Competing causes of death in NCIC CTG MA.17, a placebo-controlled trial of letrozole as extended adjuvant therapy for breast cancer patients
Bibliographic record
Abstract
540 Background: Risk of death from other malignancies (OM) and other causes (OC) than breast cancer (BC) increases with age. Effects of baseline factors on type of death were assessed with competing risks analyses. Methods: In NCIC CTG MA.17, 5,187 women free of recurrent breast cancer after 5 years of tamoxifen were randomized to letrozole (L, 2,593 women) or placebo (P, 2,594 women). The primary endpoint was disease free survival (DFS), and secondary, overall survival (OS). Follow-up was to October 9, 2005: median 3.9 years, range <0.1 to 7.0 years. Effects of competing risks were examined for endpoints of BC, OM, and OC for 11 baseline trial factors: treatment, age, menopausal status, duration of prior tamoxifen, adjuvant radiotherapy, bone fracture, osteoporosis, cardiovascular disease, hormone receptor status, nodal status, adjuvant chemotherapy. Lagakos’ hierarchical method (Lagakos, Appl. Statist. 1978; 27:235–241) was used to test for differential effects of baseline factors on type of death (BC, OM, OC). Results: Rate of censoring was 97.8%, with 256 deaths (BC, 102; OM, 50; OC, 100; unknown, 4). Non-breast cancer deaths accounted for 60% of known deaths; 72%, for those ≥70 years; and 48%, for those <70 years. Two baseline factors differentially affected type of death. Women with cardiovascular disease were more likely to die from OC (p=0.02), while those with osteoporosis were more likely to die of OM (p=0.03). Age and nodal status had directionally similar effects. Older women had shorter survival from all 3 causes of death (p=0.01). Lymph node positivity was associated with worse survival (p=0.003). Conclusions: Extended L provides similar proportional benefit in improving DFS for all ages of women (Muss ref abstract SABCS 2006). However, the magnitude of competing non-breast cancer, and non-treatment related, causes of death needs to be considered more frequently, since with early detection and improved therapies, breast cancer patients may increasingly be expected to survive their disease to die from another cause. The novel association between baseline osteoporosis and other malignancies is being explored quantitatively. No significant financial relationships to disclose.
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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 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".