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Early Breast Cancer in the Older Woman

2011· review· en· W2152078521 on OpenAlexaff
Sonal Gandhi, Sunil Verma

Bibliographic record

VenueThe Oncologist · 2011
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineBreast cancerTamoxifenContraindicationTrastuzumabCancerOncologyInternal medicineAdjuvantSystemic therapyDiseaseGynecologyAlternative medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Women aged ≥65 are generally underrepresented in early breast cancer studies. Therefore, the optimal management of this group of women remains less certain. METHODS: A literature review of recently published trials, reviews, and practice guidelines outlining the surgical and adjuvant management of early breast cancer in older women was performed. RESULTS: Surgery remains as the cornerstone treatment for early breast cancer in the elderly. Adjuvant radiation is generally considered if the projected lifespan is >5 years. Hormone receptor-positive disease is best treated with adjuvant endocrine treatment; aromatase inhibitors and tamoxifen are both options. Evidence for the use of adjuvant chemotherapy and trastuzumab for high-risk disease in the elderly is more limited. Polychemotherapy is still preferred in fit older women. Certain toxicities from systemic treatments can be more pronounced and should be carefully managed. Treatment with systemic agents should be individualized, with consideration of patient preference, performance status, comorbidities, and projected lifespan. Molecular tumor signatures may help better select patients for treatment in the future. CONCLUSIONS: Age in itself should not be an absolute contraindication to any breast cancer therapy. Comprehensive, multidisciplinary assessment of elderly patients is imperative in evaluating eligibility for beneficial therapies.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score0.659

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.045
GPT teacher head0.353
Teacher spread0.307 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations24
Published2011
Admission routes1
Has abstractyes

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