Adjuvant ovarian function suppression and cognitive function in women with breast cancer
Bibliographic record
Abstract
BACKGROUND: To examine the effect on cognitive function of adjuvant ovarian function suppression (OFS) for breast cancer. METHODS: The Suppression of Ovarian Function (SOFT) trial randomised premenopausal women with hormone receptor-positive breast cancer to 5 years adjuvant endocrine therapy with tamoxifen+OFS, exemestane+OFS or tamoxifen alone. The Co-SOFT substudy assessed objective cognitive function and patient reported outcomes at randomisation (T0), and 1 year later (T1); the primary endpoint was change in global cognitive function, measured by the composite objective cognitive function score. Data were compared for the pooled tamoxifen+OFS and exemestane+OFS groups vs the tamoxifen alone group using the Wilcoxon rank-sum test. RESULTS: Of 86 participants, 74 underwent both T0 and T1 cognitive testing; 54 randomised to OFS+ either tamoxifen (28) or exemestane (26) and 20 randomised to tamoxifen alone. There was no significant difference in the changes in the composite cognitive function scores between the OFS+ tamoxifen or exemestane groups and the tamoxifen group (mean±s.d., -0.21±0.92 vs -0.04±0.49, respectively, P=0.71, effect size=-0.20), regardless of prior chemotherapy status, and adjusting for baseline characteristics. CONCLUSIONS: The Co-SOFT study, although limited by small samples size, provides no evidence that adding OFS to adjuvant oral endocrine therapy substantially affects global cognitive function.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".