Bleeding Risk Prediction in Patients Treated with Antithrombotic Drugs According to the Anatomic Site of Bleeding, Indication for Treatment, and Time Since Treatment Initiation

Vinai Bhagirath; Tanya Kovalova; Jia Wang; Lizhen Xu; Shrikant I Bangdiwala; Martin O'Donnell; Ashkan Shoamanesh; Jackie Bosch; Rosa Coppolecchia; Tatsiana Vaitsiakhovich; Frank Kleinjung; Hardi Mundl; John Eikelboom

doi:10.1055/a-2259-1134

Bleeding Risk Prediction in Patients Treated with Antithrombotic Drugs According to the Anatomic Site of Bleeding, Indication for Treatment, and Time Since Treatment Initiation

TH Open. 2024 Mar 18;8(1):e121-e131. doi: 10.1055/a-2259-1134. eCollection 2024 Jan.

Authors

Vinai Bhagirath^{1

2}, Tanya Kovalova¹, Jia Wang¹, Lizhen Xu¹, Shrikant I Bangdiwala^{1

2}, Martin O'Donnell^{1

3}, Ashkan Shoamanesh^{1

2}, Jackie Bosch², Rosa Coppolecchia⁴, Tatsiana Vaitsiakhovich⁵, Frank Kleinjung⁵, Hardi Mundl⁶, John Eikelboom^{1

2}

Affiliations

¹ Population Health Research Institute, Hamilton, Ontario, Canada.
² McMaster University, Hamilton, Ontario, Canada.
³ University of Galway, Galway, Galway, Ireland.
⁴ Bayer US LLC, St. Louis, Missouri, United States.
⁵ Bayer AG, Berlin, Germany.
⁶ Bayer AG, Wuppertal, Germany.

Abstract

Background Reasons for the relatively poor performance of bleeding prediction models are not well understood but may relate to differences in predictors for various anatomical sites of bleeding. Methods We pooled individual participant data from four randomized controlled trials of antithrombotic therapy in patients with coronary and peripheral artery diseases, embolic stroke of undetermined source (ESUS), or atrial fibrillation. We examined discrimination and calibration of models for any major bleeding, major gastrointestinal (GI) bleeding, and intracranial hemorrhage (ICH), according to the time since initiation of antithrombotic therapy, and indication for antithrombotic therapy. Results Of 57,813 patients included, 1,948 (3.37%) experienced major bleeding, including 717 (1.24%) major GI bleeding and 274 (0.47%) ICH. The model derived to predict major bleeding at 1 year from any site (c-index, 0.69, 95% confidence interval [CI], 0.68-0.71) performed similarly when applied to predict major GI bleeding (0.71, 0.69-0.74), but less well to predict ICH (0.64, 0.61-0.69). Models derived to predict GI bleeding (0.75, 0.74-0.78) and ICH (0.72, 0.70-0.79) performed better than the general major bleeding model. Discrimination declined over time since the initiation of antithrombotic treatment, stabilizing at approximately 2 years for any major bleeding and major GI bleeding and 1 year for ICH. Discrimination was best for the model predicting ICH in the ESUS population (0.82, 0.78-0.92) and worst for the model predicting any major bleeding in the coronary and peripheral artery disease population (0.66, 0.65-0.69). Conclusion Performance of risk prediction models for major bleeding is affected by site of bleeding, time since initiation of antithrombotic therapy, and indication for antithrombotic therapy.

Keywords: ESUS, CAD, PAD; antithrombotic; atrial fibrillation; bleeding; risk prediction.

The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. ( https://creativecommons.org/licenses/by/4.0/ ).