Cytoreductive surgery for colorectal peritoneal metastasis in the era modern systemic therapies: a systematic review and meta-analysis of survival outcomes
Bibliographic record
Abstract
INTRODUCTION: The value of surgical cytoreduction over modern systemic therapy in patients with colorectal peritoneal metastasis is debated. The present systematic review and meta-analysis aimed to determine the magnitude of the benefit of cytoreduction for peritoneal metastasis over varying intensities of palliative therapies. METHODS: The databases searched were PubMed, Cochrane Library, Scopus, CINHAL (EBSCO) and Google Scholar. The risk of bias was assessed using the RoB2 tool for randomized studies and the Newcastle-Ottawa scale for non-randomised studies. The certainty of the evidence was assessed using the GRADE Pro tool. The analysis used the log hazard ratio as the outcome measure for survival data with the random-effects model. Sensitivity analyses and meta-regressions were performed to establish the robustness of the results. RESULTS: = 0%) or publication bias. There was moderate certainty of evidence, that was downgraded due to clinical heterogeneity among studies and the risk of bias from non-randomized studies. Sensitivity analyses and meta-regression confirmed that the pooled hazard ratio remained unchanged irrespective of the systemic therapies used or the risk of bias of individual studies. CONCLUSIONS: Curative intent treatment of colorectal peritoneal metastasis by adding cytoreductive surgery over systemic chemotherapy alone, increased the OS by a large magnitude with moderate certainty of evidence, irrespective of the systemic therapy used.
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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 | 0.011 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.023 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".