Abstract P2-11-02: Breast Cancer Index predicts benefit from extended endocrine therapy in HR+ breast cancer
Bibliographic record
Abstract
Abstract Background: Optimizing the duration of adjuvant endocrine therapy in patients diagnosed with early stage hormone receptor-positive (HR+) breast cancer requires improved approaches to individualize disease profile and to reduce any unnecessary treatment burden for patients. Current clinical practice guidelines recommend 10 years of adjuvant endocrine therapy for most patients unless there are characteristics of low risk disease. However, approximately 2/3rds of patients have favorable long-term outcomes after completing 5 years of adjuvant therapy. Therefore, consideration of the risk-benefit profile for each patient is critical to identify who may be spared extended endocrine therapy (EET) and its associated toxicities, and which patients will benefit from an additional 5 years of endocrine therapy. The Breast Cancer Index (BCI) is a gene expression-based signature that stratifies patients based on the risk of overall (0-10y) and late (post-5y) distant recurrence (DR) and predicted the likelihood of benefit from extended endocrine therapy in MA.17. The translational-aTTom (Trans-aTTom) study is a multi-institutional, prospective-retrospective study to validate the predictive ability of BCI by HOXB13/IL17BR (H/I) status for EET benefit in early stage HR+, N0 and N+ breast cancer. Methods: Patients treated in the aTTom (Adjuvant Tamoxifen - To Offer More?) trial with available primary tumor tissue were eligible. Biospecimens were retrospectively collected from aTTom study sites and centrally assessed for ER, PR and HER2 status. Median follow-up was 12.6 years. Primary and secondary endpoints were recurrence-free interval (RFI) and disease-free interval (DFI), respectively. Statistical significance level was set at 0.0336 as per statistical analysis plan. Weighted Kaplan-Meier and Cox proportional hazards regression analysis with time-varying coefficients were used to test the predictive activity of BCI by HOXB13/IL17BR (H/I) status (High vs Low). Likelihood ratio test based on Cox regression was used to evaluate treatment by biomarker interaction. Results: Archived tumor specimens from 3328 patients were collected across 62 aTTom trial sites, representing 48% of the parent trial population. Central testing and assessment of ER, PR, HER2, and BCI resulted in 2445 HR+ patients (1367 N0, 789 N+, 289 nodal status unknown) in the overall cohort. At final analysis, the study remained underpowered for evaluating BCI predictive performance in the overall cohort due to an observed limited effect size that was smaller than planned and did not recapitulate the parent aTTom trial. However, evaluation of BCI predictive performance in the updated N+ subset (N=789) showed that patients classified as BCI(H/I)-High (N=404, 51%) experienced a statistically significant benefit from 10y vs 5y of tamoxifen (9.7% RFI: HR=0.33 [95% CI 0.14-0.75]; P=0.016), whereas those classified as BCI(H/I)-Low showed no significant benefit (-1.2% RFI; HR=1.11 [95% CI 0.76-1.64]; P=0.58). A statistically significant interaction between continuous BCI(H/I) and treatment was demonstrated (P = 0.036) adjusted for age, tumor size and grade, whereas no significant interaction was observed between treatment and quantitative ER (P=0.939) or PR (P=0.138) expression. Conclusion: BCI by high H/I expression was predictive of endocrine response and identified a subset of HR+, N+ patients with significant benefit from 10 vs. 5 years of tamoxifen therapy. These data provide further validation, consistent with previous MA.17 data, for BCI as a predictive biomarker of benefit from extended endocrine therapy. Findings from the Trans-aTTom strengthen the clinical validity of BCI for prediction of endocrine response and its clinical utility in optimizing duration of endocrine therapy. Citation Format: John Bartlett, Dennis Sgori, Kai Treuner, Yi Zhang, Tammy Piper, Ranelle Shalunga, Ikhlaaq Ahmed, Lucy Doos, Sarah Thornber, Elena Brachtel, Sarah Pirrie, Catherine Schnabel, Daniel Rea. Breast Cancer Index predicts benefit from extended endocrine therapy in HR+ breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P2-11-02.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".