Risk of recurrent venous thromboembolism according to malignancy characteristics in patients with cancer-associated thrombosis: a systematic review of observational and intervention studies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Patients with cancer-associated venous thromboembolism (VTE) should be treated with low molecular weight heparin. The ideal duration of anticoagulation in this population is unknown. It is important to evaluate whether there is variation in susceptibility for recurrent VTE according to malignancy characteristics. In this systematic review we sought to evaluate cancer characteristics that may influence the risk for VTE recurrence and the success of anticoagulation in patients with cancer-associated VTE. A systematic literature search strategy identified potential studies on MEDLINE, Embase, the Cochrane Register of Controlled Trials, MEDLINE In-Process and other nonindexed citations using the Ovid interface. There was no restriction to study design or language. No randomized controlled trials fulfilled our inclusion criteria. We included four retrospective and six prospective studies. VTE recurrence rate according to tumour stage suggested an increased risk for patients with metastatic malignancy compared with patients with localized disease (relative risk 1.36; 95% confidence interval 1.06-1.74, P = 0.01). We were unable to pool data to evaluate VTE recurrence according to tumour site and histology. The isolated evaluation of the included studies suggested that younger patients with adenocarcinoma, lung or gastrointestinal malignancy have the highest risk. There is paucity of data regarding detailed malignancy characteristics in patients with cancer-associated VTE. It appears that metastatic malignancy, or adenocarcinoma, or lung malignancy confers a higher risk of VTE recurrence than patients with localized malignancy, nonadenocarcinoma or breast cancer.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it