Development of cardiac risk prediction model in patients with HER-2 positive breast cancer on trastuzumab therapy.

Breast Cancer Cardiotoxicity Predictive Model Trastuzumab

Journal

Cardio-oncology (London, England)
ISSN: 2057-3804
Titre abrégé: Cardiooncology
Pays: England
ID NLM: 101689938

Informations de publication

Date de publication:
19 May 2023
Historique:
received: 02 11 2022
accepted: 12 05 2023
medline: 20 5 2023
pubmed: 20 5 2023
entrez: 19 5 2023
Statut: epublish

Résumé

25% of all breast cancer patients have HER-2 overexpression. Breast Cancer patients with HER-2 overexpression are typically treated with HER-2 inhibitors such as Trastuzumab. Trastuzumab is known to cause a decrease in left ventricular ejection fraction. The aim of this study is to create a cardiac risk prediction tool among women with Her-2 positive breast cancer to predict cardiotoxicity. Using a split sample design, we created a risk prediction tool using patient level data from electronic medical records. The study included women 18 years of age and older diagnosed with HER-2 positive breast cancer who received Trastuzumab. Outcome measure was defined as a drop in LVEF by more than 10% to less than 53% at any time in the 1-year study period. Logistic regression was used to test predictors. The cumulative incidence of cardiac dysfunction in our study was 9.4%. The sensitivity and specificity of the model are 46% and 84%, respectively. Given a cumulative incidence of cardiotoxicity of 9%, the negative predictive value of the test was 94%. This suggests that in a low-risk population, the interval of screening for cardiotoxicity may be performed less frequently. Cardiac risk prediction tool can be used to identify Her-2 positive breast cancer patients at risk of developing cardiac dysfunction. Also, test characteristics in addition to disease prevalence may inform a rational strategy in performing cardiac ultrasound in Her-2 breast cancer patients. We have developed a cardiac risk prediction model with high NPV in a low-risk population which has an appealing cost-effectiveness profile.

Sections du résumé

BACKGROUND BACKGROUND
25% of all breast cancer patients have HER-2 overexpression. Breast Cancer patients with HER-2 overexpression are typically treated with HER-2 inhibitors such as Trastuzumab. Trastuzumab is known to cause a decrease in left ventricular ejection fraction. The aim of this study is to create a cardiac risk prediction tool among women with Her-2 positive breast cancer to predict cardiotoxicity.
METHOD METHODS
Using a split sample design, we created a risk prediction tool using patient level data from electronic medical records. The study included women 18 years of age and older diagnosed with HER-2 positive breast cancer who received Trastuzumab. Outcome measure was defined as a drop in LVEF by more than 10% to less than 53% at any time in the 1-year study period. Logistic regression was used to test predictors.
RESULTS RESULTS
The cumulative incidence of cardiac dysfunction in our study was 9.4%. The sensitivity and specificity of the model are 46% and 84%, respectively. Given a cumulative incidence of cardiotoxicity of 9%, the negative predictive value of the test was 94%. This suggests that in a low-risk population, the interval of screening for cardiotoxicity may be performed less frequently.
CONCLUSION CONCLUSIONS
Cardiac risk prediction tool can be used to identify Her-2 positive breast cancer patients at risk of developing cardiac dysfunction. Also, test characteristics in addition to disease prevalence may inform a rational strategy in performing cardiac ultrasound in Her-2 breast cancer patients. We have developed a cardiac risk prediction model with high NPV in a low-risk population which has an appealing cost-effectiveness profile.

Identifiants

pubmed: 37208775
doi: 10.1186/s40959-023-00177-y
pii: 10.1186/s40959-023-00177-y
pmc: PMC10197831
doi:

Types de publication

Journal Article

Langues

eng

Pagination

26

Informations de copyright

© 2023. The Author(s).

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Auteurs

Prince Otchere (P)

The University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA.

Olusola Adekoya (O)

Kettering Medical Center, Kettering, OH, USA.

Samuel B Governor (SB)

Washington University School of Medicine, St. Louis, MO, USA.

Naveen Vuppuluri (N)

Kettering Medical Center, Kettering, OH, USA.

Akruti Prabhakar (A)

Wright State University, Dayton, OH, USA.

Stella Pak (S)

Albany Medical Center, Albany, NY, USA. stellacpak@outlook.com.

Oduro Oppong-Nkrumah (O)

McGill University, Montreal, QC, Canada.

Francis Cook (F)

Harvard University, Cambridge, MA, USA.

Rudy Bohinc (R)

Kettering Medical Center, Kettering, OH, USA.

Gregory Aune (G)

The University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA.

Classifications MeSH