Cost-effectiveness of rivaroxaban compared with enoxaparin plus a vitamin K antagonist for the treatment of venous thromboembolism
Bibliographic record
Abstract
BACKGROUND: Venous thromboembolism (VTE), comprised of deep vein thrombosis (DVT) and pulmonary embolism (PE), is commonly treated with a low-molecular-weight heparin such as enoxaparin plus a vitamin K antagonist (VKA) to prevent recurrence. Administration of enoxaparin + VKA is hampered by complexities of laboratory monitoring and frequent dose adjustments. Rivaroxaban, an orally administered anticoagulant, has been compared with enoxaparin + VKA in the EINSTEIN trials. The objective was to evaluate the cost-effectiveness of rivaroxaban compared with enoxaparin + VKA as anticoagulation treatment for acute, symptomatic, objectively-confirmed DVT or PE. METHODS: A Markov model was built to evaluate the costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios associated with rivaroxaban compared to enoxaparin + VKA in adult patients treated for acute DVT or PE. All patients entered the model in the 'on-treatment' state upon commencement of oral rivaroxaban or enoxaparin + VKA for 3, 6, or 12 months. Transition probabilities were obtained from the EINSTEIN trials during treatment and published literature after treatment. A 3-month cycle length, US payer perspective ($2012), 5-year time horizon and a 3% annual discount rate were used. RESULTS: Treatment with rivaroxaban cost $2,448 per-patient less and was associated with 0.0058 more QALYs compared with enoxaparin + VKA, making it a dominant economic strategy. Upon one-way sensitivity analysis, the model's results were sensitive to the reduction in index VTE hospitalization length-of-stay associated with rivaroxaban compared with enoxaparin + VKA. At a willingness-to-pay threshold of $50,000/QALY, probabilistic sensitivity analysis showed rivaroxaban to be cost-effective compared with enoxaparin + VKA approximately 76% of the time. LIMITATIONS: The model did not account for the benefits associated with an oral and minimally invasive administration of rivaroxaban. 'Real-world' applicability is limited because data from the EINSTEIN trials were used in the model. Also, resource utilization and costs were based on the US healthcare system. CONCLUSION: Rivaroxaban is a cost-effective option for anticoagulation treatment of acute VTE patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".