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Menopausal hormone therapy after a diagnosis of breast cancer in women with a <i>BRCA</i> pathogenic variant and risk of death.

2025· article· en· W4410820468 on OpenAlexafffund
Joanne Kotsopoulos, Marta Seca, Jan Lubiński, Jacek Gronwald, Andrea Eisen, Raymond Kim, Christian F. Singer, Robert Fruscio, Ping Sun, Steven A. Narod

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNutrition, Genetics, and Disease
Canadian institutionsPrincess Margaret Cancer CentreHealth Sciences CentreSunnybrook Health Science CentreWomen's College Hospital
FundersBreast Cancer Society of Canada
KeywordsMedicineBreast cancerHormone therapyOncologyGynecologyInternal medicineMenopauseCancer

Abstract

fetched live from OpenAlex

10506 Background: Use of menopausal hormone therapy (MHT) is contraindicated for women with a personal history of breast cancer. This topic is of importance among women with a pathogenic or likely pathogenic variant (mutation) in BRCA1 or BRCA2 given their tendency to develop early onset disease as well as the recommendation to undergo oophorectomy prior to natural menopause. Methods: We conducted a prospective analysis of MHT use following breast cancer in BRCA carriers and the risk of death. The study included BRCA carriers with a diagnosis of breast cancer, no history of another cancer, no prior MHT use, and who were enrolled in a longitudinal study. Women who initiated MHT after their diagnosis were matched to women who did not use MHT on year of birth, age of diagnosis, and treatments received – resulting in 183 matched pairs. We followed women from the date of first MHT use in the exposed and the matched date in the unexposed. Cox proportional hazards was used to estimate the hazard ratio (HR) and 95% confidence intervals (CI) for the risk of death associated with MHT use. Results: Among the 183 MHT users, 53 (29%) used a local MHT and 130 (71%) used a systemic MHT. After 6.0 years of follow-up (range 0.01-22.7); there were 9 (4.9%) deaths in the MHT group vs. 22 deaths (12%) in the no MHT group ( P = 0.01). The corresponding number of breast cancer deaths were 6 (3.3%) vs. 16 (8.7%) ( P = 0.03). The HR for all-cause mortality was 0.31 (95%CI 0.14-0.69; P = 0.004) and for breast cancer-specific mortality was 0.27 (95%CI 0.10-0.70; P = 0.007). The corresponding risk estimates for all-cause death by invasiveness were 0.25 (95%CI 0.11-0.61; P = 0.002) and 0.54 (95%CI 0.07-4.02; P = 0.54) for invasive disease and DCIS, respectively. All-cause mortality with use of systemic MHT was 0.27 (95%CI 0.11-0.67; P = 0.005) and was 0.19 (95%CI 0.03-1.45; P = 0.11) for local MHT. Compared to never HRT use, the HR for E-alone was 0.35 (0.12-1.02; P = 0.05) and was 0.58 (95%CI 0.08-4.29; P = 0.59) for E+P. Subgroup analyses by formulation, gene mutation and tumour pathology are on-going. Conclusions: Although based on small strata, the preliminary findings are suggestive of no increased risk of death with MHT use after BRCA -breast cancer and may offer an opportunity to improve quality of life in this unique population. Replication in larger datasets are needed.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.343
Teacher spread0.327 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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