The incidence and risk of venous thromboembolism in patients with active malignancy and isolated superficial venous thrombosis: a systematic review and meta-analysis (the IROVAM–iSVT review)
Bibliographic record
Abstract
Background The management of cancer-associated isolated superficial venous thrombosis (iSVT) remains controversial as cancer patients are at higher risk of bleeding and venous thromboembolism (VTE). Objectives We performed a systematic review and meta-analysis to determine the incidence and risk of VTE in patients with iSVT and active malignancy. Methods Medline, Embase, Web of Science, and the Cochrane Library were searched from inception to December 2, 2024, to identify studies investigating VTE rates in adult patients with iSVT and active malignancy. The incidence of VTE in patients with active malignancy and iSVT was pooled by meta-analysis and compared to patients with iSVT without active malignancy. Secondary outcomes included the incidence of major bleeding, clinically relevant nonmajor bleeding, hospitalization, and all-cause death. Results Eight full-text studies were included, comprising 5998 iSVT patients and 448 with active malignancy. Patients with cancer-associated iSVT had an overall incidence of VTE of 18.2 events per 100 patient years (95% CI, 5.2-31.2; I 2 = 76%) and a higher rate of VTE compared to patients with iSVT without active malignancy (risk ratio, 2.57; 95% CI, 1.78-3.71; I 2 = 0%; P < .001). There were 2 major bleeding events per 100 patient years (95% CI, 0-6.7; I 2 = 59%) and 22.8 deaths per 100 patient years (95% CI, 0-58.7; I 2 = 73%) for cancer-associated iSVT. Only 1 study reported on clinically relevant nonmajor bleeding and hospitalization rates, respectively. Conclusion Patients with iSVT and active malignancy have high rates of VTE despite treatment. Future studies should investigate the role of extended duration anticoagulation on VTE rates in this population.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.024 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".