Journal
JOURNAL OF CLINICAL MEDICINE
Volume 11, Issue 3, Pages -Publisher
MDPI
DOI: 10.3390/jcm11030847
Keywords
cardiotoxicity; risk prediction models; cardiac dysfunction; trastuzumab-induced cardiotoxicity
Categories
Funding
- Hold'em for Life Oncology Clinician Scientist Award at the University of Toronto's Faculty of Medicine
- Canada Research Chair in Cardiooncology [147814]
- Heart and Stroke Foundation of Canada
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This retrospective cohort study assessed the performance of three published risk prediction models in identifying the risk of Cancer-therapeutics-related cardiac dysfunction (CTRCD) during or immediately post treatment with trastuzumab therapy for HER2+ breast cancer. The results showed that these models can identify relative differences in CTRCD risk, but their ability to predict absolute risk is limited.
Cancer-therapeutics-related cardiac dysfunction (CTRCD) is an important concern in women receiving trastuzumab therapy for HER2+ breast cancer. However, the ability to assess CTRCD risk remains limited. In this retrospective cohort study, we apply three published risk prediction models (Ezaz et al., NSABP-31 cardiac risk scores (CRS), and HFA-ICOS trastuzumab proforma) to 629 women (mean age 52.4 +/- 10.9 years) with Stage I-III HER2+ breast cancer treated with trastuzumab +/- anthracyclines to assess their performance to identify CTRCD during or immediately post treatment. Using these models, patients were classified into CTRCD risk categories according to the pre-treatment characteristics. With NSABP-31 CRS and HFA-ICOS proformas, patients in the highest risk category had a 1.7-to-2.4-fold higher relative risk of CTRCD than the low-risk category (p = 0.010 and 0.005, respectively). However, with all three risk models, those in the low-risk category had a high absolute risk of CTRCD (15.5-25.5%). The discrimination of the models for CTRCD (AUC 0.51-0.60) and their calibration was limited. NSAP-31 CRS and HFA-ICOS proformas can identify relative differences in CTRCD risk between patients, but when considering absolute risk, they are only able to identify the highest risk patients. There remains an ongoing need for accurate CTRCD risk prediction models in women with HER2+ breast cancer.
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