Effectiveness and Safety of Rivaroxaban Versus Warfarin for Treatment of Venous Thromboembolism in Patients with Known Primary Hypercoagulable States
Bibliographic record
Abstract
Background: The efficacy and safety of rivaroxaban versus enoxaparin/vitamin K antagonist (VKA) for treatment and secondary prevention of venous thromboembolism (VTE) was demonstrated in the EINSTEIN clinical trial program. As screening for primary hypercoagulable states was not required as part of the EINSTEIN trial program protocol, fewer than 500 total patients with a known primary hypercoagulable state were identified. Objective: To assess the effectiveness and safety of rivaroxaban versus warfarin for treatment and secondary prevention of VTE in patients with a known primary hypercoagulable state in a large, real-world population. Methods: US MarketScan claims data from January 2012-September 2015 were utilized. We identified adult patients with a primary International Classification of Diseases-9th Revision (ICD-9) discharge diagnosis code for deep vein thrombosis (DVT) (ICD-9=451.1, 451.2, 453.40, 453.41, 453.42, 453.8, 453.9) or pulmonary embolism (PE)(ICD-9=415.1x), diagnosed during a hospitalization or emergency department visit (the index event), with ≥180-days of continuous medical and prescription benefits prior to the index event (baseline), a documented diagnosis for a primary hypercoagulable state (ICD-9=289.81) during baseline or the index VTE encounter and newly-initiated on rivaroxaban or warfarin within 30-days of the index VTE event. Patients with a claim for an anticoagulant before the index event were excluded. Effectiveness and safety endpoints included recurrent VTE, any major bleeding (identified per the Cunningham algorithm), intracranial hemorrhage (ICH) and gastrointestinal bleeding (GIB). Patients were followed for a maximum of 12-months from the index event or until occurrence of an endpoint, switch or discontinuation (14-day permissible gap) of index oral anticoagulation or insurance disenrollment. Rivaroxaban users were 1:1 propensity-score matched to warfarin users. Balance between cohorts was evaluated by inspecting standardized differences for baseline covariates (differences >0.1 indicating imbalance). Cox regression was performed and results reported as hazard ratios (HRs) with 95% confidence intervals (CIs). Results: We matched 403 rivaroxaban and 403 warfarin users with a known primary hypercoagulable state and experiencing a VTE. Mean±standard deviation (SD) duration of patient follow-up was 0.5±3 years. All baseline covariates had a standardized difference Conclusion: Our study results suggest rivaroxaban9s relative effectiveness and safety versus warfarin is maintained when treating VTE patients with known primary hypercoagulable states in routine practice. These real-world study findings are consistent with that of the overall EINSTEIN clinical trial program and its subgroup analysis of patients with primary hypercoagulable states. Disclosures Coleman: Boehringer Ingelheim: Consultancy, Honoraria; Janssen Pharmaceuticals: Consultancy, Honoraria, Research Funding; Bayer AG: Consultancy, Honoraria, Research Funding. Turpie: Bayer HealthCare Pharmaceuticals: Consultancy; Janssen Research and Development: Consultancy, Honoraria. Beyer-Westendorf: Pfizer: Honoraria, Research Funding; Daiichi-Sankyo: Honoraria, Research Funding; Bayer: Honoraria, Research Funding; Boehringer-Ingelheim: Honoraria, Research Funding.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".