Risk of recurrent cancer-associated thrombosis after discontinuation of anticoagulant therapy
Bibliographic record
Abstract
Background: Clinical guidelines suggest continuing anticoagulation therapy for >6 months for patients with active cancer and venous thromboembolism (VTE). However, data regarding the safety of its discontinuation are scarce. Objectives: To valuate the risk factors and the incidence of recurrent VTE 6 months after the discontinuation of anticoagulation therapy in patients with cancer-associated thrombosis (CAT). Methods: We performed a retrospective study on consecutive patients with CAT recruited between 2008 and 2019. The primary and secondary outcomes were recurrent VTE at 6 and 12 months, respectively. Sensitivity analyses were conducted to investigate the possible heterogeneity of these effects. Results: A total of 311 patients were included, among whom 33.4% had metastases and 30.8% were still receiving oncological treatment after 6 months of anticoagulant therapy. At 6 and 12 months, the incidences of recurrent VTE were 6.1% (95% CI, 3.5-9.4%) and 8.7% (95% CI, 5.8-12.4%), respectively. Recurrent VTE was more frequent in patients with metastases at 6 (sub-distribution hazard ratio [SHR] 3.83; 95% CI, 1.54-9.52) and 12 months (SHR 5; 95% CI, 2.2-11.5). Patients with incidental VTE had fewer recurrent events at 6 (SHR 0.3; 95% CI, 0.1-0.8) and 12 months (SHR 0.3; 95% CI, 0.1-0.6) after discontinuing the anticoagulant therapy. Conclusion: The incidence of recurrent VTE at 6 and 12 months following the discontinuation of anticoagulant therapy is higher in patients with CAT. Patients with metastases were at an increased risk of recurrent VTE, whereas patients with incidental VTE were at a lower risk.
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".