Efficacy of Cetuximab in Nasopharyngeal Carcinoma Patients Receiving Concurrent Cisplatin-Radiotherapy: A Meta-Analysis
Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
Background: Nasopharyngeal carcinoma (NPC) is a malignant neoplasm of the nasopharyngeal epithelium. Concurrent chemoradiotherapy has been established as a standard treatment for locoregional NPC, and cisplatin is a common agent in NPC treatment. Cetuximab is a monoclonal antibody against epidermal growth factor receptor. This meta-analysis was performed to evaluate the curative effectiveness and survival outcomes of cetuximab in NPC patients who received concurrent cisplatin-radiotherapy. Methods: PubMed, Cochrane Library, EMBASE, China National Knowledge Infrastructure (CNKI), Wan Fang, and China Biology Medicine disc (CBM) were used to search publications studying on concurrent chemoradiotherapy and/or cetuximab in NPC. The qualities of included RCTs were assessed by the Newcastle-Ottawa Scale. STATA 14.0 was used to conduct the statistical analysis. Results: In total, 17 trials with 2066 patients were included in this meta-analysis. The results from this study show that cetuximab improved the therapy efficacy in NPC patients who received concurrent cisplatin-radiotherapy. Cetuximab cotreatment improved the complete response (RR = 1.92, 95% CI [1.61, 2.30]), and reduced stable disease (RR = 0.67, 95% CI [0.51, 0.88]) as well as progression disease (RR = 0.24, 95% CI [0.15, 0.40]). Besides, it also improved the overall survival (RR = 1.10, 95% CI [1.02, 1.18]), disease-free survival (RR = 1.09, 95% CI [1.03, 1.15]), metastasis-free survival (RR = 1.06, 95% CI [1.01, 1.11]), and relapse-free survival (RR = 1.04, 95% CI [1.01, 1.07]) in NPC patients. Conclusions: Cetuximab could improve the curative efficacy and survival outcomes of NPC patients who underwent concurrent cisplatin-radiotherapy. However, all the trials included were conducted in China; thus, the quality of the trials in this study remains doubtful. More high-quality RCTs should be included in further relevant studies.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.064 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".