Assessment of risk of overall and late distant recurrence by Breast Cancer Index in postmenopausal women with early-stage, HR+ breast cancer in the TEAM trial.
Bibliographic record
Abstract
509 Background: Individual risk assessment of distant recurrence (DR) is particularly relevant for early-stage HR+ breast cancer patients, as they face a prolonged risk of recurrence even after adjuvant endocrine therapy. Previously, we have shown that the Breast Cancer Index (BCI) and BCIN+ risk groups are significantly prognostic for risk of overall (0-10y) and late (5-10y) distant recurrence in N0 and N1 breast cancer patients, respectively, enrolled in the Tamoxifen and Exemestane Adjuvant Multinational (TEAM) trial. Here, the prognostic performance of BCI and BCIN+ as a continuous risk score for overall and late distant recurrence was evaluated in the TEAM trial. Methods: BCI testing was performed blinded to clinical outcome with BCI/BCIN+ risk scores calculated as previously described. Cox proportional hazard models adjusted for age, tumor size, grade and treatments were used to estimate hazard ratios (HRs) and the associated 95% confidence intervals (CIs) for BCI/ BCIN+ continuous risk scores. The 10y risk of overall and late DR were estimated as a function of risk scores from the Cox models using Breslow estimates. Results: Continuous risk curves for overall and late DR were obtained in patients who did not receive adjuvant chemotherapy and those who remained DR-free at 5 years regardless of chemotherapy, respectively, to reflect the two key time points for breast cancer treatment decision-making. InN0 patients not treated with chemotherapy (N = 1197), BCI was significantly prognostic for overall DR with a HR of 1.39 (95% CI 1.25-1.54; p < 0.001), while BCIN+ was significantly prognostic in N1 patients who did not receive chemotherapy (N = 1319) with a HR of 4.29 (95% CI 2.93-6.28; p < 0.001). Among patients who remained DR-free at 5 years, in the N0 subset (N = 1285), BCI was significantly prognostic for late DR with a HR of 1.23 (95% CI 1.07-1.42; p < 0.001), while BCIN+ remained to be significantly prognostic in the N1 subset (N = 1762) with a HR of 2.78 (95% CI 1.75-4.43; p < 0.001). Similar results were observed in the HER2- subset for both overall and late DR. Continuous risk curves for BCI and BCIN+ for overall and late DR showed an increasing risk of DR with higher BCI/BCIN+ scores. Conclusions: Results from this largest BCI study to date further support the use of BCI to provide individualized risk estimates for both overall and late DR in women with HR+ breast cancer to aid in personalized decision-making for adjuvant therapy. [Table: see text]
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".