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Post-Hoc Analysis of RE-MEDY™ Demonstrates Significant Real-World Net Clinical Benefit for Dabigatran Versus Warfarin in Prevention of Secondary Venous Thromboembolism

2014· article· en· W2560443112 on OpenAlexaffabout
Sam Schulman, Henry Eriksson, Ajay K. Kakkar, Clive Kearon, Sebastian Schellong, Patrick Mismetti, Martin Feuring, Stefan Hantel, Joerg Kreuzer, Samuel Z. Goldhaber

Bibliographic record

VenueBlood · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDabigatranMedicineWarfarinHazard ratioInternal medicineConfidence intervalDirect thrombin inhibitorMyocardial infarctionAtrial fibrillationAnesthesia

Abstract

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Abstract Background: The double-blind, parallel-group, noninferiorityRE-MEDY™ study comparing the direct oral thrombin inhibitor dabigatran etexilate to warfarin in the prevention of secondary venous thromboembolism (VTE) showed non-inferiority of dabigatran to warfarin in both hazard ratio (HR) and risk difference for recurrent symptomatic VTE and related deaths. The benefit-risk balance of dabigatran compared to warfarin in secondary VTE prevention can be further explored by evaluating the net clinical benefit (NCB). Methods: Patients with a diagnosis of VTE received dabigatran 150 mg twice daily (n = 1430), or warfarin adjusted to maintain an international normalized ratio (INR) of 2.0–3.0 (n = 1426), for an additional period of 6–36 months after 3–12 months of anticoagulant therapy. NCB in the RE-MEDY™ study was evaluated narrowly by (1) analyzing nonfatal recurrent VTE, nonfatal myocardial infarction (MI), nonfatal stroke, nonfatal systemic embolism, all-cause death, and major bleeding events (MBEs), and broadly by (2) including clinically relevant bleeding events (CRBEs). The latter is considered more applicable to real-world clinical practice. NCB was also assessed by center time in therapeutic range (cTTR – the mean TTR of all warfarin patients in each center). Results: The narrow NCB (1) was similar between dabigatran and warfarin (HR 1.05, 95% confidence interval [CI]: 0.75–1.46). For the broader NCB (2), a statistically significant difference was evident favoring dabigatran over warfarin (HR 0.73, 95% CI: 0.59–0.91). Stratification of the NCB by cTTR quintiles demonstrated that the positive benefit of dabigatran over warfarin was preserved when comparing to warfarin patients with a good INR control. Conclusion: In the assessment of real-world net clinical benefit in the prevention of secondary VTE, dabigatran was superior to warfarin, irrespective of INR control in the warfarin patients. Table. Net clinical benefit for dabigatran versus warfarin in pooled analyses of RE-MEDY™ Dabigatran (N=1430) n (%) Warfarin (N=1426) n (%) HR (95% CI) p value for superiority Narrow: Composite cardiovascular endpoint* and MBEs (NCB 1) 72 (5.0) 69 (4.8) 1.05 (0.75–1.46) 0.7818 Broad: Composite cardiovascular endpoint*, MBEs and CRBEs (NCB 2) 136 (9.5) 183 (12.8) 0.73 (0.59, 0.91) 0.0058 *Nonfatal recurrent venous thromboembolism (VTE), nonfatal myocardial infarction (MI), nonfatal stroke, nonfatal systemic embolism, all-cause death. Disclosures Schulman: Boehringer Ingelheim: Consultancy, Honoraria, Research Funding; Bayer HealthCare: Consultancy, Honoraria, Research Funding. Eriksson:Boehringer Ingelheim: Consultancy; BMS: Consultancy; Pfizer: Consultancy. Kakkar:Boehringer Ingelheim: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Honoraria, Research Funding; Daiichi: Consultancy, Honoraria, Research Funding; Bayer: Consultancy, Honoraria, Research Funding; Sanofi: Consultancy, Honoraria, Research Funding; Eisai: Consultancy, Honoraria, Research Funding. Kearon:Bayer Healthcare: Consultancy; Boehringer Ingelheim (Canada): Consultancy. Schellong:Boehringer Ingelheim: advisory boards Other, Consultancy, Honoraria; Bayer Healthcare: advisory boards, advisory boards Other, Consultancy, Honoraria; Daiichi Sankyo: advisory boards, advisory boards Other, Honoraria; BMS/Pfizer: Honoraria. Feuring:Boehringer Ingelheim: Employment. Hantel:Boehringer Ingelheim: Employment. Kreuzer:Boehringer Ingelheim: Employment. Goldhaber:Boehringer Ingelheim: Consultancy; Daiichi: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Janssen: Consultancy; Merck: Consultancy; Pfizer: Consultancy; Portola: Consultancy; Sanofi-Aventis: Consultancy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.020
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.022
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0070.005
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.271
GPT teacher head0.446
Teacher spread0.175 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations2
Published2014
Admission routes2
Has abstractyes

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