Incidence and Prognostic Impact of Amenorrhea During Adjuvant Therapy in High-Risk Premenopausal Breast Cancer: Analysis of a National Cancer Institute of Canada Clinical Trials Group Study—NCIC CTG MA.5
Bibliographic record
Abstract
PURPOSE: To investigate the therapeutic impact of chemotherapy-induced amenorrhea in premenopausal patients with breast cancer. PATIENTS AND METHODS: We conducted a retrospective cohort study of a National Cancer Institute of Canada Clinical Trials Group phase III trial involving premenopausal patients randomized to receive cyclophosphamide, methotrexate, and fluorouracil (CMF), versus intensive cyclophosphamide, epirubicin, and fluorouracil (CEF). The objectives of our study were to describe the incidence of amenorrhea at 6 and 12 months post-random assignment and to determine the association of amenorrhea with relapse-free and overall survival. RESULTS: Data on 442 patients were used in our analyses. Despite the higher cumulative dose of cyclophosphamide in the CMF treatment arm, at 6 months post-random assignment, the rate of amenorrhea was higher in the CEF group (relative risk, 1.2; 95% CI, 1.0 to 1.3), with no difference at 12 months. In the receptor-positive subgroup, 6-month amenorrhea rates were not associated with prognosis. In contrast, amenorrhea at 12 months was significantly associated with relapse-free survival (hazard ratio, 0.51; 95% CI, 0.32 to 0.82; P = .005) and overall survival (hazard ratio, 0.40; 95% CI, 0.22 to 0.72; P = .002). CONCLUSION: Late chemotherapy-induced amenorrhea seems to be associated with improved outcome in patients with premenopausal, receptor-positive breast cancer.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".