Concurrent cisplatin-based chemoradiotherapy versus exclusive radiotherapy in high-risk cervical cancer: a meta-analysis
Why this work is in the frame
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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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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 it