What's new in the prevention and treatment of cancer-associated thrombosis?
Bibliographic record
Abstract
Venous thromboembolism (VTE) is a common complication in ambulatory cancer patients receiving chemotherapy. Current clinical guidelines recommend against the use of routine primary thromboprophylaxis in unselected ambulatory cancer patients. The Khorana score is a risk assessment tool derived and prospectively validated for the identification of cancer patients at high risk of thrombotic complications. Recently, 2 randomized, controlled trials have assessed the use of low-dose direct oral Xa inhibitors, apixaban and rivaroxaban, for the prevention of cancer-associated thrombosis in ambulatory patients at intermediate to high risk of VTE (Khorana score ≥2). Taken together, these trials have shown that low-dose direct oral Xa inhibitors reduce the risk of VTE in this patient population without a significant increase in major bleeding. These results should encourage clinicians to consider the use of primary thromboprophylaxis in ambulatory cancer patients at intermediate to high risk of VTE who do not have any apparent risk factors for bleeding. The direct oral Xa inhibitors have also been assessed in the acute management of cancer-associated thrombosis. Current evidence suggests that these drugs are a convenient, effective, and safe option for the management of acute VTE in many cancer patients. Low-molecular weight heparin, however, may continue to be the treatment of choice depending on the presence of bleeding risk factors, the type of cancer, drug-drug interactions, and patient preferences.
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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".