Direct oral anticoagulants for cancer-associated venous thromboembolism: a systematic review and meta-analysis
Bibliographic record
Abstract
Direct oral anticoagulants (DOACs) are an emerging treatment option for patients with cancer and acute venous thromboembolism (VTE), but studies have reported inconsistent results. This systematic review and meta-analysis compared the efficacy and safety of DOACs and low-molecular-weight heparins (LMWHs) in these patients. MEDLINE, Embase, the Cochrane Central Register of Controlled Trials, and conference proceedings were searched to identify relevant randomized controlled trials. Additional data were obtained from the original authors to homogenize definitions for all study outcomes. The primary efficacy and safety outcomes were recurrent VTE and major bleeding, respectively. Other outcomes included the composite of recurrent VTE and major bleeding, clinically relevant nonmajor bleeding (CRNMB), and all-cause mortality. Summary relative risks (RRs) were calculated in a random effects meta-analysis. In the primary analysis comprising 2607 patients, the risk of recurrent VTE was nonsignificantly lower with DOACs than with LMWHs (RR, 0.68; 95% CI, 0.39-1.17). Conversely, the risks of major bleeding (RR, 1.36; 95% CI, 0.55-3.35) and CRNMB (RR, 1.63; 95% CI, 0.73-3.64) were nonsignificantly higher. The risk of the composite of recurrent VTE or major bleeding was nonsignificantly lower with DOACs than with LMWHs (RR, 0.86; 95% CI, 0.60-1.23). Mortality was comparable in both groups (RR, 0.96; 95% CI, 0.68-1.36). Findings were consistent during the on-treatment period and in those with incidental VTE. In conclusion, DOACs are an effective treatment option for patients with cancer and acute VTE, although caution is needed in patients at high risk of bleeding.
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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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.045 |
| Bibliometrics | 0.006 | 0.007 |
| 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".