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Real-World Data for Predicting Rapid Relapse Triple Negative Cancer: A Study Using NCDB and EHR Data

2026-01-30 oncology Title + abstract only
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BackgroundMany patients with triple-negative breast cancer (TNBC), particularly those who are older, Black, or insured by Medicaid, do not receive guideline-concordant treatment, despite its association with up to 4x higher survival. Early identification of patients at risk for rapid relapse may enable timely interventions and improve outcomes. This study applies machine learning (ML) to real-world data to predict risk of rapid relapse in TNBC. MethodsWe trained various ML models (logistic regr...

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