Patients on vitamin K treatment: is switching to direct-acting oral anticoagulation cost-effective? A target trial on a prospective cohort
Bibliographic record
Abstract
AIMS: Direct-acting oral anticoagulants (DOACs) have, to a substantial degree, replaced vitamin K antagonists (VKA) as treatments for stroke prevention in atrial fibrillation (AF) patients. However, evidence on the real-world causal effects of switching patients from VKA to DOAC is lacking. We aimed to assess the empirical incremental cost-effectiveness of switching patients to DOAC compared with maintaining VKA treatment. METHODS: The target trial approach was applied to the prospective observational Swiss-AF cohort, which enrolled 2415 AF patients from 2014 to 2017. Clinical data, healthcare resource utilisation and EQ-5D-based utilities representing quality of life were collected in yearly follow-ups. Health insurance claims were available for 1024 patients (42.4%). Overall survival, quality-of-life, costs from the Swiss statutory health insurance perspective and cost-effectiveness were estimated by emulating a target trial in which patients were randomly assigned to switch to DOAC or maintain VKA treatment. RESULTS: 228 patients switching from VKA to DOAC compared with 563 patients maintaining VKA treatment had no overall survival advantage over a 5-year observation period (HR 0.99, 95% CI 0.45, 1.55). The estimated gain in quality-adjusted life years (QALYs) was 0.003 over the 5-year period at an incremental costs of CHF 23 033 (€ 20 940). The estimated incremental cost-effectiveness ratio was CHF 425 852 (€ 387 138) per QALY gained. CONCLUSIONS: Applying a causal inference method to real-world data, we could not demonstrate switching to DOACs to be cost-effective for AF patients with at least 1 year of VKA treatment. Our estimates align with results from a previous randomised trial.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".