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Assessment of ovarian function suppression (OFS)-containing adjuvant endocrine therapy in premenopausal women by Breast Cancer Index.

2025· article· en· W4410808924 on OpenAlexaff
Ruth O’Regan, Yue Ren, Yi Zhang, Natalia Siuliukina, Catherine A. Schnabel, Roswitha Kammler, G. Viale, Patrizia Dell’Orto, Olivia Pagani, Barbara Walley, Gini F. Fleming, Prudence A. Francis, Sherene Loi, Marco Colleoni, Kai Treuner, Meredith M. Regan

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNutrition, Genetics, and Disease
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineEndocrine systemBreast cancerOncologyGynecologyAdjuvantInternal medicineCancerHormone

Abstract

fetched live from OpenAlex

557 Background: Breast Cancer Index (BCI) previously identified that premenopausal patients with HOXB13/IL17BR ratio (H/I)-Low tumors derived greater benefit than BCI(H/I)-High tumors from OFS-containing adjuvant endocrine therapy vs tamoxifen alone in the Suppression of Ovarian Function Trial (SOFT). This translational study of the Tamoxifen and Exemestane Trial (TEXT) was conducted to assess the predictive benefit of BCI (H/I) from exemestane (E) plus OFS over tamoxifen (T) plus OFS and validate the prognostic performance of BCI. Methods: Blinded BCI testing was performed in all available tumor samples from patients enrolled in TEXT, of which 1782 of 2660 had BCI successfully assessed and BCI categories assigned per established clinical cutpoints. Primary endpoints were breast cancer–free interval (BCFI) for predictive and distant recurrence–free interval (DRFI) for prognostic analyses. Per pre-specified SAP, a secondary analysis of predictive benefit combined the two OFS arms common to TEXT and SOFT (2896 of 4690 patients); clinicopathologic subgroup analyses were conducted in the combined TEXT+SOFT cohort. Cox proportional hazards models, stratified by chemotherapy use and nodal status, that included treatment assignment, BCI(H/I) status, and interaction term were used to assess BCI predictive performance by testing for treatment-by-BCI(H/I) interaction. The median follow-up was 13 years. Results: Among TEXT patients, 58% had BCI(H/I)-Low tumors.Patients with BCI (H/I)-Low tumors exhibited a 6.6% absolute benefit in 12-year BCFI (HR=0.61 [95% CI, 0.44-0.85]) for E+OFS versus T+OFS while those with BCI(H/I)-High tumors had an 6.3% absolute benefit (HR=0.78 [95% CI, 0.57-1.07]) (P-interaction = 0.29). Results were consistent in the combined TEXT+SOFT cohort and adjusting for clinicopathological variables. Clinical subgroup analyses consistently showed benefit of E+OFS vs T+OFS for BCI(H/I)-Low tumors, and more variable relative treatment effects among BCI(H/I)-High tumors, including by age. Post-hoc exploratory time-varying estimates suggested the treatment-by-BCI relationships may differ in years 0-5 vs >5 years. BCI and BCIN+ as continuous indices were prognostic for distant recurrence in N0 (P = 0.0004) and N1 (P < 0.0001) cancers. The 12-year DRFI was 96.3%, 90.3% and 84.9% for BCI-low, intermediate and high-risk N0 cancers, respectively. Conclusions: BCI was confirmed as prognostic in premenopausal women with HR+ early breast cancer enrolled in TEXT. BCI(H/I) status did not clearly predict differential benefit from E+OFS vs T+OFS. The TEXT results complement the prior results from SOFT, indicating premenopausal patients with BCI(H/I)-Low tumors benefit from more intensive endocrine therapy .

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)0.003
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 score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.028
GPT teacher head0.424
Teacher spread0.396 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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