Disease-free (DFS) and overall survival (OS) at 3.4 years (yrs) for neoadjuvant bevacizumab (Bev) added to docetaxel followed by fluorouracil, epirubicin and cyclophosphamide (D-FEC), for women with HER2 negative early breast cancer: The ARTemis trial.
Bibliographic record
Abstract
1014 Background: ARTemis compared the addition of Bev to neoadjuvant D-FEC in HER2 negative breast cancer. Improved pathological complete response (pCR) with Bev has been reported previously. Methods: We enrolled women ≥ 18 yrs with radiological tumour size > 20mm, ± axillary involvement, at 66 centres in the UK. Patients (pts) were randomly assigned to 3 cycles of D (100 mg/m² every [q] 21 days [d]) followed by 3 cycles of F (500mg/m2), E (100mg/m2) and C (500 mg/m²) q 21d (D-FEC), ± 4 cycles Bev (15mg/kg) (Bev+D-FEC). We present the DFS and OS results, analysed by intention-to-treat. pCR is defined by report review; analysis by central pathology review will be available at the time of presentation. Results: Between May’09 and Jan’13, we randomised 800 pts; 401 to D-FEC and 399 to Bev+D-FEC. Median follow-up was 3.4 yrs (IQR 2.5–4.4). 131 deaths and 183 DFS events have occurred. Both OS and DFS were similar across treatments (3-yr OS: Bev+D-FEC 85%, D-FEC 87%; hazard ratio (HR) 0.80 (95%CI 0.57-1.12) p = 0.19. 3-yr DFS: Bev+D-FEC 77%, D-FEC 80%; HR 0.86 (95%CI 0.64-1.14) p = 0.29). pCR was associated with improved OS in D-FEC pts (3-yr OS: pCR 96%, non-pCR 84%; log-rank p = 0.01) but not with Bev+D-FEC (3-yr OS: pCR 87%, non-pCR 83%; log-rank p = 0.71). Similarly pCR predicted for improved DFS with D-FEC (3-yr DFS: pCR 97%, non-pCR 76%; log-rank p = 0.0006), but not with Bev+D-FEC (3-yr DFS: pCR 84%, non-pCR 74%; log-rank p = 0.19). There was borderline heterogeneity in the effect of the addition of Bev between pCR and non-pCR groups in terms of OS (p = 0.07), and significant heterogeneity in terms of DFS (p = 0.02). Conclusions: Although Bev+D-FEC produced significantly higher pCR rates when added to chemotherapy in the ARTemis trial, OS and DFS were not improved. Moreover pCR achieved by Bev+D-FEC does not appear to be associated with the improved OS and DFS which is seen with pCR achieved by D-FEC. This data suggests that micro-metastatic breast cancer may be angiogenesis-independent and hence not altered by neoadjuvant Bev treatment. Clinical trial information: ISRCTN 68502941.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".