Impact of recent clinical trials on meta-analysis of stereotactic body radiation therapy for spine metastases and urgent call for consistent study endpoints
Bibliographic record
Abstract
Pain from spinal metastases can result in significant impact to patients' quality of life. Conventional external beam radiation therapy (cEBRT) has long been shown to be effective in the pain control of patients with spinal metastases. With the advancement in radiation therapy, stereotactic body radiation therapy (SBRT) has been increasingly adopted for the treatment of spinal metastases. Multiple randomised controlled trials (RCT) have been performed to evaluate whether SBRT provides better pain relief compared to cEBRT. Previous meta-analyses showed that SBRT have significantly better complete pain response at 3 months compared to cEBRT. This report updates meta-analyses by incorporating the complete pain response data obtained from personal communication with the NRG Oncology Radiation Therapy Oncology Group (RTOG) 0631 principal investigator and the recently published RCT by Guckenberger et al. The results demonstrate that the results for complete pain response at 3 months have now changed and no longer favour SBRT. It is postulated that inconsistent definitions and reporting of study endpoints, specifically regarding vertebral compression fractures induced by radiation therapy, could be possible reasons for the difference in meta-analyses results. A consensus for standardizing study endpoints for future clinical trials in SBRT for painful bone metastases is needed to allow for better interpretation of study results.
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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 | 0.149 | 0.285 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.067 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".