Patient outcomes in idiopathic scoliosis are associated with biological endophenotypes: 2020 SOSORT award winner
Bibliographic record
Abstract
PURPOSE: Bracing is the treatment of choice for idiopathic scoliosis (IS), unfortunately factors underlying brace response remain unknown. Clinicians are currently unable to identify patients who may benefit from bracing, and therefore, better molecular stratification is critically needed. The aim of this study is to evaluate IS patient outcomes at skeletal maturity in relation to biological endophenotypes, and determine specific endophenotypes associated to differential bracing outcomes. This is a retrospective cohort with secondary cross-sectional comparative studies. METHODS: Clinical and radiological data were collected from 563 IS patients, stratified into biological endophenotypes (FG1, FG2, FG3) based on a cell-based test. Measured outcomes were maximum Cobb angle at skeletal maturity, and if severe, spinal deformity (≥ 45°) or surgery was attained. Treatment success/failure was determined by standard progression thresholds (Cobb ≥ 45° or surgery; Cobb angle progression ≥ 6°). Multivariable analyses were performed to evaluate associations between endophenotypes and clinical outcome. RESULTS: Higher Cobb angles at maturity for FG1 and FG2 patients were observed (p = 0.056 and p = 0.05), with increased likelihood of ≥ 45° and/or surgery for FG1 (OR = 2.181 [1.002-4.749] and FG2 (OR = 2.141 [1.038-4.413]) compared to FG3. FG3 was 9.31 [2.58-33.61] and 5.63 [2.11-15.05] times more likely for bracing success at treatment termination and based on the < 6° progression criterion, respectively, compared to FG1. CONCLUSION: Associations between biological endophenotypes and outcomes suggest differences in progression and/or bracing response among IS patients. Outcomes were most favorable in FG3 patients. The results pave the way for establishing personalized treatments, distinguishing who may benefit or not from treatment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".