High epiregulin (<i>EREG</i>) gene expression plus <i>K-ras</i> wild-type (WT) status as predictors of cetuximab benefit in the treatment of advanced colorectal cancer (ACRC): Results from NCIC CTG CO.17—A phase III trial of cetuximab versus best supportive care (BSC)
Bibliographic record
Abstract
4016 Background: Cetuximab, a monoclonal antibody targeting the epidermal growth factor receptor (EGFR), improves overall survival (OS) and progression free survival (PFS) in patients with K-ras WT chemotherapy refractory ACRC. Gene expression of the EGFR ligand epiregulin (EREG) may further predict benefit from cetuximab. Methods: CRC tumour samples were analyzed from a phase III clinical trial of cetuximab plus BSC vs BSC alone (NEJM 2007; 357(20)). EREG gene expression was detected in tumour-derived genomic RNA blinded to clinical outcome by quantitative real time-PCR. Using a pre-specified threshold for “high” EREG derived from a prior study (CA225–045), the predictive effect of (1) high vs low EREG among K-ras WT and (2) high EREG/K-ras WT status (“Combimarker”) versus all other patients on OS and PFS was examined using a Cox model with tests for treatment-biomarker interaction. Results: Both EREG gene expression levels and K-ras mutation status were ascertained in 385 (67%) of the total study population (193 cetuximab, 192 BSC). In the K-ras WT subset, OS was better for cetuximab than BSC among patients with high EREG (HR 0.43; p<0.0001) but not for low EREG patients (HR 0.77, p=0.28). The test for interaction showed a non-significantly larger treatment effect in the high EREG group (HR 0.62, p=0.13). High EREG AND K-ras WT status (“Combimarker”) was present in 139 (36%). Within the Combimarker positive group the median PFS was 5.4 vs 1.9 months (HR, 0.31; p<0.0001), and median OS 9.8 vs 5.1 months (HR, 0.43; p<0.001) in the cetuximab vs BSC arms, respectively. In the rest (n=246, 64%) cetuximab was not associated with improved PFS (HR, 0.82; p=0.12) or OS (HR, 0.90; p=0.45). The test for treatment-Combimarker interaction showed a larger cetuximab effect on OS (HR 0.52; p=0.007) and PFS (HR 0.49; p=0.001) in the Combimarker positive group. Conclusions: In the setting of pre-treated ACRC, patients with both high EREG gene expression and K-ras wild- type status may benefit from cetuximab therapy. Determination of EREG gene expression levels should be prospectively evaluated in patient selection for EGFR targeted therapy. [Table: see text]
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".