Emergent radiotherapy for spinal cord compression/impingement—a narrative review
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Malignant epidural spinal cord compression (MESCC), often presenting with back pain and motor/sensory deficits, is associated with poor survival, particularly when there is loss of ambulation. The purpose of this review is to evaluate the literature and discuss appropriate workup and management of MESCC, specifically in the emergent setting. METHODS: A PubMed search was conducted on "spinal cord compression" and "radiation therapy." Articles were analyzed for the purpose of this narrative review. KEY CONTENT AND FINDINGS: If MESCC is suspected, neurologic examination and complete spine imaging are recommended. Emergent treatment is indicated if there is radiographic evidence of high-grade compression and/or clinically significant motor deficits. Treatment involves a combination of medical management, surgical decompression, radiation therapy (RT), and rehabilitation. For motor deficits, emergent initiation of high dose steroids is recommended. Circumferential surgical decompression ± stabilization followed by RT provides superior clinical outcomes than RT alone. For patients whom surgery is not reasonable, RT alone may provide significant treatment response which depends on radioresponsiveness of the pathology. Systemic therapy, if indicated, is typically reserved till after primary treatment of MESCC, but patients with chemoresponsive tumors may receive primary chemotherapy. The selected RT schedule should be personalized to each patient and commonly is 30 Gy in 10 fractions (fx), 20 Gy in 5 fx, or 8 Gy in 1 fx. MESCC recurrence may be treated with additional RT, if within the spinal cord tolerance, or surgery. Stereotactic body radiation therapy (SBRT) has been used for high grade MESCC in patients with relatively intact neurologic function at a few centers with a very robust infrastructure to support rapid initiation of treatment within a short period of time, but is generally not feasible for most clinical practices. SBRT may be advantageous for low grade MESCC, recurrence, or in the post-operative setting. Detection of MESCC prior to development of high-grade compression or deterioration of neurologic function may allow patients to benefit more from advanced therapies and improve prognosis. CONCLUSIONS: MESCC is a devastating condition; optimal treatment should be personalized to each patient and approached collaboratively by a multidisciplinary team.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".