Concurrent cisplatin-based chemoradiotherapy versus exclusive radiotherapy in high-risk cervical cancer: a meta-analysis
Bibliographic record
Abstract
OBJECTIVE: To evaluate the efficacy and safety of cisplatin-based concurrent chemoradiotherapy (DDP-CCRT) in patients with high-risk cervical carcinoma (CC) compared with exclusive radiotherapy (RT). MATERIALS AND METHODS: Databases were searched for randomized controlled trials (RCTs) and cohort studies comparing DDP-CCRT with RT alone. Risk of bias assessment for RCTs was performed using the Cochrane Collaboration's tool, and the Newcastle-Ottawa quality scale was used to perform quality assessment for cohort studies. Meta-analysis was conducted using Review Manager 5 and Stata 12.0 software. RESULTS: Finally, eight RCTs and three cohort studies containing 2,130 subjects were included. Analysis on total failures revealed a statistically significant difference in favor of DDP-CCRT (risk ratio =0.77, 95% confidence intervals [CIs]: 0.67-0.89). No significant heterogeneity was detected for pooled analysis concerning overall survival; the result of which demonstrated the superiority of DDP-CCRT over RT alone (hazard ratio =0.68, 95% CI: 0.57-0.80), and stable and established accumulative effects were observed in cumulative meta-analysis. Similar results were observed for progression-free survival (hazard ratio =0.63, 95% CI: 0.50-0.76). In terms of treatment-related Grade 3 and 4 adverse events, our pooled analysis with a fixed-effects model showed significantly enhanced toxicity in the DDP-CCRT group compared with that in the RT group (odds ratio =3.13, 95% CI: 2.37-4.13). CONCLUSION: Solid and stable beneficial effects are associated with DDP-CCRT, and its superiority over comparative RT in patients with high-risk CC is confirmed. DDP-CCRT should be considered one of the frontline treatment options for high-risk CC patients without contraindications. However, enhanced toxicity associated with DDP-CCRT should never be ignored.
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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 | 0.018 | 0.025 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.065 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 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".