Key result
Nomogram accurately predicts 6-month post-treatment myocardial injury in breast cancer with ~0.90 AUC.
Why the study?
Improved prognostic models are needed to predict early myocardial injury after anti-cancer therapy and guide personalized prevention and treatment decisions in breast cancer patients.
Does a prognostic nomogram incorporating hs-cTnT, HDL-C, thoracic aortic calcification score, and anti-HER2 therapy accurately predict early myocardial injury at 6 months in breast cancer patients after anti-cancer treatment?
Cohort (n=551)
Random division into training (n=366) and validation (n=185) cohorts
Does a prognostic nomogram incorporating hs-cTnT, HDL-C, thoracic aortic calcification score, and anti-HER2 therapy accurately predict early myocardial injury at 6 months in breast cancer patients after anti-cancer treatment?
A prognostic nomogram combining hs-cTnT, HDL-C, thoracic aortic calcification score, and anti-HER2 therapy accurately predicts the 6-month risk of early myocardial injury in breast cancer patients after anti-cancer treatment.
Nomogram may support early injury stratification; leaves open prospective validation before adoption.
Improved prognostic models are needed to guide personalized prevention and treatment decisions for breast cancer patients to reduce the risk of myocardial injury after anti-cancer therapy. This study aimed to develop and validate a prognostic nomogram to predict early myocardial injury after treatment. Breast cancer patients with at least three hypersensitive troponin T (hs-cTnT) measurements between January 2014 and December 2021 were included. Patients with hs-cTnT >14 pg/mL during 6-month follow-up were considered to have early myocardial injury. Participants were randomly divided into a training cohort (n = 366) and a validation cohort (n = 185). Univariate Cox regression and LASSO analysis were used to identify candidate predictors, followed by multivariable Cox regression to construct the nomogram. A total of 551 patients were included. Independent predictors included hs-cTnT level, HDL-C level, thoracic aortic calcification score, and anti-HER2 therapy. The nomogram demonstrated good discrimination (AUC 0.901, 95% CI 0.832–0.971) and calibration (C-index 0.908, 95% CI 0.883–0.933) in the validation cohort. Decision curve analysis indicated clinical usefulness, and patients were effectively stratified into high- and low-risk groups (p < 0.001). This nomogram accurately predicts the 6-month risk of myocardial injury after anti-cancer treatment and may assist in risk stratification and clinical decision-making for breast cancer patients.Abstract_Figure1.jpegAbstract_Figure2.jpg
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Zhou et al. (2026) conducted a cohort in Breast cancer receiving anti-cancer therapy (n=551). Nomogram prediction model (incorporating hs-cTnT, HDL-C, thoracic aortic calcification score, and anti-HER2 therapy) was evaluated on Early myocardial injury (defined as hs-cTnT >14 pg/mL during 6-month follow-up) (AUC 0.901, 95% CI 0.832-0.971, p=<0.001). A prognostic nomogram accurately predicted 6-month post-treatment myocardial injury in breast cancer patients (validation AUC 0.901, 95% CI 0.832-0.971; C-index 0.908).
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