Surgical Management of Spinal Chondrosarcomas
Bibliographic record
Abstract
STUDY DESIGN: An ambispective cohort study. OBJECTIVE: The aim of this study was to determine whether the application of the Enneking classification in the management of spinal chondrosarcomas influences local recurrence and survival. SUMMARY OF BACKGROUND DATA: Primary spinal chondrosarcomas are rare. Best available evidence is based on small case series, thus making it difficult to determine optimal management and risk factors for local recurrence and survival. METHODS: The AOSpine Knowledge Forum Tumor developed a multicenter ambispective database of surgically treated patients with spinal chondrosarcoma. Patient data pertaining to demographics, diagnosis, treatment, cross-sectional survival, and local recurrence were collected. Tumors were classified according to the Enneking classification. Patients were divided into two cohorts: Enneking appropriate (EA) and Enneking inappropriate (EI). They were categorized as EA when the final pathological assessment of the margin matched the Enneking recommendation, and otherwise, they were categorized as EI. RESULTS: Between 1987 and 2011, 111 patients (37 female; 74 male) received surgical treatment for a primary spinal chondrosarcoma at a mean age of 47.4 ± 15.8 years. Patients were followed for a median period of 3.1 years (range = 203 d-18.7 yrs). Median survival for the entire cohort was 8.4 years postoperative. After 10 years postoperative, 36 (32%) patients died and 37 (35%) patients suffered a local recurrence. Twenty-three of these 37 patients who suffered a local recurrence died. Sixty (58%) patients received an EA procedure while 44 (42%) received an EI procedure. EI patients had a higher hazard ratio for local recurrence than those who received an EA procedure (P = 0.052). Local recurrence was strongly associated with chondrosarcoma-related death (risk ratio = 3.6, P < 0.010). CONCLUSION: This is the largest multicenter cohort of spinal chondrosarcomas. EA surgical management appeared to correlate with a decreased risk of local recurrence, yet no relationship with survival was found. Where possible, surgeons should strive to achieve EA margins to minimize the risk of local recurrence. LEVEL OF EVIDENCE: 4.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".