دورية أكاديمية

A Predictive Model for the Early Death of Breast Cancer With Synchronous Liver Metastases: A Population-Based Study

التفاصيل البيبلوغرافية
العنوان: A Predictive Model for the Early Death of Breast Cancer With Synchronous Liver Metastases: A Population-Based Study
المؤلفون: Shaochun Liu, Yingxue Jia, Jiaying Chai, Han Ge, Runze Huang, Anlong Li, Huaidong Cheng
المصدر: Cancer Control, Vol 30 (2023)
بيانات النشر: SAGE Publishing, 2023.
سنة النشر: 2023
المجموعة: LCC:Neoplasms. Tumors. Oncology. Including cancer and carcinogens
مصطلحات موضوعية: Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
الوصف: Background Breast cancer liver metastasis (BCLM) is a severe condition often resulting in early death. The identification of prognostic factors and the construction of accurate predictive models can guide clinical decision-making. Methods A large sample of data from the Surveillance, Epidemiology, and End Results (SEER) database was analyzed, including 3711 patients diagnosed with de novo BCLM between 2010 and 2015. Predictive models were developed using histograms, and stepwise regression addressed variable collinearity. Internal validation was performed, and results were compared to similar studies. Results In this study of 3711 BCLM patients, 2571 didn't have early death. Out of the 1164 who died early, 1086 had cancer-specific early death. Prognostic factors for early death, including age, race, tumor size, and lymph node involvement, were identified. A nomogram based on these factors was constructed, accurately predicting early all-cause and cancer-specific death. Conclusions Valuable insights into the prognosis of BCLM patients were provided, and important prognostic factors for early death were identified. The developed nomogram can assist clinicians in identifying high-risk patients for early death and inform treatment decisions.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1526-2359
10732748
Relation: https://doaj.org/toc/1526-2359
DOI: 10.1177/10732748231202851
URL الوصول: https://doaj.org/article/abbd6c105e7e4df780d22588545fb66c
رقم الأكسشن: edsdoj.bbd6c105e7e4df780d22588545fb66c
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:15262359
10732748
DOI:10.1177/10732748231202851