring System may be of particular prognostic utility for the study of curve progression. The reliability of the system has been addressed; however, its value as a prognostic marker for the outcomes of AIS has not. The BrAIST trial followed a sample of untreated AIS patients from enrollment to skeletal maturity, providing a rare source of prospective data for prognostic modeling. METHODS: The development sample included 115 untreated BrAIST participants. Logistic regression was used to predict curve progression to ≥45° (or surgery) before skeletal maturity. Predictors included the Cobb angle, age, sex, curve type, triradiate cartilage, and skeletal maturity stage (SMS). Internal and external validity was evaluated using jackknifed samples of the BrAIST data set and an independent cohort (n = 152). Indices of discrimination and calibration were estimated. A risk classification was created and the accuracy evaluated via the positive (PPV) and negative predictive values (NPV). RESULTS: The final model included the SMS, Cobb angle, and curve type. The model demonstrated strong discrimination (c-statistics 0.89-0.91) and calibration in all data sets. The classification system resulted in PPVs of 0.71-0.72 and NPVs of 0.85-0.93. CONCLUSIONS: This study provides the first rigorously validated model predicting a short-term outcome of untreated AIS. The resultant estimates can serve two important functions: 1) setting benchmarks for comparative effectiveness studies and 2) most importantly, providing clinicians and families with individual risk estimates to guide treatment decisions. LEVEL OF EVIDENCE: Level 1, prognostic.
STUDY DESIGN: Prognostic study and validation using prospective clinical trial data. OBJECTIVE: To derive and validate a model predicting curve progression to ≥45° before skeletal maturity in untreated patients with adolescent idiopathic scoliosis (AIS). SUMMARY OF BACKGROUND DATA: Studies have linked the natural history of AIS with characteristics such as sex, skeletal maturity, curve magnitude, and pattern. The Simplified Skeletal Maturity Scoring System may be of particular prognostic utility for the study of curve progression. The reliability of the system has been addressed; however, its value as a prognostic marker for the outcomes of AIS has not. The BrAIST trial followed a sample of untreated AISpatients from enrollment to skeletal maturity, providing a rare source of prospective data for prognostic modeling. METHODS: The development sample included 115 untreated BrAIST participants. Logistic regression was used to predict curve progression to ≥45° (or surgery) before skeletal maturity. Predictors included the Cobb angle, age, sex, curve type, triradiate cartilage, and skeletal maturity stage (SMS). Internal and external validity was evaluated using jackknifed samples of the BrAIST data set and an independent cohort (n = 152). Indices of discrimination and calibration were estimated. A risk classification was created and the accuracy evaluated via the positive (PPV) and negative predictive values (NPV). RESULTS: The final model included the SMS, Cobb angle, and curve type. The model demonstrated strong discrimination (c-statistics 0.89-0.91) and calibration in all data sets. The classification system resulted in PPVs of 0.71-0.72 and NPVs of 0.85-0.93. CONCLUSIONS: This study provides the first rigorously validated model predicting a short-term outcome of untreated AIS. The resultant estimates can serve two important functions: 1) setting benchmarks for comparative effectiveness studies and 2) most importantly, providing clinicians and families with individual risk estimates to guide treatment decisions. LEVEL OF EVIDENCE: Level 1, prognostic.
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