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Abstract S6-5: Primary results of BEATRICE, a randomized phase III trial evaluating adjuvant bevacizumab-containing therapy in triple-negative breast cancer

2012· article· en· W2003492008 on OpenAlexaff
David Cameron, Julia Brown, Rebecca Dent, C Jackisch, John R. Mackey, Xavier Pivot, G. Steger, Thomas Suter, Masakazu Toi, Mahesh Parmar, Lida Bubuteishvili‐Pacaud, Volkmar Henschel, R. Laeufle, Rachel Bell

Bibliographic record

VenueCancer Research · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineTaxaneInternal medicineBreast cancerOncologyBevacizumabAnthracyclineTriple-negative breast cancerRandomized controlled trialCancerMastectomyAdjuvantChemotherapy

Abstract

fetched live from OpenAlex

Abstract Background: Bevacizumab (BEV), an anti-VEGF antibody, significantly enhanced progression-free survival in metastatic breast cancer (BC) (E2100, AVADO, RIBBON-1, RIBBON-2) and pathologic complete response rates in the neoadjuvant setting (GeparQuinto, NSABP B-40) when combined with chemotherapy (CT). The dependence of micro-metastases on angiogenesis [Holmgren 1995] suggests that patients might benefit from anti-angiogenic strategies applied in the adjuvant setting. The BEATRICE trial was designed to test this hypothesis in patients with triple-negative BC, who have a poor prognosis and lack targeted options for treatment. Methods: In this open-label randomized multinational phase III trial, patients with centrally confirmed triple-negative operable primary invasive BC (pT1a-pT3) were randomized 1:1 after definitive surgery to receive ≥4 cycles of either CT alone or the same CT + 1 year of BEV 5 mg/kg/wk equivalent. CT was anthracycline [anth] and/or taxane-based. Patients were stratified by nodal status (0 vs 1–3 vs ≥4 involved nodes), CT backbone (anth vs anth + taxane vs taxane), hormone receptor status (negative vs low), and surgery (breast-conserving vs mastectomy). The primary objective is to compare invasive disease-free survival (IDFS) [Hudis 2007] with adjuvant CT ± 1 year of BEV. Secondary outcome measures are overall survival (OS), breast cancer-free interval, disease-free survival (DFS), distant DFS, and safety (NCI CTCAE v3.0). The sample size was calculated to provide 80% power for a HR=0.75 at α=0.05 assuming 5-year IDFS of 72.0% with CT vs 78.2% with CT + BEV with 388 events. BEATRICE also includes evaluation of potential predictive and prognostic biomarkers. Results: Between Dec 2007 and Mar 2010, 2591 patients were randomized. At data cut-off (Feb 29, 2012), median follow-up was 32 months. The mean CT exposure was balanced between treatment arms. Median BEV duration was 11.7 months. BEV was associated with an increased incidence of grade ≥3 congestive heart failure/left ventricular dysfunction (3% vs <1% with CT), grade ≥3 hypertension (12% vs <1%), and treatment discontinuation (BEV and/or CT: 20% vs 2%) but no increase in the risk of fatal adverse events (0.3% vs 0.2%). No new safety signals were observed. Conclusion: There was no statistically significant improvement in IDFS with the addition of 1 year's BEV to adjuvant CT for triple-negative BC. Further follow-up is required to assess the impact of BEV on OS. The safety profile was consistent with previous reports in metastatic BC with a low incidence of fatal adverse events. Protocol-specified biomarker analyses are ongoing. Updated OS results are expected in 2013. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr S6-5.

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)0.003
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 score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.089
GPT teacher head0.449
Teacher spread0.360 · 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".

Quick stats

Citations11
Published2012
Admission routes1
Has abstractyes

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