On-treatment Comparative Effectiveness of Vitamin K Antagonists and Direct Oral Anticoagulants in GARFIELD-VTE, and Focus on Cancer and Renal Disease
Bibliographic record
Abstract
Background Direct oral anticoagulants (DOACs) provide a safe, effective alternative to vitamin K antagonists (VKAs) for venous thromboembolism (VTE) treatment, as shown via intention-to-treat comparative effectiveness analysis. However, on-treatment analysis is imperative in observational studies because anticoagulation choice and duration are at investigators' discretion. Objectives The aim of the study is to compare the effectiveness of DOACs and VKAs on 12-month outcomes in VTE patients using on-treatment analysis. Methods The Global Anticoagulant Registry in the FIELD - VTE (GARFIELD-VTE) is a world-wide, prospective, non-interventional study observing treatment of VTE in routine clinical practice. Results In total, 8,034 patients received VKAs (n = 3,043, 37.9%) or DOACs (n = 4,991, 62.1%). After adjustment for baseline characteristics and follow-up bleeding events, and accounting for possible time-varying confounding, all-cause mortality was significantly lower with DOACs than VKAs (hazard ratio: 0.58 [95% confidence interval 0.42–0.79]). Furthermore, patients receiving VKAs were more likely to die of VTE complications (4.9 vs. 2.2%) or bleeding (4.9 vs. 0.0%). There was no significant difference in rates of recurrent VTE (hazard ratio: 0.74 [0.55–1.01]), major bleeding (hazard ratio: 0.76 [0.47–1.24]), or overall bleeding (hazard ratio: 0.87 [0.72–1.05]) with DOACs or VKAs. Unadjusted analyses suggested that VKA patients with active cancer or renal insufficiency were more likely to die than patients treated with DOAC (52.51 [37.33–73.86] vs. 26.52 [19.37–36.29] and 9.97 [7.51–13.23] vs. 4.70 [3.25–6.81] per 100 person-years, respectively). Conclusion DOACs and VKAs had similar rates of recurrent VTE and major bleeding. However, DOACs were associated with reduced all-cause mortality and a lower likelihood of death from VTE or bleeding compared with VKAs.
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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) | 0.001 | 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 | 0.000 |
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".