ArticleOpen heart2023
External validation and updating of prediction models of bleeding risk in patients with cancer receiving anticoagulants.
Article in Open heart, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- Predictive Performance of HAS-BLED Score in Patients with Atrial Fibrillation and Cancer: A Meta-Analysis.Cardiology · 2025Pooled it
- Risk factors for anticoagulant-related bleeding in cancer: traditional and cancer-specific factors.Blood vessels, thrombosis & hemostasis · 2026Article
- Simple, Effective and Validated. VTE CASE Risk Assessment Score for Venous Thromboembolism in Metastatic Germ Cell Tumour Patients Before First-Line Chemotherapy.Cancer medicine · 2024Article
- Development and Validation of Machine Learning Algorithms to Predict 1-Year Ischemic Stroke and Bleeding Events in Patients with Atrial Fibrillation and Cancer.Cardiovascular toxicology · 2024Article
- Left Atrial Appendage Occlusion in Cancer-Associated Atrial Fibrillation: Who, When, and How to Manage Antithrombotic Therapy.Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/HemostasisReview
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivePatients with cancer are at increased bleeding risk, and anticoagulants increase this risk even more. Yet, validated bleeding risk models for prediction of bleeding risk in patients with cancer are lacking. The aim of this study is to predict bleeding risk in anticoagulated patients with cancer.
methodsWe performed a study using the routine healthcare database of the Julius General Practitioners' Network. Five bleeding risk models were selected for external validation. Patients with a new cancer episode during anticoagulant treatment or those initiating anticoagulation during active cancer were included. The outcome was the composite of major bleeding and clinically relevant non-major (CRNM) bleeding. Next, we internally validated an updated bleeding risk model accounting for the competing risk of death.
resultsThe validation cohort consisted of 1304 patients with cancer, mean age 74.0±10.9 years, 52.2% males. In total 215 (16.5%) patients developed a first major or CRNM bleeding during a mean follow-up of 1.5 years (incidence rate; 11.0 per 100 person-years (95% CI 9.6 to 12.5)). The c-statistics of all selected bleeding risk models were low, around 0.56. Internal validation of an updated model accounting for death as competing risk showed a slightly improved c-statistic of 0.61 (95% CI 0.54 to 0.70). On updating, only age and a history of bleeding appeared to contribute to the prediction of bleeding risk.
conclusionsExisting bleeding risk models cannot accurately differentiate bleeding risk between patients. Future studies may use our updated model as a starting point for further development of bleeding risk models in patients with cancer.
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