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

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 creat...

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Autores principales: Otchere, Prince, Adekoya, Olusola, Governor, Samuel B., Vuppuluri, Naveen, Prabhakar, Akruti, Pak, Stella, Oppong-Nkrumah, Oduro, Cook, Francis, Bohinc, Rudy, Aune, Gregory
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10197831/
https://www.ncbi.nlm.nih.gov/pubmed/37208775
http://dx.doi.org/10.1186/s40959-023-00177-y
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author Otchere, Prince
Adekoya, Olusola
Governor, Samuel B.
Vuppuluri, Naveen
Prabhakar, Akruti
Pak, Stella
Oppong-Nkrumah, Oduro
Cook, Francis
Bohinc, Rudy
Aune, Gregory
author_facet Otchere, Prince
Adekoya, Olusola
Governor, Samuel B.
Vuppuluri, Naveen
Prabhakar, Akruti
Pak, Stella
Oppong-Nkrumah, Oduro
Cook, Francis
Bohinc, Rudy
Aune, Gregory
author_sort Otchere, Prince
collection PubMed
description 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: 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: 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: 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.
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spelling pubmed-101978312023-05-20 Development of cardiac risk prediction model in patients with HER-2 positive breast cancer on trastuzumab therapy Otchere, Prince Adekoya, Olusola Governor, Samuel B. Vuppuluri, Naveen Prabhakar, Akruti Pak, Stella Oppong-Nkrumah, Oduro Cook, Francis Bohinc, Rudy Aune, Gregory Cardiooncology Research 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: 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: 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: 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. BioMed Central 2023-05-19 /pmc/articles/PMC10197831/ /pubmed/37208775 http://dx.doi.org/10.1186/s40959-023-00177-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Otchere, Prince
Adekoya, Olusola
Governor, Samuel B.
Vuppuluri, Naveen
Prabhakar, Akruti
Pak, Stella
Oppong-Nkrumah, Oduro
Cook, Francis
Bohinc, Rudy
Aune, Gregory
Development of cardiac risk prediction model in patients with HER-2 positive breast cancer on trastuzumab therapy
title Development of cardiac risk prediction model in patients with HER-2 positive breast cancer on trastuzumab therapy
title_full Development of cardiac risk prediction model in patients with HER-2 positive breast cancer on trastuzumab therapy
title_fullStr Development of cardiac risk prediction model in patients with HER-2 positive breast cancer on trastuzumab therapy
title_full_unstemmed Development of cardiac risk prediction model in patients with HER-2 positive breast cancer on trastuzumab therapy
title_short Development of cardiac risk prediction model in patients with HER-2 positive breast cancer on trastuzumab therapy
title_sort development of cardiac risk prediction model in patients with her-2 positive breast cancer on trastuzumab therapy
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10197831/
https://www.ncbi.nlm.nih.gov/pubmed/37208775
http://dx.doi.org/10.1186/s40959-023-00177-y
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