A Meta-Analysis to Assess the Efficacy of HER2-Targeted Treatment Regimens in HER2-Positive Metastatic Colorectal Cancer (mCRC)
Bibliographic record
Abstract
Recent trials provide evidence that HER2 is a potential new target for patients with colorectal cancer. While HER2-positive tumors do not show a very encouraging response to anti-HER2-positive agents like trastuzumab alone, promising results have been observed when combined with other synergistically acting tyrosine kinase inhibitors (TKIs). Our meta-analysis was conducted following the Cochrane Handbook and written following the PRISMA guidelines. The protocol was registered on PROSPERO with the registration number CRD42022338935. After a comprehensive search for relevant articles, 14 CTs were identified and uploaded to Rayyan, and six trials were ultimately selected for inclusion. The meta-analysis revealed that a median of three prior lines of therapy was used before enrolling in the six trials comprising 238 patients with HER2-positive metastatic colorectal cancer (mCRC). The pooled objective response rate (ORR) and disease control rate (DCR) were 31.33% (95% confidence interval [CI] 24.27-38.39) and 74.37% (95% CI 64.57-84.17), respectively. The pooled weighted progression-free survival (PFS) was 6.2 months. The pooled ORR and DCR meta-analysis indicate a significant response to HER2-targeted therapy in this patient in HER2-positive mCRC. Additionally, a pooled PFS of 6.2 months suggests that HER2-targeted treatment regimens are associated with a meaningful improvement in survival outcomes in this population.
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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 | 0.025 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.062 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".