A Meta-Analysis of Concurrent Chemoradiotherapy for Advanced Esophageal Cancer
Bibliographic record
Abstract
BACKGROUND: Concurrent chemoradiotherapy is a standard treatment for local advanced esophageal cancer, but the outcomes are controversial. Our goals were to compare the therapeutic effects of concurrent chemoradiotherapy and radiotherapy alone in local advanced esophageal cancer using meta-analysis. METHODS: MEDLINE, EMBASE and the Cochrane library were searched for studies comparing chemoradiotherapy with radiotherapy alone for advanced esophageal cancer. Only randomized controlled trials were included, and extracted data were analyzed with Review Manager Version 5.2. The pooled relative risks (RR) and their 95% confidence intervals (CI) were calculated for statistical analysis. RESULTS: Nine studies were included. Of 1,135 cases, 612 received concurrent chemoradiotherapy and 523 were treated with radiotherapy alone. The overall response rate (complete remission and partial remission) was 93.4% for concurrent chemoradiotherapy and 83.7% for radiotherapy alone (P = 0.05). The RR values of 1-year, 3-year, and 5-year survival rates were 1.14 (95% CI: 1.04 - 1.24, P = 0.006), 1.66 (95% CI: 1.34 - 2.06, P < 0.001), and 2.43 (95% CI: 1.63 - 3.63, P < 0.001), respectively. The RR value of the merged occurrence rate of acute toxic effects was 2.34 (95% CI: 1.90 - 2.90, P <0.001). There was no difference in the incidence of late toxic effects, which had an RR value of 1.21 (95% CI: 0.96 - 1.54, P = 0.11). The RR level of persistence and recurrence was 0.71 (95% CI: 0.62 - 0.81, P <0.001), and for the distant metastasis rate, the RR value was 0.79 (95% CI: 0.61 - 1.02, P = 0.07). CONCLUSIONS: Concurrent chemoradiotherapy significantly improved overall survival rate, reduced the risk of persistence and recurrence, but had little effect on the primary tumor response, and increased the occurrence of acute toxic effects.
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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 | 0.022 | 0.037 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.070 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".