ArticleHeliyon2024
A prognostic model for triple-negative breast cancer patients with liver metastasis: A population-based study.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Potential benefits of local radiotherapy in addition to adjuvant chemotherapy in female patients with triple-negative breast cancer in the absence of distant metastases: a SEER database analysis.Translational cancer research · 2026Article
- Ammonia Detoxification Inhibits Liver Metastasis by Reshaping Hepatic Microenvironment.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Prognostic model for pulmonary metastasis in patients with HER2-positive breast cancer: a population-based study.Breast cancer (Tokyo, Japan) · 2026Article
- Anti-CSF-1R therapy with combined immuno-chemotherapy coordinate an adaptive immune response to eliminate macrophage enriched triple negative breast cancers.Nature communications · 2026Article
- Nomogram for the prediction of the prognosis of patients with triple-negative invasive ductal carcinoma of breast after neoadjuvant chemotherapy.Scientific reports · 2025Article
- Identification of Molecular Subtypes and Prognostic Features for Triple-Negative Breast Cancer Based on Golgi Apparatus-Related Gene Signature.Oncology research · 2025Article
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10 authors.
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Abstract
However, it is still difficult for clinicians to establish prognostic stratifications and therapeutic strategies because of the lack of tools for predicting the survival of triple-negative breast cancer patients with liver metastases (TNBC-LM). Based on clinical data from large populations, a sensitive and discriminative nomogram was developed and validated to predict the prognosis of TNBC patients with LM at initial diagnosis or at the later course. Introduction/background: Liver metastasis (LM) in TNBC patients is associated with significant morbidity and mortality. The objective of this study was to construct a clinical model to predict the survival of TNBC-LM patients. Materials and methods: Clinicopathologic data were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database and the Fifth Affiliated Hospital of Sun Yat-Sen University (FAFSYU). Based on patients with newly diagnosed TNBC with LM (nTNBC-LM) from the SEER database, a predictive nomogram was established and validated. Its predictive effect on TNBC patients with LM at later disease course by enrolling TNBC patients from FAFSYU who developed LM later. The prognostic effect of different treatment for nTNBC-LM was further assessed. Results: A prognostic model was developed and validated to predict the prognosis of TNBC-LM patients. For LM patients diagnosed at the initial or later treatment stage, the C-index (0.712, 0.803 and 0.699 in the training, validation and extended groups, respectively) and calibration plots showed the acceptable prognostic accuracy and clinical applicability of the nomogram. Surgical resection on the primary tumour and chemotherapy were found to be associated with significantly better overall survival (OS). Conclusion: A sensitive and discriminative model was developed to predict OS in TNBC-LM patients both at and after initial diagnosis.
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