Anticoagulation for the prevention of arterial thromboembolism in cancer patients by primary tumour site: a systematic review and meta-analysis of randomized trials
Bibliographic record
Abstract
AIMS: The incidence of arterial thromboembolism (ATE) among ambulatory cancer patients varies by primary tumour site. However, it is unclear whether this alters the benefit-to-harm profile of prophylactic anticoagulation for ATE prevention. Therefore, we systematically evaluated the efficacy and safety of anticoagulants for ATE prevention among ambulatory cancer patients according to the primary tumour site. METHODS AND RESULTS: We conducted a systematic review using Medline, Embase, SCOPUS, and CENTRAL, and included randomized trials comparing prophylactic anticoagulation to no anticoagulation among ambulatory cancer patients who initiated tumour-directed systemic therapy. The incidence of symptomatic ATE (acute ischaemic stroke, acute myocardial infarction, or peripheral artery occlusion) and major bleeding, as well as risk differences (RDs) attributable to anticoagulation, were meta-analysed by primary tumour site using random-effects modelling. We included 10 randomized controlled trials with 9875 patients with follow-up ranging from 3.3 to 68 (median 6.6) months. While prophylactic anticoagulation did not reduce ATE risks overall (RD -0.49%; 95% CI -0.49% to 0.01%; I2 = 0%), it conferred a protective effect among pancreatic cancer patients (RD -3.2%; 95%CI -5.7% to -0.8%; I2 = 0%) without a detectable increase in major bleeding (RD -1.4%; 95% CI -4.6% to 1.8%; I2 = 0%). Prophylactic anticoagulation was not associated with ATE risk reduction in other tumour sites. CONCLUSION: Based on available evidence, prophylactic anticoagulation did not reduce ATE risk among ambulatory cancer patients overall. However, we observed a lower incidence of ATE among pancreatic cancer patients randomized to receive anticoagulation. Prophylactic anticoagulant use to reduce ATEs in pancreatic cancer should be evaluated in future research.
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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 | 0.012 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.034 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 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".