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Establishing a Competing Risk Regression Nomogram Model for Survival Data
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Nomogram for Predicting Risk of Cancer Therapy-Related Cardiac Dysfunction in Patients With Human Epidermal Growth
Anthony F Yu1,2, I-Hsin Lin3, Justine Jorgensen1
1Department of Medicine Memorial Sloan Kettering Cancer Center New York NY USA.
Journal of the American Heart Association
|September 26, 2023
Summary
A new nomogram helps estimate the risk of cancer therapy-related cardiac dysfunction (CTRCD) in HER2-positive breast cancer patients. This tool aids clinicians in personalizing treatment and cardiac monitoring for better patient outcomes.
Area of Science:
- Cardiology
- Oncology
- Medical Informatics
Background:
- Cancer therapy-related cardiac dysfunction (CTRCD) is a significant toxicity in HER2-positive breast cancer, impacting treatment and outcomes.
- Existing methods for CTRCD risk assessment are limited, necessitating simpler, individualized tools.
Purpose of the Study:
- To develop and validate a nomogram for predicting 1-year risk of CTRCD in patients with HER2-positive breast cancer receiving trastuzumab-based therapy.
Main Methods:
- A cohort of 1440 patients with HER2-positive breast cancer treated between 2004-2013 was analyzed.
- A multivariable Cox model identified risk factors, leading to a nomogram incorporating 9 clinical variables.
- The nomogram's predictive accuracy was validated using bootstrap resampling.
Main Results:
- A total of 177 CTRCD events occurred within 1 year.
- The developed nomogram demonstrated good discrimination (concordance index: 0.687) and calibration.
- The nomogram includes age, race, BMI, LVEF, blood pressure, CAD, diabetes, arrhythmia, and anthracycline exposure.
Conclusions:
- A 9-variable nomogram provides individualized 1-year CTRCD risk estimates for HER2-positive breast cancer patients.
- This tool can assist clinicians and patients in treatment decisions, cardiac surveillance, and cardioprotective strategies.
- The nomogram offers a practical approach to managing CTRCD risk in this patient population.
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