When can we stop anticoagulation in patients with cancer-associated thrombosis?
Bibliographic record
Abstract
The optimal duration of anticoagulation in patients with cancer-associated venous thromboembolism (VTE) is unknown. Without well-designed studies evaluating the efficacy, safety and cost-effectiveness of continuing anticoagulant therapy beyond the acute treatment period of 3 to 6 months, evidence-based recommendations are lacking. Consensus guidelines generally suggest continuing anticoagulation in patients with active cancer or receiving cancer treatment, with periodic reassessment of the risks and benefits. Unfortunately, with very little published data on the epidemiology of cancer-associated VTE beyond the initial 6 months, it is not possible for clinicians and patients to weigh risks and benefits in a quantitatively informed manner. Further research is needed to provide reliable and contemporary estimates on the risk of recurrent VTE off anticoagulation, risk of bleeding on anticoagulation, case fatality or all-cause mortality, and other important consequences of living with cancer-associated VTE. This chapter provides an overview of the published literature on real-world data on anticoagulant therapy use, the risks and risk factors of recurrent VTE and bleeding, and patient preference and values regarding long-term anticoagulation. It will conclude with a pragmatic, experience-informed approach for tailoring anticoagulant therapy in patients with cancer-associated VTE.
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 | 0.006 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".