Effects of Celecoxib and Low-dose Aspirin on Outcomes in Adjuvant Aromatase Inhibitor–Treated Patients: CCTG MA.27
Bibliographic record
Abstract
Background: Celecoxib and low-dose aspirin might decrease risk of breast cancer recurrence. Methods: In the Canadian Cancer Trials Group MA.27, postmenopausal hormone receptor-positive breast cancer patients were randomly assigned (2 × 2) to adjuvant exemestane or anastrozole, and celecoxib or placebo. Low-dose aspirin of 81 mg or less was a stratification factor. Due to concerns about cardiac toxicity, celecoxib use was stopped in December 2004, while stratification by aspirin use was removed through protocol amendment. We examined the effects of celecoxib and low-dose aspirin on event-free survival (EFS), defined as time from random assignment to time of locoregional or distant disease recurrence, new primary breast cancer, or death from any cause; distant disease-free survival (DDFS); and overall survival (OS). All statistical tests were two-sided. Results: Random assignment to celecoxib (n = 811, 50.0%) or placebo (n = 811, 50.0%) was discontinued after 18 months (n = 1622). At a median of 4.1 years' follow-up, among 1622 patients, 186 (11.5%) patients had an EFS event: 80 (4.9%) had distant relapse, and 125 (7.7%) died from any cause. Celecoxib did not statistically significantly impact EFS, DDFS, or OS in univariate analysis (respectively, P = .92, P = .55, and P = .56) or multivariable analysis (respectively, P = .74, P = .60, and P = .76). Low-dose aspirin use (aspirin users n = 476, 21.5%; non-aspirin users n = 1733, 78.5%) was associated in univariate analyses with worse EFS (hazard ratio [HR] = 1.48, 95% confidence interval [CI] = 1.12 to 1.96, P = 0.006) and worse OS (HR = 1.87, 95% CI = 1.35 to 2.61, P < .001). After adjusting for baseline characteristics and treatment arm, aspirin use showed no statistical association with EFS (P = .08) and DDFS (P = .82), but was associated with statistically worse OS (HR = 1.67, 95% CI = 1.13 to 2.49, P = .01). Conclusion: Random assignment to short-term (≤18 months) celecoxib as well as use of low-dose aspirin showed no effect on DDFS and EFS in multivariable analysis. Low-dose aspirin increased "all-cause" mortality, presumably because of higher preexisting cardiovascular risks.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".