Cancer‐Associated ThrOmboSIs – Patient‐Reported OutcoMes With RivarOxaban (COSIMO) – Baseline characteristics and clinical outcomes
Bibliographic record
Abstract
BACKGROUND: Patients with cancer-associated thrombosis (CAT) have a high risk of recurrent venous thromboembolic events, which contribute to significant morbidity and mortality. Direct oral anticoagulants may provide a convenient treatment option for these patients. OBJECTIVES: To assess clinical characteristics and outcomes of patients with active cancer changing to rivaroxaban after ≥4 weeks of standard therapy for the treatment of venous thromboembolism (VTE) in clinical practice. This analysis focused on secondary outcomes of Cancer-associated thrOmboSIs - Patient-reported outcoMes with rivarOxaban (COSIMO). PATIENTS: COSIMO was a multinational, prospective, noninterventional, single-arm cohort study. Overall, 505 patients received at least one dose of rivaroxaban; 96.6% changing from low-molecular-weight heparin, 1.6% from a vitamin K antagonist, and 1.8% from fondaparinux. RESULTS: Most patients had solid tumors (n = 449; 88.9%) and approximately half of these patients had metastases. The qualifying venous thromboembolic event was deep vein thrombosis (DVT) in 45.3% of patients, pulmonary embolism (PE) in 37.2% of patients, DVT with PE in 9.7% of patients, and catheter-associated DVT in 7.5% of patients. Approximately 75.1% of patients received rivaroxaban for at least 3 months; 150 (29.7%) patients received concomitant chemotherapy during the study. VTE recurrence, major bleeding, nonmajor bleeding, and major adverse cardiovascular events occurred in 18 (3.6%), 18 (3.6%), 81 (16.0%), and 12 (2.4%) patients, respectively. CONCLUSIONS: In patients with CAT who changed to rivaroxaban treatment after ≥4 weeks of standard therapy, the observed incidence proportions of recurrent VTE and bleeding events were in keeping with the recognized effectiveness and safety profile of rivaroxaban for the treatment of CAT.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 | 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".