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The Prognostic Prediction Value of Systemic Inflammation Score and the Development of a Nomogram for Patients With Surgically Treated Breast Cancer

Background: Systemic inflammation score (SIS) has been verified as a novel prognostic indicator in several cancer types. However, its prognostic value in breast cancer remains unknown. Furthermore, a nomogram based on SIS is yet to be constructed for breast cancer. We conducted this study to explore...

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Autores principales: Huang, Zhang-Zan, Hua, Xin, Song, Chen-Ge, Xia, Wen, Bi, Xi-Wen, Yuan, Zhong-Yu, He, Zhen-Yu, Huang, Jia-Jia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7606938/
https://www.ncbi.nlm.nih.gov/pubmed/33194636
http://dx.doi.org/10.3389/fonc.2020.563731
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author Huang, Zhang-Zan
Hua, Xin
Song, Chen-Ge
Xia, Wen
Bi, Xi-Wen
Yuan, Zhong-Yu
He, Zhen-Yu
Huang, Jia-Jia
author_facet Huang, Zhang-Zan
Hua, Xin
Song, Chen-Ge
Xia, Wen
Bi, Xi-Wen
Yuan, Zhong-Yu
He, Zhen-Yu
Huang, Jia-Jia
author_sort Huang, Zhang-Zan
collection PubMed
description Background: Systemic inflammation score (SIS) has been verified as a novel prognostic indicator in several cancer types. However, its prognostic value in breast cancer remains unknown. Furthermore, a nomogram based on SIS is yet to be constructed for breast cancer. We conducted this study to explore the association between SIS and prognosis of breast cancer, and to construct a good prognostic nomogram model. Methods: A total of 1,180 breast cancer patients who underwent curative surgery between December 2010 and January 2013 were recruited. They were randomly assigned to the training set (n = 944) or the validation set (n = 236). All patient blood samples were collected within 1 week prior to operation. According to previous reports, SIS was calculated for all patients, who were then classified into two groups: high-SIS and low-SIS. The Kaplan–Meier method was employed for survival analyses, and univariate and multivariate analyses (Cox proportional hazards regression model) were used for prognostic assessment. A nomogram was constructed based on the results of multivariate analysis. Calibration curves and concordance index (C-index) were compiled to determine predictive and discriminatory capacity. Results: In the training set, the median follow-up time was 6.07 years. Patients in the high-SIS group had an average OS time of 68.05 months, which is shorter than that of the low-SIS group (72.87 months; P = 0.033). Patients in the high-SIS group had average RFS and DMFS times of 56.04 and 54.46 months, respectively, which are shorter than those of the low-SIS group (60.85 and 59.47 months, respectively; P = 0.247 and P = 0.032). Univariate and multivariate analyses revealed SIS to be an independent prognostic factor for OS and DMFS time. The nomogram for the training set indicated OS and DMFS C-indexes of 0.794 (95% CI, 0.772–0.816) and 0.712 (95% CI, 0.684–0.740), respectively. In the validation set, the OS and DMFS C-indexes were 0.889 (95% CI, 0.845–0.933) and 0.696 (95%. CI, 0.611–0.781), respectively. Conclusions: SIS was confirmed as an independent prognostic predictor among patients with breast cancer who had undergone surgery with curative intent. Higher preoperative SIS may indicate higher risk of metastasis and shorter overall survival time. The prognostic nomogram based on SIS was dependable for breast cancer patients who underwent curative surgery.
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spelling pubmed-76069382020-11-13 The Prognostic Prediction Value of Systemic Inflammation Score and the Development of a Nomogram for Patients With Surgically Treated Breast Cancer Huang, Zhang-Zan Hua, Xin Song, Chen-Ge Xia, Wen Bi, Xi-Wen Yuan, Zhong-Yu He, Zhen-Yu Huang, Jia-Jia Front Oncol Oncology Background: Systemic inflammation score (SIS) has been verified as a novel prognostic indicator in several cancer types. However, its prognostic value in breast cancer remains unknown. Furthermore, a nomogram based on SIS is yet to be constructed for breast cancer. We conducted this study to explore the association between SIS and prognosis of breast cancer, and to construct a good prognostic nomogram model. Methods: A total of 1,180 breast cancer patients who underwent curative surgery between December 2010 and January 2013 were recruited. They were randomly assigned to the training set (n = 944) or the validation set (n = 236). All patient blood samples were collected within 1 week prior to operation. According to previous reports, SIS was calculated for all patients, who were then classified into two groups: high-SIS and low-SIS. The Kaplan–Meier method was employed for survival analyses, and univariate and multivariate analyses (Cox proportional hazards regression model) were used for prognostic assessment. A nomogram was constructed based on the results of multivariate analysis. Calibration curves and concordance index (C-index) were compiled to determine predictive and discriminatory capacity. Results: In the training set, the median follow-up time was 6.07 years. Patients in the high-SIS group had an average OS time of 68.05 months, which is shorter than that of the low-SIS group (72.87 months; P = 0.033). Patients in the high-SIS group had average RFS and DMFS times of 56.04 and 54.46 months, respectively, which are shorter than those of the low-SIS group (60.85 and 59.47 months, respectively; P = 0.247 and P = 0.032). Univariate and multivariate analyses revealed SIS to be an independent prognostic factor for OS and DMFS time. The nomogram for the training set indicated OS and DMFS C-indexes of 0.794 (95% CI, 0.772–0.816) and 0.712 (95% CI, 0.684–0.740), respectively. In the validation set, the OS and DMFS C-indexes were 0.889 (95% CI, 0.845–0.933) and 0.696 (95%. CI, 0.611–0.781), respectively. Conclusions: SIS was confirmed as an independent prognostic predictor among patients with breast cancer who had undergone surgery with curative intent. Higher preoperative SIS may indicate higher risk of metastasis and shorter overall survival time. The prognostic nomogram based on SIS was dependable for breast cancer patients who underwent curative surgery. Frontiers Media S.A. 2020-10-20 /pmc/articles/PMC7606938/ /pubmed/33194636 http://dx.doi.org/10.3389/fonc.2020.563731 Text en Copyright © 2020 Huang, Hua, Song, Xia, Bi, Yuan, He and Huang. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Huang, Zhang-Zan
Hua, Xin
Song, Chen-Ge
Xia, Wen
Bi, Xi-Wen
Yuan, Zhong-Yu
He, Zhen-Yu
Huang, Jia-Jia
The Prognostic Prediction Value of Systemic Inflammation Score and the Development of a Nomogram for Patients With Surgically Treated Breast Cancer
title The Prognostic Prediction Value of Systemic Inflammation Score and the Development of a Nomogram for Patients With Surgically Treated Breast Cancer
title_full The Prognostic Prediction Value of Systemic Inflammation Score and the Development of a Nomogram for Patients With Surgically Treated Breast Cancer
title_fullStr The Prognostic Prediction Value of Systemic Inflammation Score and the Development of a Nomogram for Patients With Surgically Treated Breast Cancer
title_full_unstemmed The Prognostic Prediction Value of Systemic Inflammation Score and the Development of a Nomogram for Patients With Surgically Treated Breast Cancer
title_short The Prognostic Prediction Value of Systemic Inflammation Score and the Development of a Nomogram for Patients With Surgically Treated Breast Cancer
title_sort prognostic prediction value of systemic inflammation score and the development of a nomogram for patients with surgically treated breast cancer
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7606938/
https://www.ncbi.nlm.nih.gov/pubmed/33194636
http://dx.doi.org/10.3389/fonc.2020.563731
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