Adjuvant Endocrine Therapy in Premenopausal Breast Cancer: 12-Year Results From SOFT
Bibliographic record
Abstract
Clinical trials frequently include multiple end points that mature at different times. The initial report, typically based on the primary end point, may be published when key planned co-primary or secondary analyses are not yet available. Clinical Trial Updates provide an opportunity to disseminate additional results from studies, published in JCO or elsewhere, for which the primary end point has already been reported. The Suppression of Ovarian Function Trial (SOFT; ClinicalTrials.gov identifier: NCT00066690 ) randomly assigned premenopausal women with hormone receptor–positive breast cancer to 5 years of adjuvant tamoxifen, tamoxifen plus ovarian function suppression (OFS), or exemestane plus OFS. The primary analysis compared disease-free survival (DFS) between tamoxifen plus OFS versus tamoxifen alone; exemestane plus OFS versus tamoxifen was a secondary objective. After 8 years, SOFT reported a significant reduction in recurrence and improved overall survival (OS) with adjuvant tamoxifen plus OFS versus tamoxifen alone. Here, we report outcomes after median follow-up of 12 years. DFS remained significantly improved with tamoxifen plus OFS versus tamoxifen (hazard ratio, 0.82; 95% CI, 0.69 to 0.98) with a 12-year DFS of 71.9% with tamoxifen, 76.1% with tamoxifen plus OFS, and 79.0% with exemestane plus OFS. OS was improved with tamoxifen plus OFS versus tamoxifen (hazard ratio, 0.78; 95% CI, 0.60 to 1.01) and was 86.8% with tamoxifen, 89.0% with tamoxifen plus OFS, and 89.4% with exemestane plus OFS at 12 years. Among those who received prior chemotherapy for human epidermal growth factor receptor-2–negative tumors, OS was 78.8% with tamoxifen, 81.1% with tamoxifen plus OFS, and 84.4% with exemestane plus OFS. In conclusion, after 12 years, there remains a benefit from including OFS in adjuvant endocrine therapy, with an absolute improvement in OS more apparent with higher baseline risk of recurrence. [Media: 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 | 0.017 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".