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Record W2324736805 · doi:10.2174/1573394711309010005

Going Beyond Anthracyclines and Taxanes in Breast Cancer What’s Next?

2013· article· en· W2324736805 on OpenAlexaff
Sunil Verma

Bibliographic record

VenueCurrent Cancer Therapy Reviews · 2013
Typearticle
Languageen
FieldMedicine
TopicCancer Treatment and Pharmacology
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsTaxaneTolerabilityCapecitabineAnthracyclineMedicineMetastatic breast cancerBreast cancerOncologyInternal medicineAdjuvantCancerChemotherapyAdverse effectColorectal cancer

Abstract

fetched live from OpenAlex

In recent years, a clear trend has been observed for taxanes to be used earlier in the course of breast cancer, with a large proportion of patients previously treated with anthracyclines and/or taxanes in the (neo)adjuvant setting. In addition, tolerability issues associated with taxane use in elderly patients and patients with substantial comorbidity, means that taxane use is frequently compromised in a substantial proportion of patients with metastatic breast cancer (MBC). Retreatment with taxanes yields variable results, and alternative cytotoxic agents with good activity in patients with anthracycline- and taxane-pretreated MBC are required. Large studies and meta-analyses have helped to establish the role of anthracycline- and taxane-based adjuvant therapy for early breast cancer (EBC). Addition of further cytotoxic agents has generally met with little success, thus the focus has moved towards optimization of adjuvant therapy through scheduling and patient selection. This review considers recent and ongoing developments in the chemotherapeutic management of EBC and MBC. Keywords: Anthracyclines, capecitabine, chemotherapy, early breast cancer, metastatic breast cancer, taxanes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.924
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.118
GPT teacher head0.432
Teacher spread0.314 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2013
Admission routes1
Has abstractyes

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