ArticleJournal of personalized medicine2022
Web-Based Dynamic Nomograms for Predicting Overall Survival and Cancer-Specific Survival in Breast Cancer Patients with Lung Metastases.
Article in Journal of personalized medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- A scoping review of web-based, interactive, personalized decision-making tools available to support breast cancer treatment and survivorship care.Journal of cancer survivorship : research and practice · 2025Article
- Prognostic factors analysis and nomogram construction of breast cancer patients lung metastases and bone metastases.Surgery open science · 2025Article
- Nomogram for predicting the risk and prognosis of lung metastasis of four subtypes of breast cancer: A population-based study from SEER.Cancer pathogenesis and therapy · 2025Article
- Nomogram for predicting survival in breast cancer with lung metastasis based on SEER data.Translational cancer research · 2025Article
- A network dynamic nomogram for predicting overall survival and cancer-specific survival in patients with breast cancer liver metastases: an analysis based on the SEER database.Discover oncology · 2024Article
- Early death prediction model for breast cancer with synchronous lung metastases: an analysis of the SEER database.Gland surgery · 2024Article
- A dynamic visualization clinical tool constructed and validated based on the SEER database for screening the optimal surgical candidates for bone metastasis in primary kidney cancer.Scientific reports · 2024Article
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4 authors.
Funding
Abstract
background60-70% of patients who die from breast cancer have lung metastases. However, there is a lack of readily available tools for accurate risk stratification in patients with breast cancer lung metastases (BCLM). Therefore, a web-based dynamic nomogram was developed for BCLM to quickly, accurately, and intuitively assess overall and cancer-specific survival rates.
methodsPatients diagnosed with BCLM between 2004 and 2016 were extracted from the Surveillance, Epidemiology, and Final Results (SEER) database. After excluding incomplete data, all patients were randomly assigned to training and validation cohorts (2:1). Patients' basic clinical information, detailed pathological staging and treatment information, and sociological information were included in further analysis. Nomograms were constructed following the evaluations of the Cox regression model and verified using the concordance index (C-index), calibration curves, time-dependent receiver operating characteristic (ROC) curves, and decision curve analysis (DCA). Web-based dynamic nomograms were published online.
results3916 breast cancer patients with lung metastases were identified from the SEER database. Based on multivariate Cox regression analysis, overall survival (OS) and cancer-specific survival (CSS) are significantly correlated with 13 variables: age, marital status, race, grade, T stage, surgery, chemotherapy, bone metastatic, brain metastatic, liver metastatic, estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2). These are included in the construction of the nomogram of OS and CSS. The time-dependent receiver operating characteristic curve, decision curve analysis, consistency index, and calibration curve prove the distinct advantages of the nomogram.
conclusionsOur web-based dynamic nomogram effectively integrates patient molecular subtype and sociodemographic characteristics with clinical characteristics and guidance and can be easily used. ER-Negative should receive attention in diagnosing and treating BCLM.
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