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A Nomogram Based on Radiomics with Mammography Texture Analysis for the Prognostic Prediction in Patients with Triple-Negative Breast Cancer
Joint Authors
Jiang, Xian
Zou, Xiuhe
Sun, Jing
Zheng, Aiping
Su, Chao
Source
Contrast Media & Molecular Imaging
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-08-25
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Objectives.
To develop and validate a radiomics-based nomogram with texture features from mammography for the prognostic prediction in patients with early-stage triple-negative breast cancer (TNBC).
Methods.
The study included 200 consecutive patients with TNBC (training cohort: n = 133, validation cohort: n = 67).
A total of 136 mammography-derived textural features were extracted, and LASSO (least absolute shrinkage and selection operator) was applied to select features for building the radiomics score (Rad-score).
After univariate and multivariate logistic regression, a radiomics-based nomogram was constructed with independent prognostic factors.
The discrimination and calibration power were assessed, and further the clinical applicability of the nomograms was evaluated.
Results.
Among the 136 mammography-derived textural features, fourteen were used to build the Rad-score after LASSO regression.
A radiomics nomogram that incorporates Rad-score and pN stage was constructed.
This nomogram achieved a C-index of 0.873 (95% CI: 0.758–0.989) for predicting iDFS (invasive disease-free survival), which outperformed the clinical model.
Moreover, it is feasible to stratify patients into high-risk and low-risk groups based on the optimal cut-off point of Rad-score.
The validations of the nomogram confirmed favorable discrimination and considerable predictive efficiency.
Conclusions.
The radiomics nomogram that incorporates Rad-score and pN stage exhibited favorable performance in the prediction of iDFS in patients with early-stage TNBCs.
American Psychological Association (APA)
Jiang, Xian& Zou, Xiuhe& Sun, Jing& Zheng, Aiping& Su, Chao. 2020. A Nomogram Based on Radiomics with Mammography Texture Analysis for the Prognostic Prediction in Patients with Triple-Negative Breast Cancer. Contrast Media & Molecular Imaging،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1139263
Modern Language Association (MLA)
Jiang, Xian…[et al.]. A Nomogram Based on Radiomics with Mammography Texture Analysis for the Prognostic Prediction in Patients with Triple-Negative Breast Cancer. Contrast Media & Molecular Imaging No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1139263
American Medical Association (AMA)
Jiang, Xian& Zou, Xiuhe& Sun, Jing& Zheng, Aiping& Su, Chao. A Nomogram Based on Radiomics with Mammography Texture Analysis for the Prognostic Prediction in Patients with Triple-Negative Breast Cancer. Contrast Media & Molecular Imaging. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1139263
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1139263