Chemo-radiotherapy versus radiotherapy alone for nasopharyngeal carcinoma: A meta-analysis of 78 randomized controlled trials (RCTs) from English and non-English databases
Bibliographic record
Abstract
5522 Background: To obtain the best estimate for survival benefits of chemo-radiotherapy (CT + RT) compared with radiotherapy alone (RT) in nasopharyngeal cancer (NPC) and to evaluate the optimal timing of CT Methods: Datasources: 10 English language databases, 6 Chinese, including hand searching 26 Chinese Oncology Journals, 3 Korean, 2 Japanese, 1 African and 1 South East Asian databases. The Cochrane search strategy was used. Study Selection: Published reports or abstracts of RCTs comparing CT + RT versus RT for newly diagnosed NPC. Data Extraction: 2 reviewers independently extracted data and scored for trial quality.Where available, authors were contacted for actual number of events. Quality Scores: 2 points for randomization, 1 for completeness of follow up and 1 for intention-to-treat analysis (score range 0–4) Results: Data Synthesis: 101 RCTs were identified, 88 from Chinese and 13 from English language. 78 RCTs (9279 pts) reported 2 year or longer survival with characteristics as follows: median quality score 2, median sample size 89, number of RCTs : neoadjuvant (N) only 28, concurrent (C) only 19, adjuvant (A) only 8, C+A 3, N+C 5, N+A 14, N+C+A 6 ( > 2 arms in 3 RCTs). CT was cisplatin in 68, non-cisplatin in 10. Pooled Analysis: [table] Across all trials, CT + RT improve overall survival (OS) and disease free survival (DFS). Concurrent CT with or without adjuvant CT and neoadjuvant CT alone all improve OS and DFS. Sensitivity analysis of 3 year OS was done by excluding poor quality studies. The results were unchanged; however the effect of all trials and of neoadjuvant CT are borderline when all Chinese trials were excluded. Conclusions: CT administered concurrently with or without adjuvant therapy + RT improves OS and DFS in NPC. The role of CT as neoadjuvant remains controversial when Chinese trials are excluded from the analysis. No significant financial relationships to disclose.
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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 | 0.060 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.044 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".