Systematic Review of the Diagnosis and Management of Malignant Extradural Spinal Cord Compression: The Cancer Care Ontario Practice Guidelines Initiative‘s Neuro-Oncology Disease Site Group
Bibliographic record
Abstract
PURPOSE: This systematic review describes the diagnosis and management of adult patients with a suspected or confirmed diagnosis of extradural malignant spinal cord compression (MSCC). METHODS: MEDLINE, CANCERLIT, and the Cochrane Library databases were searched to January 2004 using the following terms: spinal cord compression, nerve compression syndromes, spinal cord neoplasms, clinical trial, meta-analysis, and systematic review. RESULTS: Symptoms for MSCC include sensory changes, autonomic dysfunction, and back pain; however, back pain was not predictive of MSCC. The sensitivity and specificity for magnetic resonance imaging (MRI) range from 0.44 to 0.93 and 0.90 to 0.98, respectively, in the diagnosis of MSCC. The sensitivity and specificity for myelography range from 0.71 to 0.97 and 0.88 to 1.00, respectively. A randomized study detected higher ambulation rates in patients with MSCC who received high-dose dexamethasone before radiotherapy (RT) compared with patients who did not receive corticosteroids before RT (81% v 63% at 3 months, respectively; P = .046). There is no direct evidence that supports or refutes the type of surgery patients should have for the treatment of MSCC, whether surgical salvage should be attempted if patient is progressing on or shortly after RT, and whether patients with spinal instability should be treated with surgery. CONCLUSION: Patients with symptoms of MSCC should be managed to minimize treatment delay. MRI is the preferred imaging technique. Treatment for patients with MSCC should consider pretreatment ambulatory status, comorbidities, technical surgical factors, the presence of bony compression and spinal instability, potential surgical complications, potential RT reactions, and patient preferences.
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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 | 0.007 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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".