Instability and impending instability of the thoracolumbar spine in patients with spinal metastases: a systematic review
Bibliographic record
Abstract
Metastatic disease commonly occurs in the spine and incidence is likely to increase secondary to improved survival rates in many cancer patients. Despite published research on instability in patients with metastatic disease of the thoracolumbar spine, controversy exists regarding risk factors for instability and indications for surgical stabilization. The objective of this systematic review was to determine what defines instability and impending instability in patients with metastatic disease of the thoracic and lumbar spine. We systematically reviewed the medical literature in order to identify all the relevant studies concerning patients with metastatic involvement of T1-L5, in the domains of biomechanics, epidemiology, clinical issues, and radiographic parameters. Two independent observers performed study selection, methodological quality assessment, and data extraction in a blinded and objective manner for all the identified studies. We were then able to define the criteria to identify instability of the spine with metastases. A literature search and review identified 14 relevant, good quality studies for inclusion. The predictors of instability included increased tumor size, a larger cross-sectional area of bone defect, increased force of spinal loading, decreased bone density, posterior location of the tumor within the vertebrae, destruction of the costovertebral joint, pedicle destruction in the thoracolumbar spine, increased axial rigidity, and sagittal spinal deformity. Definitive conclusions cannot be reached due to lack of evidence. However, variables such as tumor size, magnitude of spinal loading, bone density, tumor location within the vertebrae and spine, and tumor type are risk factors for instability in spinal metastases. Improved clinical research methodology for this patient population is required.
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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 | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".