ArticleTechnology in cancer research & treatment
Nomograms for Estimating Cause-Specific Death Rates of Patients With Inflammatory Breast Cancer: A Competing-Risks Analysis.
Article in Technology in cancer research & treatment. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Triple-Negative Inflammatory Metaplastic Breast Cancer Presenting as a Non-Mass Lesion.Journal of medical cases · 2026Article
- How to Define Inflammatory Breast Cancer: A Systematic Review.Indian journal of surgical oncology · 2025Review
- Nomograms to predict the long-term prognosis for non-metastatic invasive lobular breast carcinoma: a population-based study.Scientific reports · 2024Article
- ER+/PR- phenotype exhibits more aggressive biological features and worse outcome compared with ER+/PR+ phenotype in HER2-negative inflammatory breast cancer.Scientific reports · 2024Article
- A nomogram for predicting survival in patients with gastrointestinal stromal tumor: a study based on the surveillance, epidemiology, and end results database.Frontiers in medicine · 2024Article
- Time-varying effect in older patients with early-stage breast cancer: a model considering the competing risks based on a time scale.Frontiers in oncology · 2024Article
- A nomogram for predicting survival in patients with skin non-keratinizing large cell squamous cell carcinoma: A study based on the Surveillance, Epidemiology, and End Results database.Frontiers in medicine · 2023Article
- Characteristics, Prognosis, and Competing Risk Nomograms of Cutaneous Malignant Melanoma: Evidence for Pigmentary Disorders.Frontiers in oncology · 2022Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeInflammatory breast cancer (IBC) is a rare, aggressive and special subtype of primary breast cancer. We aimed to establish competing-risks nomograms to predict the IBC-specific death (BCSD) and other-cause-specific death (OCSD) of IBC patients.
methodsWe extracted data on primary IBC patients from the SEER (Surveillance, Epidemiology, and End Results) database by applying specific inclusion and exclusion criteria. Cumulative incidence function (CIF) was used to calculate the cumulative incidence rates and Gray's test was used to evaluate the difference between groups. Fine-Gray proportional subdistribution hazard method was applied to identify the independent predictors. We then established nomograms to predict the 1-, 3-, and 5-year cumulative incidence rates of BCSD and OCSD based on the results. The calibration curves and concordance index (C-index) were adopted to validate the nomograms.
resultsWe enrolled 1699 eligible IBC patients eventually. In general, the 1-, 3-, and 5-years cumulative incidence rates of BCSD were 15.3%, 41.0%, and 50.7%, respectively, while those of OCSD were 3.0%, 5.1%, and 7.4%. The following 9 variables were independent predictive factors for BCSD: race, lymph node ratio (LNR), AJCC M stage, histological grade, ER (estrogen receptor) status, PR (progesterone receptor) status, HER-2 (human epidermal growth factor-like receptor 2) status, surgery status, and radiotherapy status. Meanwhile, age, ER, PR and chemotherapy status could predict OCSD independently. These factors were integrated for the construction of the competing-risks nomograms. The results of calibration curves and C-indexes indicated the nomograms had good performance.
conclusionsBased on the SEER database, we established the first competing-risks nomograms to predict BCSD and OCSD of IBC patients. The good performance indicated that they could be incorporated in clinical practice to provide references for clinicians to make individualized treatment strategies.
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