Apixaban and dalteparin in active malignancy associated venous thromboembolism
Bibliographic record
Abstract
Currently, low molecular weight heparin (LMWH) is the guideline endorsed treatment of patients with cancer associated venous thromboembolism (VTE). While apixaban is approved for the treatment of acute VTE, there are limited data supporting its use in cancer patients. The rationale and design of this investigator initiated Phase IV, multicenter, randomized, open label, superiority trial assessing the safety of apixaban versus dalteparin for cancer associated VTE is provided (ADAM-VTE; NCT02585713). The main aim of the ADAM-VTE trial is to test the hypothesis that apixaban is associated with a significantly lower rate of major bleeding compared to dalteparin in the treatment of cancer patients with acute VTE. The primary safety outcome is rate of major bleeding. Secondary efficacy objective is to assess the rates of recurrent VTE or arterial thromboembolism. Cancer patients with acute VTE (n=300) are randomized to receive apixaban (10 mg twice daily for 7 days followed by 5 mg twice daily thereafter) or dalteparin (200 IU/Kg daily for 30 days followed by 150 IU/kg daily thereafter) for 6 months. Stratification factors used for randomization include cancer stage and cancer specific risk of venous thromboembolism using the Khorana score. Participating centers are chosen from the Academic and Community Cancer Research United (ACCRU) consortium comprised of 90 oncology practices in the United States and Canada. Based on the hypothesis to be tested, we anticipate that these trial results will provide evidence supporting apixaban as an effective treatment of cancer associated VTE at lower rates of major bleeding compared to LMWH.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".