Osteoporosis therapy and outcomes for postmenopausal patients with hormone receptor–positive breast cancer: NCIC CTG MA.27
Bibliographic record
Abstract
BACKGROUND: Breast cancer patients in the MA.27 trial had similar outcomes with steroidal aromatase inhibitor (AI) exemestane and nonsteroidal anastrozole. AIs increase the risk of osteoporosis. This study examined the effects of self-reported osteoporosis and osteoporosis therapy (OPT) on outcomes. METHODS: The MA.27 phase 3 adjuvant trial enrolled 7576 postmenopausal women. The primary outcome was event-free survival (EFS), and the secondary outcome was distant disease-free survival (DDFS). Patients were permitted bisphosphonates to prevent or treat osteopenia/osteoporosis. In a multivariate, stratified Cox regression, factors were significant with a 2-sided Wald test P value ≤ .05. RESULTS: Osteoporosis was reported at the baseline by 654 of the 7576 women (8.6%) and in total by 1294 patients. Oral OPT was received at the baseline by 815 of the 7576 women (10.8%) and in total by 2711 patients (36%). With a median follow-up of 4.1 years, 693 EFS events (9.15%) and 321 DDFS events (4.2%) occurred. Osteoporosis was not associated with EFS or DDFS. Few EFS events occurred before the initiation of OPT, with no substantive evidence of a time-differing effect on outcomes (nonproportional hazards). OPT (yes vs no) was significantly associated with improved EFS (hazard ratio [HR] for yes vs no, 0.67; 95% confidence interval [CI], 0.57-0.80; P < .001) and DDFS (HR, 0.57; 95% CI, 0.44-0.73; P <. 001). Time-differing (time-dependent) OPT was not (EFS; P = .45). OPT did not alter the incidence of visceral-only metastasis (P = .31). CONCLUSIONS: Oral OPT, administered to postmenopausal breast cancer patients receiving adjuvant AI therapy, was associated with improved EFS and DDFS; the time of OPT initiation (a time-dependent effect) did not affect the outcome. OPT did not alter the risk of visceral metastasis. Cancer 2017;123:2444-51. © 2017 American Cancer Society.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".