ArticleBMC cancer2020
A nomogram for predicting survival in patients with de novo metastatic breast cancer: a population-based study.
Article in BMC cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- A Nomogram and Risk Classification System Predicting the Prognosis of Patients with De Novo Metastatic Breast Cancer Undergoing Immediate Breast Reconstruction: A Surveillance, Epidemiology, and End Results Population-Based Study.Current oncology (Toronto, Ont.) · 2023Trial
- Aggressive local therapy forOncology reports · 2023Trial
- Article
- Observational
- Development and validation of a nomogram for predicting overall survival in patients with lower extremity melanoma: based on the Surveillance, Epidemiology, and End Results (SEER) database.Archives of dermatological research · 2025Article
- Subdivision of M1 category and prognostic stage for de novo metastatic breast cancer to enhance prognostic prediction and guide the selection of locoregional therapy.Thoracic cancer · 2024Article
- Deep neural network provides personalized treatment recommendations forJournal of Cancer · 2024Article
- Machine Learning-Based Predictive Model for Mortality in Female Breast Cancer Patients Considering Lifestyle Factors.Cancer management and research · 2024Article
- Survival nomogram for patients withCancer pathogenesis and therapy · 2023Article
- Novel Prognostic Staging System for Patients With De Novo Metastatic Breast Cancer.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2023Article
- Development of a predictive model to identify patients most likely to benefit from surgery in metastatic breast cancer.Scientific reports · 2023Article
- Prognostic value of plasma circulating tumor DNA fraction across four common cancer types: a real-world outcomes study.Annals of oncology : official journal of the European Society for Medical Oncology · 2023Article
- Different risk and prognostic factors for liver metastasis of breast cancer patients withFrontiers in oncology · 2023Article
- Web-Based Dynamic Nomograms for Predicting Overall Survival and Cancer-Specific Survival in Breast Cancer Patients with Lung Metastases.Journal of personalized medicine · 2022Article
- Using Machine Learning Methods to Predict Bone Metastases in Breast Infiltrating Ductal Carcinoma Patients.Frontiers in public health · 2022Article
- DCBLD1 Overexpression Is Associated With a Poor Prognosis in Head and Neck Squamous Cell Carcinoma.Frontiers in immunology · 2022Article
- Nomogram Predicts the Role of Primary Tumor Surgery onFrontiers in oncology · 2022Article
- Construction and validation of a prognostic nomogram in metastatic breast cancer patients of childbearing age: A study based on the SEER database and a Chinese cohort.Frontiers in oncology · 2022Article
- HBV Infection Status Does Not Influence the Initial Metastatic Pattern and the Prognosis of Breast Cancer Patients with de novo and Relapsed Metastatic Disease.Journal of inflammation research · 2022Article
- Article
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background5-10% of patients are diagnosed with metastatic breast cancer (MBC) at the initial diagnosis. This study aimed to develop a nomogram to predict the overall survival (OS) of these patients.
methodsde novo MBC patients diagnosed in 2010-2016 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. They were randomly divided into a training and a validation cohort with a ratio of 2:1. The best subsets of covariates were identified to develop a nomogram predicting OS based on the smallest Akaike Information Criterion (AIC) value in the multivariate Cox models. The discrimination and calibration of the nomogram were evaluated using the Concordance index, the area under the time-dependent receiver operating characteristic curve (AUC) and calibration curves.
resultsIn this study, we included 7986 patients with de novo MBC. The median follow-up time was 36 months (range: 0-83 months). Five thousand three-hundred twenty four patients were allocated into the training cohort while 2662 were allocated into the validation cohort. In the training cohort, age at diagnosis, race, marital status, differentiation grade, subtype, T stage, bone metastasis, brain metastasis, liver metastasis, lung metastasis, surgery and chemotherapy were selected to create the nomogram estimating the 1-, 3- and 5- year OS based on the smallest AIC value in the multivariate Cox models. The nomogram achieved a Concordance index of 0.723 (95% CI, 0.713-0.733) in the training cohort and 0.719 (95% CI, 0.705-0.734) in the validation cohort. AUC values of the nomogram indicated good specificity and sensitivity in the training and validation cohort. Calibration curves showed a favorable consistency between the predicted and actual survival probabilities.
conclusionThe developed nomogram reliably predicted OS in patients with de novo MBC and presented a favorable discrimination ability. While further validation is needed, this may be a useful tool in clinical practice.
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