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Anthracyclines in Early-Stage Breast Cancer: Is It the End of an Era?

2009· review· en· W2116280772 on OpenAlexaff
Danny Robson, Sunil Verma

Bibliographic record

VenueThe Oncologist · 2009
Typereview
Languageen
FieldMedicine
TopicCancer Treatment and Pharmacology
Canadian institutionsSunnybrook Health Science Centre
FundersSanofiAstraZenecaPfizer
KeywordsAnthracyclineMedicineBreast cancerOncologyInternal medicineAdjuvantStage (stratigraphy)TopoisomeraseCancerChemotherapyTrastuzumab

Abstract

fetched live from OpenAlex

Anthracycline regimens have been the mainstay of adjuvant care in breast cancer for >20 years. A growing body of clinical experience has uncovered an unacceptable rate of significant cardiac and leukomogenic toxicities. A systematic review of the literature was performed highlighting anthracycline- and nonanthracycline-based adjuvant regimens. The published data suggest that nonanthracycline alternatives are less toxic than anthracycline-containing regimens and equally, if not more, efficacious. Molecular predictors, such as human epidermal growth factor receptor 2 and topoisomerase II alpha, are further refining the optimal role of anthracyclines. With these new advances, the current role of anthracycline-based chemotherapy in early-stage breast cancer demands re-examination.

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 score0.988
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.117
GPT teacher head0.482
Teacher spread0.365 · 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

Citations20
Published2009
Admission routes1
Has abstractyes

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