A Canadian Study of the Cost-Effectiveness of Apixaban Compared With Enoxaparin for Post-Surgical Venous Thromboembolism Prevention
Bibliographic record
Abstract
BACKGROUND: Occurrence of a venous thromboembolism (VTE) in patients undergoing major orthopedic surgery who are not given thromboprophylactic therapy presents considerable danger to patient medical outcomes and a significant economic burden to the health care system at large. Apixaban is a direct factor Xa inhibitor that has been shown in clinical trial use to safely reduce the composite of VTE and mortality rates in patients undergoing total hip arthroplasty (THA) and total knee arthroplasty (TKA); however, the cost-effectiveness of apixaban treatment in Canadian settings has not been studied. Our study evaluated the cost-effectiveness of apixaban compared with enoxaparin as VTE preventive therapy in patients undergoing elective THA or TKA in Canada. METHODS: An economic model, including both a decision-tree component and a Markov model, was created. The decision tree considered VTE, bleeding, and mortality incidence that occurred in patients within 90 days post-surgery using data from the Apixaban Versus Enoxaparin for Thromboprophylaxis After Knee or Hip Replacement (ADVANCE) trials, which compared apixaban therapy with 30-mg twice daily and 40-mg daily enoxaparin treatment. The Markov model provided the option to simulate events that may occur over the long term, such as recurrent VTE and post-thrombotic syndrome. Outcomes during the short-term phase directly impact the risk of events occurring during the long-term phase (5 years post-surgery). RESULTS: The results of our analysis indicated that apixaban is dominant (ie, more effective and less expensive) than enoxaparin in treating patients undergoing THA and TKA. There were fewer occurrences of VTEs, bleeding events, recurrent VTEs, and post-thrombotic syndrome events in the TKA population with apixaban therapy. Similar results were seen in patients undergoing THA, with the exception of bleeding events, which were more common with apixaban treatment. Savings of $180 to $270 per patient are expected with apixaban treatment compared with enoxaparin treatment, and health outcomes in general are better with apixaban use. Sensitivity analyses yielded consistent results across the THA and TKA populations. CONCLUSION: : This is the first economic evaluation of apixaban use for VTE thromboprophylaxis in the Canadian setting, and our study results show apixaban to be a cost-effective treatment alternative to preventive treatment with enoxaparin.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".