Percutaneous Cordotomy for Pain Palliation in Advanced Cancer: A Randomized Clinical Trial Study Protocol
Bibliographic record
Abstract
BACKGROUND: Cancer pain, one of the most common symptoms for patients with advanced cancer, is often refractory to maximal medical therapy. A controlled clinical trial is needed to provide definitive evidence to support the use of ablative procedures such as cordotomy for patients with medically refractory cancer pain. OBJECTIVE: To assess the efficacy of cordotomy for patients with unilateral advanced cancer pain using a controlled clinical trial study design. The secondary objectives are to define the patient experience of cordotomy for medically refractory cancer pain as well as to determine the utility of magnetic resonance imaging as a non-invasive biomarker for successful cordotomy. METHODS: We will undertake a single-institution, double-blind, sham-controlled clinical trial of cordotomy in patients with refractory cancer pain. Patients in the cordotomy arm will undergo a percutaneous computed tomography-guided cordotomy at C1-C2, while patients in the control arm will undergo a similar procedure where the needle will not penetrate the thecal sac. The primary endpoint will be the reduction in pain intensity, as measured by the Edmonton Symptoms Assessment Scale. EXPECTED OUTCOMES: We expect that patients randomized to cordotomy will have a significantly greater reduction in pain intensity than those patients randomized to the control surgical intervention. DISCUSSION: This randomized clinical trial comparing cordotomy with a control intervention will provide the level of evidence necessary to determine whether cordotomy should be the standard of care intervention for patients with advanced cancer pain.
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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 | 0.029 | 0.025 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.056 | 0.010 |
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".