ArticleBMC cancer2020
Risk factors, prognostic factors, and nomograms for bone metastasis in patients with newly diagnosed infiltrating duct carcinoma of the breast: 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 33 papers.
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Who cites it
33 citing papers in PubMed, 38 citations in OpenAlex.
- A new prediction model for overall survival of elderly patients with solitary bone plasmacytoma: A population-based study.Frontiers in public health · 2022Trial
- External validation of a nomogram for de novo bone metastasis in breast cancer: a single-center Mexican cohort.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Article
- Machine learning-based prognostic model for metastatic breast cancer and its interpretability: a multicenter retrospective study.Gland surgery · 2025Article
- Dynamic conditional survival nomogram for non-early-stage infiltrating ductal carcinoma based on SEER database.Scientific reports · 2025Article
- 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
- Observational
- Prognostic factors analysis and nomogram construction of breast cancer patients lung metastases and bone metastases.Surgery open science · 2025Article
- Analysis of clinicopathological characteristics in rhabdomyosarcoma and identification of risk factors for metastasis to the lung, bone, liver, and brain: a population-based cohort study.Discover oncology · 2025Article
- Development and validation of a nomogram for predicting bone metastasis in breast cancer: a retrospective study.Frontiers in surgery · 2025Article
- AI models predicting breast cancer distant metastasis using LightGBM with clinical blood markers and ultrasound maximum diameter.Scientific reports · 2024Article
- Prognostic value of serum tartrate‑resistant acid phosphatase‑5b for bone metastasis in patients with resectable breast cancer.Oncology letters · 2024Article
- Construction and validation of a nomogram for cancer specific survival of postoperative pancreatic cancer based on the SEER and China database.BMC gastroenterology · 2024Article
- Development and validation of AI models using LR and LightGBM for predicting distant metastasis in breast cancer: a dual-center study.Frontiers in oncology · 2024Article
- Prognostic factors for hormone receptor-positive breast cancer with liver metastasis and establishment of novel nomograms for prediction: a SEER-based study.Translational cancer research · 2023Article
- Development of a predictive model to identify patients most likely to benefit from surgery in metastatic breast cancer.Scientific reports · 2023Article
- Benefits of Dynamic Nomogram Models for Elderly Diffuse Large B-Cell Lymphoma Patients' Early Death Prediction and Clinical Application.Mediators of inflammation · 2023Article
- Predicting survival of patients with bone metastasis of unknown origin.Frontiers in endocrinology · 2023Article
- Review
- Establishment of the diagnostic and prognostic nomograms for pancreatic cancer with bone metastasis.Scientific reports · 2022Article
- Risk factors and predictive nomograms for early death of patients with advanced hepatocellular carcinoma: a large retrospective study based on the SEER database.BMC gastroenterology · 2022Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBreast cancer is the most common malignancy in women, and it is also the leading cause of death in female patients; the most common pathological type of BC is infiltrating duct carcinoma (IDC). Some nomograms have been developed to predict bone metastasis (BM) in patients with breast cancer. However, there are no studies on diagnostic and prognostic nomograms for BM in newly diagnosed IDC patients.
methodsIDC patients with newly diagnosed BM from 2010 to 2016 in the Surveillance, Epidemiology and End Results (SEER) database were reviewed. Multivariate logistic regression analysis was used to identify risk factors for BM in patients with IDC. Univariate and multivariate Cox proportional hazards regression analysis were used to explore the prognostic factors of BM in patients with IDC. We then constructed nomograms to predict the risk and prognosis of BM for patients with IDC. The results were validated using bootstrap resampling and retrospective research on 113 IDC patients with BM from 2015 to 2018 at the Affiliated Hospital of Chengde Medical University.
resultsThis study included 141,959 patients diagnosed with IDC in the SEER database, of whom 2383 cases were IDC patients with BM. The risk factors for BM in patients with IDC included sex, primary site, grade, T stage, N stage, liver metastasis, race, brain metastasis, breast cancer subtype, lung metastasis, insurance status, and marital status. The independent prognostic factors were brain metastases, race, grade, surgery, chemotherapy, age, liver metastases, breast cancer subtype, insurance status, and marital status. Through calibration, receiver operating characteristic curve and decision curve analyses, we found that the nomogram for predicting the prognosis of IDC patients with BM displayed great performance both internally and externally.
conclusionThese nomograms are expected to be a precise and personalized tool for predicting the risk and prognosis for BM in patients with IDC. This will help clinicians develop more rational and effective treatment strategies.
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