Comparison of Short-Course Radiotherapy Versus Long-Course Radiotherapy for Treatment of Metastatic Spinal Cord Compression
Bibliographic record
Abstract
In this study, we evaluate the efficacy of short-course radiotherapy (SCRT) versus long-course radiotherapy (LCRT) in the treatment of metastatic spinal cord compression (MSCC).PubMed, EMBASE, and Web of Science were searched up to April 2015. Relevant data were extracted based on inclusion and exclusion criteria. Methodological quality of randomized controlled trial (RCT) was evaluated using modified Jadad scale; non-RCT was evaluated using Newcastle-Ottawa Scale. Meta-analysis was performed using RevMan 5.3 software.Fourteen studies with 2239 patients were included. Results of meta-analysis showed that there were no significant differences between SCRT and long-course radiotherapy LCRT in 6-month overall survival rate (risk ratio [RR] = 0.97, 95% confidence interval [CI] 0.88, 1.07, P = 0.55), 1-year overall survival rate (RR = 0.94, 95% CI 0.85, 1.04, P = 0.22), motor function improvement (RR = 0.96, 95% CI 0.81, 1.13, P = 0.63), no change on motor function (RR = 0.98, 95% CI (0.88, 1.09), P = 0.74], and deterioration on motor function (RR = 0.96, 95% CI 0.71, 1.31, P = 0.78). Compared with SCRT, LCRT significantly increased 6-month local control rate (RR = 0.87, 95% CI 0.80, 0.95, P = 0.002), 1-year local control rate (RR = 0.83, 95% CI 0.71, 0.97, P = 0.02), and 2-year local control rate (RR = 0.83, 95% CI 0.79, 0.87, P < 0.00001).Both LCRT and SCRT provided similar survival rates and functional outcome, but LCRT showed better local control rates than SCRT. However, considering low cost and good patient's compliance, SCRT may be a better choice.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.009 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| 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".