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Proposal 1455

Title of the Proposed Research

Prediction of major bleeding in atrial fibrillation patients with a history of stroke or transient ischemic attack Jacoba Greving

Affiliation

Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, the Netherlands

Funding Source

This research is supported by a grant from the Dutch Heart Foundation, grant number 2013T128, to dr. J.P. Greving.

Potential Conflicts of Interest

None

Data Sharing Agreement Date

3 June 2016

Lay Summary

Background Antithrombotic therapy substantially reduces the risk of recurrent ischemic events in patients with a stroke. However, bleeding is an important and potentially life threatening side effect of antithrombotic therapy. For each individual, the risk of ischemic events should be carefully balanced against the risk of bleeding events. Estimation of an individuals’ bleeding risk before the start of therapy may help to identify those patients in whom the benefits of antithrombotic therapy outweigh the risks.

Recently, we developed a prediction model for major bleeding events in patients with a stroke from arterial origin. This provided insight in important predictors for major bleeding in stroke patients on antiplatelet therapy. Patients with a stroke from cardiac origin have an indication for treatment with oral anticoagulants (OAC). Use of OAC is accompanied with an even greater risk of bleeding and accurate risk stratification before the start of therapy is essential. Several prediction models for major bleeding in patients on OAC exist, but their performance in patients with a history of stroke is not well established.

Several prediction models for major bleeding in patients on OAC exist, but their performance in patients with a history of stroke is not well established.

Aim Our aim is to study the performance of existing prediction models for major bleeding in atrial fibrillation (AF) patients with a history of stroke or transient ischemic attack (TIA) and to investigate whether existing prediction models can be improved for this specific subgroup.

Methods We will perform a post hoc subgroup analysis among AF patients with a history of stroke or TIA in the RE-LY trial. This trial included 18,113 patients with atrial fibrillation, of whom 3623 had a history of stroke or TIA. Patients were randomized to warfarin or dabigatran. We will examine the predictive performance of existing prediction models (e.g. HAS-BLED, ATRIA) in AF patients with a history of stroke or TIA. Subsequently, we will assess whether we can improve predictions for patients in this specific subgroup. We will study which factors are associated with major bleeding in this subgroup and combine those predictive factors with known predictors for major bleeding. The performance of this model will be assessed and if prediction is improved, we will translate this model into an easily applicable score chart, with which physicians can estimate an individuals’ risk of major bleeding.

Study Data Provided

Study BI-1160.26 Randomized Evaluation of Long Term Anticoagulant Therapy (RE-LY) With Dabigatran Etexilate

Statistical Analysis Plan

The statistical analysis plan will be added after the research is published.

Publication Citation

The publication citation will be added after the research is published.

Summary Results

Results summary or link will be posted when available.