Surgical management of spinal osteoblastomas
Bibliographic record
Abstract
OBJECTIVE Osteoblastoma is a rare primary benign bone tumor with a predilection for the spinal column. Although of benign origin, osteoblastomas tend to behave more aggressively clinically than other benign tumors. Because of the low incidence of osteoblastomas, evidence-based treatment guidelines and high-quality research are lacking, which has resulted in inconsistent treatment. The goal of this study was to determine whether application of the Enneking classification in the management of spinal osteoblastomas influences local recurrence and survival time. METHODS A multicenter database of patients who underwent surgical intervention for spinal osteoblastoma was developed by the AOSpine Knowledge Forum Tumor. Patient data pertaining to demographics, diagnosis, treatment, cross-sectional survival, and local recurrence were collected. Patients in 2 cohorts, based on the Enneking classification of the tumor (Enneking appropriate [EA] and Enneking inappropriate [EI]), were analyzed. If the final pathology margin matched the Enneking-recommended surgical margin, the tumor was classified as EA; if not, it was classified as EI. RESULTS A total of 102 patients diagnosed with a spinal osteoblastoma were identified between November 1991 and June 2012. Twenty-nine patients were omitted from the analysis because of short follow-up time, incomplete survival data, or invalid staging, which left 73 patients for the final analysis. Thirteen (18%) patients suffered a local recurrence, and 6 (8%) patients died during the study period. Local recurrence was strongly associated with mortality (relative risk 9.2; p = 0.008). When adjusted for Enneking appropriateness, this result was not altered significantly. No significant differences were found between the EA and EI groups in regard to local recurrence and mortality. CONCLUSIONS In this evaluation of the largest multicenter cohort of spinal osteoblastomas, local recurrence was found to be strongly associated with mortality. Application of the Enneking classification as a treatment guide for preventing local recurrence was not validated.
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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) | 0.001 | 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".