Economic Analysis Comparing Dalteparin to Vitamin K Antagonists to Prevent Recurrent Venous Thromboembolism in Patients With Cancer Having Renal Impairment
Bibliographic record
Abstract
BACKGROUND: In a randomized trial (ie, Comparison of Low-Molecular-Weight Heparin versus Oral Anticoagulant Therapy for the Prevention of Recurrent Venous Thromboembolism in Patients with Cancer [CLOT]) that evaluated secondary prophylaxis of recurrent venous thromboembolism (VTE) in patients with cancer, dalteparin reduced the relative risk by 52% compared to oral vitamin K antagonists (VKAs; hazard ratio = 0.48, P = .002). A recent subgroup analysis in patients with moderate to severe renal impairment also revealed lower absolute VTE rates with dalteparin (3% vs 17%; P = .011). To measure the economic value of dalteparin in these populations, a pharmacoeconomic analysis was conducted from the Dutch health-care system perspective. METHODS: Resource utilization data contained within the CLOT trial database were extracted and converted into direct cost estimates. Univariate analysis was then conducted to compare the total cost of therapy between patients randomized to dalteparin or VKA therapy. Health state utilities were then measured in 24 members of the general public using the time trade-off technique. RESULTS: When all of the cost components were combined for the entire population (n = 676), the dalteparin group had significantly higher overall costs than the VKA control group (dalteparin = €2375 vs VKA = €1724; P < .001). However, dalteparin was associated with a gain of 0.14 (95% confidence interval [CI]: 0.10-0.18) quality-adjusted life years (QALYs) over VKA. When the incremental cost was combined with the utility gain, dalteparin had a cost of €4,697 (95% CI: €3824-€4951) per QALY gained. CONCLUSION: Secondary prophylaxis with dalteparin is a cost-effective alternative to VKA for the prevention of recurrent VTE in patients with cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".