Risk Prediction Model for Development of Heart Failure or Cardiomyopathy After Breast Cancer Treatment.

Abstract

Women receiving breast cancer (BC) treatment are at risk for heart failure or cardiomyopathy (HF/CM). No standard method exists to identify women at risk who might benefit from preventive cardiac strategies and surveillance during and after treatment. To develop and validate a model predicting the 10-year risk of developing HF/CM in women receiving systemic treatment for invasive early-stage BC to inform cardiac risk management. This longitudinal cohort study of patients cared for in Kaiser Permanente Southern California, a vertically integrated health care system. The goal of the study was to predict the 10-year HF/CM risk using multivariable elastic-net Cox proportional hazards models. Women aged 18 to 79 years with newly diagnosed invasive local or regional BC from 2008 to 2020, with a median follow-up of 5.2 years, were included. The cohort was randomly split into derivation (60%) and validation (40%) cohorts. Data were analyzed from April 2024 to May 2025. HF/CM risk predictors included age at BC diagnosis, race and ethnicity, area-level socioeconomic status, local and systemic BC treatments, cancer stage, obesity, and history of hypertension, diabetes, hyperlipidemia, smoking, and other CV conditions. Incident HF/CM events. Women were categorized into low-, moderate-, and high-risk groups based on the tertiles of the risk score in the derivation cohort. Of 26 044 women included in the total cohort, the median (IQR) age was 61 (52-68) years. The risk model had good calibration and high accuracy in predicting HF/CM risk in the 3 subgroups, with HF/CM risk in the validation cohort matching the estimates from the derivation for identifying women at low risk (1.7%; 95% CI, 1.1%-2.4%) and high risk (19.4%; 95% CI. 17.3%-21.5%) of HF/CM at 10 years. The model's discrimination ability was good, based on the time-dependent area under the curve of 0.79 at 10 years in the validation cohort. This risk prediction model among women with early-stage BC was able to prospectively identify those at risk of HF/CM over a 10-year period based on the selected BC treatment and clinical variables available at BC diagnosis. The model can be used to inform risk-guided cardiac management for these women.