MétaCan
Menu
Back to cohort
Record W4313260748 · doi:10.3390/curroncol30010032

Optimizing Adjuvant Treatment Recommendations for Older Women with Biologically Favorable Breast Cancer: Short-Course Radiation or Long-Course Endocrine Therapy?

2022· review· en· W4313260748 on OpenAlexvenueno aff
Susan G. R. McDuff, Rachel Blitzblau

Bibliographic record

VenueCurrent Oncology · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRandomized controlled trialEndocrine systemRadiation therapyBreast cancerAdjuvantOncologyInternal medicineHormone therapyCancerHormone

Abstract

fetched live from OpenAlex

Omission of radiotherapy among older women taking 5 years of adjuvant endocrine therapy following breast conserving surgery for early-stage, hormone sensitive breast cancers is well-studied. However, endocrine therapy toxicities are significant, and many women have difficulty tolerating endocrine therapy, particularly elderly patients with comorbidities. Omission of endocrine therapy among women receiving adjuvant radiation is less well-studied, but available randomized and non-randomized data suggest that this approach may confer equivalent local control and survival for select patients. Herein we review available randomized and non-randomized outcome data for women treated with radiation monotherapy and emphasize the need for future prospective, randomized studies of endocrine therapy omission.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.144
GPT teacher head0.445
Teacher spread0.300 · 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 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

Citations13
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueCurrent OncologySame topicBreast Cancer Treatment StudiesFrench-language works237,207