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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.

2016· article· en· W2702220459 on OpenAlexaff
Helena Earl, Louise Hiller, Janet Dunn, Clare Blenkinsop, Louise Grybowicz, Anne-Laure Vallier, Jean Abraham, Luke Hughes‐Davies, Karen McAdam, Stephen Chan, Rizvana Ahmad, Tamas Hickish, Stephen Houston, Daniel Rea, John M.S. Bartlett, Carlos Caldas, David Cameron, Elena Provenzano, Jeremy Thomas, Larry Hayward

Bibliographic record

VenueJournal of Clinical Oncology · 2016
Typearticle
Languageen
FieldMedicine
TopicCancer Treatment and Pharmacology
Canadian institutionsOntario Institute for Cancer Research
Fundersnot available
KeywordsMedicineDocetaxelInternal medicineEpirubicinFluorouracilHazard ratioBreast cancerNeoadjuvant therapyOncologyBevacizumabGastroenterologyChemotherapyCancerConfidence interval

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.049
GPT teacher head0.406
Teacher spread0.357 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

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Citations5
Published2016
Admission routes1
Has abstractyes

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