Idraparinux versus standard therapy in the treatment of deep venous thrombosis in cancer patients: A subgroup analysis of the Van Gogh DVT trial
Bibliographic record
Abstract
Standard treatment with heparin followed by vitamin K antagonists is frequently complicated by bleeding and recurrent venous thromboembolism (VTE) in cancer patients with VTE. To compare the efficacy, safety and overall survival of long-term idraparinux treatment to standard therapy in cancer patients we conducted a post-hoc analysis in the subgroup of non-active and active cancer patients included in the Van Gogh DVT clinical trial. The cancer patients with deep venous thrombosis (DVT) and without pulmonary embolism (PE) were randomised to standard treatment or a once-weekly subcutaneous injection of idraparinux (2.5 mg), a synthetic pentasaccharide. 421 cancer patients were included. A total of 220 patients received idraparinux and 201 were allocated to standard therapy for three months (8%) or six months (92%). A recurrent VTE was observed during the first six months in 2.5% (n=5) of the idraparinux recipients compared to 6.4% (n=12) in the standard therapy group (hazard ratio 0.39, 95% confidence interval [CI]; 0.14-1.11). The rate of bleeding was comparable (odds ratio 0.89, 95% CI; 0.50-1.59). The outcomes were similar at three months after randomisation in all patients. Of the idraparinux recipients, 22.7% (n=50) died during the study period compared to 48 patients (23.9%) in the standard treatment group (hazard ratio 0.99, 95% CI; 0.66-1.48). In conclusion, no significant safety or survival differences were observed between cancer patients with DVT treated with idraparinux for six months compared to standard therapy. Fewer recurrent VTEs were observed in the idraparinux group; however, this was not statistically significant and also because of study limitations this should be interpreted with caution.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.011 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".