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Record W2082216032 · doi:10.3747/co.20.1543

Comparison of Recurrence and Survival Rates after Breast-Conserving Therapy and Mastectomy in Young Women with Breast Cancer

2013· review· en· W2082216032 on OpenAlexaffvenue
Jeffrey Cao, Robert Olson, Scott Tyldesley

Bibliographic record

VenueCurrent Oncology · 2013
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsUniversity of British ColumbiaBC Cancer Agency
Fundersnot available
KeywordsMedicineMastectomyBreast cancerRadiation therapyOncologyBreast-conserving surgeryInterim analysisInterimStage (stratigraphy)Randomized controlled trialCancerInternal medicine

Abstract

fetched live from OpenAlex

Multiple randomized trials have demonstrated that breast-conserving therapy with partial mastectomy and radiotherapy provides survival equivalent to that seen with mastectomy for patients with early-stage breast cancer. Breast-conserving therapy has been associated with better quality of life relative to mastectomy and has become the standard of care for patients with early-stage breast cancer. Young age has been identified as a risk factor for recurrence and death from breast cancer. Some studies have suggested that young women (less than 35 or 40 years of age) have inferior outcomes with breast-conserving therapy, implying that such women may be better served by mastectomy. On review of the available literature, there is no definitive evidence that mastectomy provides a consistent, unequivocal recurrence-free or overall survival benefit over breast-conserving therapy. However, available meta-analyses have not compared outcomes in young women specifically, and such analyses should be performed. In the interim, breast-conserving therapy is not contraindicated in young women (less than 40 years of age) and can be used cautiously; however, such women should be advised of the lack of unequivocal data proving that survival is equivalent to that with mastectomy in their age group.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.752
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.092
GPT teacher head0.418
Teacher spread0.326 · 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 designOther design
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

Citations69
Published2013
Admission routes2
Has abstractyes

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