Surgical or Radiation Therapy for the Treatment of Cervical Spine Metastases: Results From the Epidemiology, Process, and Outcomes of Spine Oncology (EPOSO) Cohort
Bibliographic record
Abstract
Study Design: Ambispective cohort study design. Objectives: Cervical spine metastases have distinct clinical considerations. The aim of this study was to determine the impact of surgical intervention (± radiotherapy) or radiotherapy alone on health-related quality of life (HRQOL) outcomes in patients treated for cervical metastatic spine tumours. Methods: Patients treated with surgery and/or radiotherapy for cervical spine metastases were identified from the Epidemiology, Process, and Outcomes of Spine Oncology (EPOSO) international multicentre prospective observational study. Demographic, diagnostic, treatment, and HRQOL (numerical rating scale [NRS] pain, EQ-5D (3L), SF-36v2, and SOSGOQ) measures were prospectively collected at baseline, 6 weeks, 3 months, and 6 months postintervention. Results: Fifty-five patients treated for cervical metastases were identified: 38 underwent surgery ± radiation and 17 received radiation alone. Surgically treated patients had higher mean spinal instability neoplastic scores compared with the radiation-alone group (13.0 vs 8.0, P < .001) and higher NRS pain scores and lower HRQOL scores compared to the radiation alone group ( P < .05). From baseline to 6 months posttreatment, surgically treated patients demonstrated statistically significant improvements in NRS pain, EQ-5D (5L), and SOSGOQ2.0 scores compared with nonsignificant improvements in the radiotherapy alone group. Conclusions: Surgically treated cervical metastases patients presented with higher levels of instability, worse baseline pain and HRQOL scores compared with patients who underwent radiotherapy alone. Significant improvements in pain and HRQOL were noted for those patients who received surgical intervention. Limited or no improvements were found in those treated with radiotherapy alone.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".