Osteosarcoma of the Spine: Prognostic Variables for Local Recurrence and Overall Survival, A Multicenter Ambispective Study
Bibliographic record
Abstract
Introduction Primary spinal osteosarcomas are rare and aggressive neoplasms with poor outcomes. Enneking appropriate, en bloc resection is recommended for appendicular osteosarcomas. Obtaining even marginal margins is technically demanding in the spine, resulting in significant morbidity and possible functional sacrifice. The aim of this study was to identify prognostic variables on local recurrence and mortality, in surgically treated patients diagnosed with a primary osteosarcoma of the spine. Methods A multicenter ambispective database of surgically treated patients with primary spine osteosarcomas was developed by the AOSpine knowledge forum tumor. Patient demographic, diagnosis, treatment, perioperative morbidity, local recurrence, and cross-sectional survival data were collected. Tumors were classified according to Enneking principles and analyzed in the following two cohorts: Enneking appropriate (EA) and Enneking inappropriate (EI). EA was defined by the final pathology margin matching the Enneking recommended surgical margin and EI by not matching. Prognostic variables including age, previous spine tumor operation, biopsy type, spine level, tumor size, and chemotherapy timing were analyzed in reference to local recurrence and survival. Results Between 1987 and 2012, 57 patients (31 females and 26 males) underwent surgical treatment for a primary spinal osteosarcoma at a mean age of 36 ± 16 years. Patients were followed for a mean period of 3.4 ± 3.5 years (range, 0.5 days–14.3 years). Median survival for the entire cohort was 6.7 years postoperative. Overall, 24 (42%) patients died and 17 (30%) patients suffered a local recurrence, 10 (59%) of which died. Overall, 28 (52%) patients underwent EA resection while 26 (48%) patients were treated by EI resection. Median survival for patients with EA was 6.8 years postoperative, whereas median survival for EI patients was 3.7 years postoperatively ( p = 0.062). EI patients were at a higher risk of local recurrence than EA patients ( p = 0.002). Patient age, previous spine tumor operation, tumor size, spine level, and chemotherapy timing did not significantly influence recurrence and survival. Conclusion Osteosarcoma of the spine presents a significant challenge and most patients die from their disease in spite of aggressive surgery. There is a significant decrease in recurrence with en bloc resection when compared with intralesional resection.
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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) | 0.001 | 0.000 |
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".