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The B-S2CALED Score’s Utility in Predicting Stroke Risk in Breast Cancer Patients with Atrial Fibrillation
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The B-S2CALED Score’s Utility in Predicting Stroke Risk in Breast Cancer Patients with Atrial Fibrillation
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The B-S2CALED Score’s Utility in Predicting Stroke Risk in Breast Cancer Patients with Atrial Fibrillation
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Journal Article
The B-S2CALED Score’s Utility in Predicting Stroke Risk in Breast Cancer Patients with Atrial Fibrillation
2025
Overview
Background: Breast cancer (BC) patients have heightened risks of atrial fibrillation (AF) and ischemic stroke (IS). Standard IS scores are poorly validated in cancer, omit cancer-specific factors, and guidelines offer no cancer-tailored management. Objectives: To develop and validate a novel score to predict IS risk in BC patients with AF. Methods: Data sources: UH Seidman Cancer Center (derivation; 40% set aside for internal validation) and MCG Cancer Center (external validation). Adults ≥ 18 years old with DCIS or stage I–IV BC who developed AF after diagnosis were included. Variable selection by LASSO Cox regression; continuous predictors dichotomized via cubic splines; points assigned from multivariable hazards to form B-S2CALED. Continuous scores were split into risk groups. Discrimination of categorized B-S2CALED versus CHA2DS2-VASc was assessed with the concordance index (C-index) and net reclassification improvement (NRI). Results: In the internal validation cohort (n = 935), 87 patients experienced IS/TIA. The B-S2CALED score achieved a C-index of 0.64 (95% CI 0.59–0.70) compared with 0.54 (95% CI: 0.51–0.56) for CHA2DS2-VASc, yielding a total NRI of 0.188. In the external validation cohort (n = 95), 8 patients developed IS/TIA. The B-S2CALED score produced a C-index of 0.77 (95% CI: 0.72–0.83) versus 0.53 (95% CI: 0.51–0.56) for CHA2DS2-VASc, with a total NRI of 0.563. Similar advantages were observed when the score was treated as a continuous variable. Conclusions: The BC-specific B-S2CALED score outperformed CHA2DS2-VASc for predicting thromboembolic events in BC patients with AF. Validation in larger datasets is needed before clinical adoption.
