Does the addition of biologic agents to chemotherapy in patients with unresectable colorectal cancer metastases result in a higher proportion of patients undergoing resection? A systematic review and meta-analysis.
Bibliographic record
Abstract
690 Background: The likelihood of converting unresectable metastatic colorectal cancer (CRC) to operable disease with systemic therapy is unknown. The purpose of this study was to determine the proportion of patients with unresectable CRC metastases that become resectable on combination systemic therapy, and whether biologic agents (antiantiogenics, anti-EGFR and multitargeted agents) improve the rate of resection (primary outcome). Methods: We searched Medline, Embase, CENTRAL and PubMed for randomized controlled trials comparing chemotherapy and biologics (intervention) vs. combination chemotherapy alone (control) in patients with unresectable CRC metastases. Study selection, data abstraction, risk of bias and quality of the evidence assessment were carried out in duplicate. Secondary outcomes included overall survival (OS) and progression free survival (PFS). Risk of bias was assessed using the Cochrane tool. Statistical heterogeneity was calculated using chi-squared and I2. Clinical heterogeneity was explored via subgroup analyses. The quality of the evidence was assessed using GRADE. Protocol was published in PROSPERO. Results: Of 7954 abstracts retrieved, 12 studies were analyzed and 8 reported the primary outcome, with 2604 intervention and 2661 control patients. The proportion of patients resected was higher in the intervention group, Relative Risk 1.36, 95% confidence interval (CI) 1.08-1.69, p = 0.008. The absolute risk of undergoing resection was 48 per 1000 (control); compared to 65 per 1000 (intervention). There was no difference in OS, Hazard Ratio (HR) 0.91, 95% CI 0.82-1.01. PFS was better in the intervention group (HR 0.83, 95% CI 0.74-0.92). Overall the risk of bias for the included studies was low. Statistical test for heterogeneity was low (I2 was 0%, p = 0.72). There was significant clinical heterogeneity, which was not explained with subgroup analyses. The quality of the evidence (GRADE) was moderate. Conclusions: The addition of biologic agents to systemic chemotherapy in patients with unresectable CRC metastasis improves resectability and PFS but not OS.
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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 | 0.021 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.040 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 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".