Rivaroxaban versus aspirin for secondary prevention of ischaemic stroke in patients with cancer: a subgroup analysis of the NAVIGATE ESUS randomized trial
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Cancer is a frequent finding in ischaemic stroke patients. The frequency of cancer amongst participants in the NAVIGATE ESUS randomized trial and the distribution of outcome events during treatment with aspirin and rivaroxaban were investigated. METHODS: Trial participation required a recent embolic stroke of undetermined source. Patients' history of cancer was recorded at the time of study entry. During a mean follow-up of 11 months, the effects of aspirin and rivaroxaban treatment on recurrent ischaemic stroke, major bleeding and all-cause mortality were compared between patients with cancer and patients without cancer. RESULTS: Amongst 7213 randomized patients, 543 (7.5%) had cancer. Of all patients, 3609 were randomized to rivaroxaban [254 (7.0%) with cancer] and 3604 patients to aspirin [289 (8.0%) with cancer]. The annual rate of recurrent ischaemic stroke was 4.5% in non-cancer patients in the rivaroxaban arm and 4.6% in the aspirin arm [hazard ratio (HR) 0.98, 95% confidence interval (CI) 0.78-1.24]. In cancer patients, the rate of recurrent ischaemic stroke was 7.7% in the rivaroxaban arm and 5.4% in the aspirin arm (HR 1.43, 95% CI 0.71-2.87). Amongst cancer patients, the annual rate of major bleeds was non-significantly higher for rivaroxaban than aspirin (2.9% vs. 1.1%; HR 2.57, 95% CI 0.67-9.96; P for interaction 0.95). All-cause mortality was similar in both groups. CONCLUSIONS: Our exploratory analyses show that patients with embolic stroke of undetermined source and a history of cancer had similar rates of recurrent ischaemic strokes and all-cause mortality during aspirin and rivaroxaban treatments and that aspirin appeared safer than rivaroxaban in cancer patients regarding major bleeds. www.clinicaltrials.gov (NCT02313909).
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.010 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".