Abstract 16520: Treatment Persistence With New Oral Anticoagulants for Non-Valvular Atrial Fibrillation: The Quebec Observational Study
Bibliographic record
Abstract
Introduction: Continuous use of oral anticoagulant therapy is essential to reduce the risk of stroke in patients with non-valvular atrial fibrillation (NVAF). To date, no study has compared real world treatment persistence patterns between users of new oral anticoagulants (NOACs) and warfarin, before and after the introduction of NOACs in 2011 Objective: To compare treatment persistence between NOACs and warfarin users with NVAF. Methods: A retrospective cohort of patients 40 years of age or older with a first inpatient or outpatient diagnosis for NVAF during 2006-14 was identified using the healthcare databases of the Regie de I′assurance-maladie du Quebec (RAMQ). Patients were followed until the emigration date, end of prescription drug coverage, death or December 31, 2014. Treatment persistence was defined from dispensed prescriptions that follow each other with a gap of no more than 20% of the duration of the previous prescription. Kaplan-Meier curves were used to describe the cumulative probability of persistence of the initiating treatment. Cox proportional hazards models were used to estimate hazard ratios (HRs) of discontinuation of NOACs relative to VKAs, after adjustment for baseline confounders. Results: The cohort included 154,101 patients with NVAF, of which 74,000 were diagnosed before January 2011 (54,000 on VKA) and 70,119 after (22,458 on VKA and 16,637 on NOAC). Patients initially treated with VKAs were slightly older and had more comorbidity, including prior bleeding events, cardiovascular diseases as well as other chronic and acute conditions. At twelve months following treatment initiation, persistence was 36% for patients on NOACs compared with 14% for patients on VKAs before and after January 2011. A similar pattern was seen for rivaroxaban versus VKA. After adjustment, the probability of NOAC treatment discontinuation was half that of VKA (HR 0.50; 95% CI: 0.49-0.51). Sensitivity analyses using a longer grace period of 60 days to define persistence confirmed a higher one-year persistence of 80% for NOACs versus 60% for VKAs (HR of discontinuation 0.50; 95% CI: 0.48-0.52). Conclusions: This real world study shows that twice as many patients initiated on NOACs, including rivaroxaban, remain on therapy than those initiating VKAs.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".