Treatment of Cancer-Associated Thrombosis: Recent Advances, Unmet Needs, and Future Direction
Bibliographic record
Abstract
Cancer-associated thrombosis, with the incidence rising over the years, is associated with significant morbidity and mortality in patients with cancer. Recent advances in the treatment of cancer-associated venous thromboembolism (VTE) include the introduction of direct oral anticoagulants (DOACs), which provide a more convenient and effective option than low-molecular-weight heparin (LMWH). Nonetheless, important unmet needs remain including an increased risk of bleeding in certain patient subgroups such as those with gastroesophageal cancer, concerns about drug-drug interactions, and management of patients with severe renal impairment. Although DOACs are more convenient than LMWH, persistence can decline over time. Factor XI inhibitors have potential safety advantages over DOACs because factor XI appears to be essential for thrombosis but not hemostasis. In phase II trials, some factor XI inhibitors were superior to enoxaparin for the prevention of VTE after knee replacement surgery without increasing the risk of bleeding. Ongoing trials are assessing the efficacy and safety of factor XI inhibitors for the treatment of cancer-associated VTE.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".