Skip to main content

ORIGINAL RESEARCH article

Front. Endocrinol.
Sec. Cancer Endocrinology
Volume 15 - 2024 | doi: 10.3389/fendo.2024.1388861
This article is part of the Research Topic Advances in Targeted Therapy and Biomarker Research for Endocrine-Related Cancers View all 7 articles

A nomogram based on inflammation and nutritional biomarkers for predicting the survival of breast cancer patients

Provisionally accepted
Caibiao Wei Caibiao Wei 1Huaying Ai Huaying Ai 2Dan Mo Dan Mo 3Liling Wei Liling Wei 4Zhimin Liu Zhimin Liu 5Peizhang Li Peizhang Li 5Taijun Huang Taijun Huang 5Miaofeng Liu Miaofeng Liu 6*
  • 1 202220730@sr.gxmu.edu.cn, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Region, China
  • 2 Department of Injection Room, Yingtan People's Hospital, Yingtan, China
  • 3 Department of Breast, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi Zhuang Region, China
  • 4 Department of Anesthesiology, First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi Zhuang Region, China
  • 5 Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, Guangxi Zhuang Region, China
  • 6 Department of Clinical Laboratory, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Region, China

The final, formatted version of the article will be published soon.

    Background: We aim to develop a new prognostic model that incorporates inflammation, nutritional parameters and clinical-pathological features to predict overall survival (OS) and disease free survival (DFS) of breast cancer (BC) patients. Methods: The study included clinicopathological and follow-up data from a total of 2857 BC patients between 2013 and 2021. Data were randomly divided into two cohorts: training (n=2001) and validation (n=856) cohorts. A nomogram was established based on the results of a multivariate Cox regression analysis from the training cohorts. The predictive accuracy and discriminative ability of the nomogram were evaluated by the concordance index (C-index) and calibration curve. Furthermore, decision curve analysis (DCA) was performed to assess the clinical value of the nomogram.Results: A nomogram was developed for BC, incorporating lymphocyte, platelet count, hemoglobin levels, albumin-to-globulin ratio, prealbumin level and other key variables: subtype and TNM staging.In the prediction of OS and DFS, the concordance index (C-index) of the nomogram is statistically greater than the C-index values obtained using TNM staging alone. Moreover, the time-dependent AUC, exceeding the threshold of 0.7, demonstrated the nomogram's satisfactory discriminative performance over different periods. DCA revealed that the nomogram offered a greater overall net benefit than the TNM staging system. Conclusion: The nomogram incorporating inflammation, nutritional and clinicopathological variables exhibited excellent discrimination. This nomogram is a promising instrument for predicting outcomes and defining personalized treatment strategies for patients with BC.

    Keywords: breast cancer, inflammation, nutrition, nomogram, prognosis Breast cancer, TNM: tumor-node-metastasis staging, HR: Hazard ratio, CI: confidence interval, OS: overall survival, DFS: Disease free survival, IDC: Invasive ductal carcinoma, ILC: Invasive lobular carcinoma, NLR: Neutrophil-lymphocyte ratio

    Received: 20 Feb 2024; Accepted: 24 Jul 2024.

    Copyright: © 2024 Wei, Ai, Mo, Wei, Liu, Li, Huang and Liu. 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) or licensor 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.

    * Correspondence: Miaofeng Liu, Department of Clinical Laboratory, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Region, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.