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Radiomics Nomogram: Prediction of 2-Year Disease-Free Survival in Young Age Breast Cancer

SIMPLE SUMMARY: Breast cancer in young women under 40 years of age shows a poor prognosis, and its treatment is difficult due to premenopausal status and fertility preservation. The early prediction of prognosis of young age breast cancer would be helpful for planning treatment and postoperative sur...

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Autores principales: Lee, Jeongmin, Kim, Sung Hun, Kim, Yelin, Park, Jaewoo, Park, Ga Eun, Kang, Bong Joo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9497155/
https://www.ncbi.nlm.nih.gov/pubmed/36139620
http://dx.doi.org/10.3390/cancers14184461
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author Lee, Jeongmin
Kim, Sung Hun
Kim, Yelin
Park, Jaewoo
Park, Ga Eun
Kang, Bong Joo
author_facet Lee, Jeongmin
Kim, Sung Hun
Kim, Yelin
Park, Jaewoo
Park, Ga Eun
Kang, Bong Joo
author_sort Lee, Jeongmin
collection PubMed
description SIMPLE SUMMARY: Breast cancer in young women under 40 years of age shows a poor prognosis, and its treatment is difficult due to premenopausal status and fertility preservation. The early prediction of prognosis of young age breast cancer would be helpful for planning treatment and postoperative surveillance. In this study, the radiomics-based nomogram for the prediction of recurrence shows good predictive ability, especially 2-year disease-free survival after surgery. Several radiomics features presumed to be unique imaging features of young age breast cancer were also observed: tumor homogeneity and tumor sphericity. As these radiomics features are quantitative parameters extracted through the texture analysis of breast MRI, they may reflect the information of tumors more objectively, such as the tumor microenvironment. Furthermore, these results will be the basis for identifying the unique biology of young age breast cancer through multi-omics studies such as radio-genomics. ABSTRACT: This study aimed to predict early breast cancer recurrence in women under 40 years of age using radiomics signature and clinicopathological information. We retrospectively investigated 155 patients under 40 years of age with invasive breast cancer who underwent MRI and surgery. Through stratified random sampling, 111 patients were assigned as the training set, and 44 were assigned as the validation set. Recurrence-associated factors were investigated based on recurrence within 5 years during the total follow-up period. A Rad-score was generated through texture analysis (3D slicer, ver. 4.8.0) of breast MRI using the least absolute shrinkage and selection operator Cox regression model. The Rad-score showed a significant association with disease-free survival (DFS) in the training set (p = 0.003) and validation set (p = 0.020) in the Kaplan–Meier analysis. The nomogram was generated through Cox proportional hazards models, and its predictive ability was validated. The nomogram included the Rad-score and estrogen receptor negativity as predictive factors and showed fair DFS predictive ability in both the training and validation sets (C-index 0.63, 95% CI 0.45–0.79). In conclusion, the Rad-score can predict the disease recurrence of invasive breast cancer in women under 40 years of age, and the Rad-score-based nomogram showed reasonably high DFS predictive ability, especially within 2 years of surgery.
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spelling pubmed-94971552022-09-23 Radiomics Nomogram: Prediction of 2-Year Disease-Free Survival in Young Age Breast Cancer Lee, Jeongmin Kim, Sung Hun Kim, Yelin Park, Jaewoo Park, Ga Eun Kang, Bong Joo Cancers (Basel) Article SIMPLE SUMMARY: Breast cancer in young women under 40 years of age shows a poor prognosis, and its treatment is difficult due to premenopausal status and fertility preservation. The early prediction of prognosis of young age breast cancer would be helpful for planning treatment and postoperative surveillance. In this study, the radiomics-based nomogram for the prediction of recurrence shows good predictive ability, especially 2-year disease-free survival after surgery. Several radiomics features presumed to be unique imaging features of young age breast cancer were also observed: tumor homogeneity and tumor sphericity. As these radiomics features are quantitative parameters extracted through the texture analysis of breast MRI, they may reflect the information of tumors more objectively, such as the tumor microenvironment. Furthermore, these results will be the basis for identifying the unique biology of young age breast cancer through multi-omics studies such as radio-genomics. ABSTRACT: This study aimed to predict early breast cancer recurrence in women under 40 years of age using radiomics signature and clinicopathological information. We retrospectively investigated 155 patients under 40 years of age with invasive breast cancer who underwent MRI and surgery. Through stratified random sampling, 111 patients were assigned as the training set, and 44 were assigned as the validation set. Recurrence-associated factors were investigated based on recurrence within 5 years during the total follow-up period. A Rad-score was generated through texture analysis (3D slicer, ver. 4.8.0) of breast MRI using the least absolute shrinkage and selection operator Cox regression model. The Rad-score showed a significant association with disease-free survival (DFS) in the training set (p = 0.003) and validation set (p = 0.020) in the Kaplan–Meier analysis. The nomogram was generated through Cox proportional hazards models, and its predictive ability was validated. The nomogram included the Rad-score and estrogen receptor negativity as predictive factors and showed fair DFS predictive ability in both the training and validation sets (C-index 0.63, 95% CI 0.45–0.79). In conclusion, the Rad-score can predict the disease recurrence of invasive breast cancer in women under 40 years of age, and the Rad-score-based nomogram showed reasonably high DFS predictive ability, especially within 2 years of surgery. MDPI 2022-09-14 /pmc/articles/PMC9497155/ /pubmed/36139620 http://dx.doi.org/10.3390/cancers14184461 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lee, Jeongmin
Kim, Sung Hun
Kim, Yelin
Park, Jaewoo
Park, Ga Eun
Kang, Bong Joo
Radiomics Nomogram: Prediction of 2-Year Disease-Free Survival in Young Age Breast Cancer
title Radiomics Nomogram: Prediction of 2-Year Disease-Free Survival in Young Age Breast Cancer
title_full Radiomics Nomogram: Prediction of 2-Year Disease-Free Survival in Young Age Breast Cancer
title_fullStr Radiomics Nomogram: Prediction of 2-Year Disease-Free Survival in Young Age Breast Cancer
title_full_unstemmed Radiomics Nomogram: Prediction of 2-Year Disease-Free Survival in Young Age Breast Cancer
title_short Radiomics Nomogram: Prediction of 2-Year Disease-Free Survival in Young Age Breast Cancer
title_sort radiomics nomogram: prediction of 2-year disease-free survival in young age breast cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9497155/
https://www.ncbi.nlm.nih.gov/pubmed/36139620
http://dx.doi.org/10.3390/cancers14184461
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