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Published on: February 28, 2012
Development and Validation of an Intracranial Hemorrhage Risk Score in Older Adults with Atrial Fibrillation Treated
Lily G Bessette1, Daniel E Singer2, Ajinkya Pawar1
1Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Insights
A new claims-based model accurately predicts intracranial hemorrhage (ICH) risk in older adults with atrial fibrillation (AF) starting oral anticoagulation (OAC). This tool improves upon existing scores, aiding safer OAC prescribing decisions.
Area of Science:
- Cardiology
- Geriatrics
- Health Informatics
Background:
- High risk of intracranial hemorrhage (ICH) is a significant barrier to anticoagulation therapy in patients with atrial fibrillation (AF).
- Developing accurate risk prediction models is crucial for optimizing oral anticoagulation (OAC) use in this population.
Purpose of the Study:
- To develop and validate a novel claims-based risk prediction model for ICH in older adults with AF initiating OAC.
- To compare the performance of the new model against established risk scores like HAS-BLED and Homer.
Main Methods:
- Utilized US Medicare claims data from 2010-2017 to identify patients aged ≥65 with AF initiating OAC.
- Employed regularized Cox regression to select ICH predictors and developed an AF ICH risk score.
- Compared the new score with HAS-BLED and Homer using area under the receiver operating characteristic curve (AUC) and net reclassification improvement (NRI).
Main Results:
- The study included 840,020 patients; the developed AF ICH risk score demonstrated superior predictive performance (AUC 0.653/0.650) compared to HAS-BLED (0.580/0.567) and Homer (0.624/0.623) in training and validation sets.
- The novel score significantly improved risk reclassification for patients categorized by HAS-BLED (NRI 15.3%) and Homer (NRI 21.9%) scores.
- The model identified 50 predictors for ICH risk in the AF population.
Conclusions:
- A novel, claims-based ICH risk prediction model was developed and validated for older adults with AF initiating OAC.
- This model shows superior performance over existing scores, offering a valuable tool for clinical decision-making.
- The findings support the use of this model to inform OAC prescribing and potentially mitigate bleeding risks.
Background:
High risk of intracranial hemorrhage (ICH) is a leading reason for withholding anticoagulation in patients with atrial fibrillation (AF). We aimed to develop a claims-based ICH risk prediction model in older adults with AF initiating oral anticoagulation (OAC).
Methods:
We used US Medicare claims data to identify new users of OAC aged ≥65 years with AF in 2010-2017. We used regularized Cox regression to select predictors of ICH. We compared our AF ICH risk score with the HAS-BLED bleed risk and Homer fall risk scores by area under the receiver operating characteristic curve (AUC) and assessed net reclassification improvement (NRI) when predicting 1-year risk of ICH.
Results:
Our study cohort comprised 840,020 patients (mean [SD] age 77.5 [7.4] years and female 52.2%) split geographically into training (3963 ICH events [0.6%] in 629,804 patients) and validation (1397 ICH events [0.7%] in 210,216 patients) sets. Our AF ICH risk score, including 50 predictors, had superior AUCs of 0.653 and 0.650 in the training and validation sets than the HAS-BLED score of 0.580 and 0.567 (p<0.001) and the Homer score of 0.624 and 0.623 (p<0.001). In the validation set, our AF ICH risk score reclassified 57.8%, 42.5%, and 43.9% of low, intermediate, and high-risk patients, respectively, by HAS-BLED score (NRI: 15.3%, p<0.001). Similarly, it reclassified 0.0, 44.1, and 19.4% of low, intermediate, and high-risk patients, respectively, by the Homer score (NRI: 21.9%, p<0.001).
Conclusion:
Our novel claims-based ICH risk prediction model outperformed the standard HAS-BLED score and can inform OAC prescribing decisions.
