Key result
Integrative score with cancer treatments improves AF prediction over standard models to ~0.82 C-index.
Why the study?
Long-term cardiovascular complications such as AF are increasingly relevant in breast cancer survivors, yet conventional AF prediction models rarely incorporate cancer treatment exposures that may modify risk.
Does an integrative atrial fibrillation risk score incorporating breast cancer-specific treatment variables improve prediction of incident atrial fibrillation compared to a conventional clinical model in women with breast cancer?
Cohort (n=1,233)
Yes
Does an integrative atrial fibrillation risk score incorporating breast cancer-specific treatment variables improve prediction of incident atrial fibrillation compared to a conventional clinical model in women with breast cancer?
An integrative risk score incorporating surgical extent and anthracycline dose with traditional cardiovascular risk factors significantly improves long-term atrial fibrillation prediction in breast cancer survivors.
Answers are grounded in this paper and cite their sources.
May aid AF risk stratification in breast cancer survivors; leaves open external validation before clinical use.
Background As breast cancer (BC) survival improves, long-term cardiovascular complications such as atrial fibrillation (AF) are increasingly relevant. Conventional AF prediction models rarely incorporate cancer treatment exposures that may modify risk. We developed and internally optimized an integrative AF risk score combining traditional cardiovascular risk factors with BC-specific treatment variables. Methods We analyzed a multicenter cohort of 1,233 women with BC. Incident AF was assessed over follow-up. To reduce overfitting and optimize predictor selection, we applied penalized LASSO Cox regression with K-fold cross-validation. Predictors retained in the final multivariable model were converted into an integer-based point score using effect sizes from the Cox model. Results Over a median follow-up of 103.4 months, 2.1% of patients developed AF. Variables retained in the final multivariable model were: prior heart failure (HR 18.26, p=0.004; 6 points), age (per 10-year increase above 50 years; HR 2.42, p<0.001; 4 points), hypertension (HR 2.45, p=0.06; 3 points), radical mastectomy (HR 2.27, p=0.120; 1 point), and doxorubicin dose (per 100 mg/m²; HR 1.46, p=0.089; 1 point). Incorporating cancer-related variables (surgical extent and anthracycline exposure) improved discrimination, increasing the C-index to 0.82 (p<0.001) with an absolute gain of 0.038 versus a conventional clinical model (p=0.007). A total score ≥7 identified a high-risk group, with an estimated 28% higher AF risk per additional point. Conclusion An integrative risk score incorporating cancer specific risk factors with conventional cardiovascular risk factors improves AF prediction in BC survivors. This tool may support personalized cardio-oncology surveillance strategies and targeted rhythm monitoring in long-term follow-up.
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Kim et al. (2026) conducted a cohort in Breast cancer (n=1,233). Integrative AF risk score (prior heart failure, age, hypertension, radical mastectomy, doxorubicin dose) vs. Conventional clinical model was evaluated on Incident atrial fibrillation (C-index 0.82 (absolute gain 0.038), p=<0.001). An integrative risk score adding breast cancer treatment variables improved atrial fibrillation prediction vs a conventional clinical model (C-index 0.82, p<0.001; absolute gain 0.038, p=0.007).
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