ArticleJournal of healthcare engineering2022
Construction of a Prognostic Nomogram Model for Patients with Mucinous Breast Cancer.
Article in Journal of healthcare engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 7 citations in OpenAlex.
- Development and validation of novel machine learning-based prognostic models and propensity score matching for comparison of surgical approaches in mucinous breast cancer.Frontiers in endocrinology · 2025Article
- Nomogram for predicting outcomes in elderly women with mucinous breast cancer: A retrospective study combined with external validation in southwest China.Cancer reports (Hoboken, N.J.) · 2024Article
- Nomogram model includingWorld journal of gastrointestinal surgery · 2024Article
- A prognostic nomogram for patients with HR+ mucinous breast carcinoma based on the SEER database and a Chinese cohort study.Frontiers in oncology · 2024Article
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Authors and funding
11 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: The objective of the study is to develop a nomogram for estimating three- and five-year survival rates in mucinous breast cancer patients. Methods: Between 2010 and 2016, the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) were searched as a data source for patients associated with mucinous breast cancer (MBC). A total of 3964 patients were recruited after screening. The multivariate Cox model and the univariate Kaplan-Meier (KM) approach were employed to evaluate the independent prognostic markers, followed by developing a nomogram for estimating three- and five-year survival rates in MBC patients. Consequently, the consistency index (C-index) was employed to assess the predictive accuracy of the generated nomogram. Results: Age, race, T stage, M stage, surgery, and radiotherapy were all independent predictive biomarkers for the MBC patients ( Conclusions: In patients with mucinous breast cancer, the proposed nomogram provides a viable tool for accurate prognostic prediction. In clinical practice, it could serve as a personalized diagnosis tool, estimate prognosis, and help in suggesting treatment plans for patients with MBC.
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Registered trials
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