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Record W4396658533 · doi:10.31128/ajgp-02-23-6709

Safety of vaginal oestrogens for genitourinary symptoms in women with breast cancer

2024· article· en· W4396658533 on OpenAlexaff
Belinda E. Kiely, Rhea Liang, Christina Jang, Karen Magraith

Bibliographic record

VenueAustralian Journal of General Practice · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEstrogen and related hormone effects
Canadian institutionsCascades (Canada)
Fundersnot available
KeywordsGenitourinary systemBreast cancerMedicineGynecologyOestrogen receptorCancerHormoneQuality of life (healthcare)OncologyInternal medicineObstetrics

Abstract

fetched live from OpenAlex

BACKGROUND: Oestrogen deprivation is the mainstay of treatment for women with hormone receptor-positive breast cancer, but unfortunately it causes multiple side effects that can significantly impair quality of life. Genitourinary symptoms are very common and although these symptoms can be effectively managed with vaginal oestrogens, concerns about their safety in women with breast cancer limits their use. OBJECTIVE: The aim of this review is to provide a summary of the data on the safety of vaginal oestrogens in women with breast cancer to help general practitioners advise their patients in this situation. DISCUSSION: Although there are no large randomised prospective studies to assess safety, the current evidence suggests reassurance can be provided to the majority of women with a history of breast cancer considering vaginal oestrogens. Consultation with the oncology team is advised for women taking aromatase inhibitors, where the safety of vaginal oestrogens is less certain.

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)0.003
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.007
GPT teacher head0.289
Teacher spread0.281 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations5
Published2024
Admission routes1
Has abstractyes

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