The Efficacy and Safety of Celecoxib in Addition to Standard Cancer Therapy: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Bibliographic record
Abstract
The purpose of this meta-analysis was to evaluate the efficacy and safety of celecoxib, a selective cyclooxygenase-2 (COX-2) inhibitor, in addition to standard anticancer therapy. Randomized controlled trials (RCTs) that evaluated the efficacy and safety of celecoxib-combined cancer therapy were systematically searched in PubMed and Embase databases. The endpoints were overall survival (OS), progression-free survival (PFS), disease-free survival (DFS), objective response rate (ORR), disease control rate (DCR), pathological complete response (pCR), and adverse events (AEs). The results of 30 RCTs containing 9655 patients showed limited benefits in celecoxib-combined cancer therapy. However, celecoxib-combined palliative therapy prolonged PFS in epidermal growth factor receptor (EGFR) wild-type patients (HR = 0.57, 95%CI = 0.35-0.94). Moreover, despite a slight increase in thrombocytopenia (RR = 1.35, 95%CI = 1.08-1.69), there was no increase in other toxicities. Celecoxib combined with adjuvant therapy indicated a better OS (HR = 0.850, 95%CI = 0.725-0.996). Furthermore, celecoxib plus neoadjuvant therapy improved the ORR in standard cancer therapy, especially neoadjuvant therapy (overall: RR = 1.13, 95%CI = 1.03-1.23; neoadjuvant therapy: RR = 1.25, 95%CI = 1.09-1.44), but not pCR. Our study indicated that adding celecoxib to palliative therapy prolongs the PFS of EGFR wild-type patients, with good safety profiles. Celecoxib combined with adjuvant therapy prolongs OS, and celecoxib plus neoadjuvant therapy improves the ORR. Thus, celecoxib-combined cancer therapy may be a promising therapy strategy.
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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 | 0.016 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.039 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| 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".