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Record W4317933043 · doi:10.3390/cancers15030711

Long-Term Non-Cancer Risks in People with BRCA Mutations following Risk-Reducing Bilateral Salpingo-Oophorectomy and the Role of Hormone Replacement Therapy: A Review

2023· review· en· W4317933043 on OpenAlexafffund
Amanda Nitschke, Helena Abreu do Valle, Lesa Dawson, Janice S. Kwon, Gillian E. Hanley

Bibliographic record

VenueCancers · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsMedicineOophorectomyHormone replacement therapy (female-to-male)Hormone replacementCancerOncologyBRCA mutationGynecologyHormoneBioinformaticsOvarian cancerInternal medicineSurgeryHysterectomyBiology

Abstract

fetched live from OpenAlex

Risk-reducing bilateral salpingo-oophorectomy (RRBSO) is the gold standard preventative option for BRCA mutation carriers at high risk for ovarian and breast cancer. However, when performed at the recommended ages of 35–45 years, RRBSO induces immediate premature surgical menopause, along with the accompanying adverse psychosocial, cardiovascular, bone, and cognitive health consequences. While these health consequences have been thoroughly studied in the general population, little is known about the long-term health outcomes in the BRCA population. Hormone replacement therapy (HRT) until the average age of natural menopause can help mitigate these health risks, yet the initiation of HRT is a complex decision among BRCA carriers due to concern of increasing the already high risk of breast cancer in these people. This review summarizes the current research on long-term non-cancer risks in BRCA carriers following RRBSO-induced premature surgical menopause, and highlights the existing evidence in support of HRT use in this population.

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)0.002
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.028
GPT teacher head0.344
Teacher spread0.317 · 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

Citations14
Published2023
Admission routes2
Has abstractyes

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