Brain Metastasis in Endometrial Cancer: A Systematic Review.

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Tác giả: Annalisa Bonasera, Giuseppe Caputo, Danilo Centonze, Paolo Di Mattia, Vittorio Gebbia, Salvatore Lavalle, Basilio Pecorino, Andrea Maria Onofrio Quattrocchi, Daniela Sambataro, Giuseppa Scandurra, Giuseppe Scibilia, Maria Rosaria Valerio, Ernesto Vinci

Ngôn ngữ: eng

Ký hiệu phân loại: 283.3 Branches not in communion with the See of Canterbury

Thông tin xuất bản: Switzerland : Cancers , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 75743

 BACKGROUND: Brain metastases (BMs) from endometrial cancer (EC) are rare and challenging to treat, with limited standardized guidelines. This systematic review aims to evaluate the incidence, therapeutic strategies, and outcomes associated with brain metastases in EC patients, offering insights for clinical practice and future research. METHODS: A comprehensive literature search was conducted using PRISMA guidelines, including PUBMED up to October 2024. Reports reporting individual or aggregate data on EC brain metastases were included. Descriptive and quantitative analyses were performed on incidence, treatment modalities, and survival outcomes. Three reports that used data from the Surveillance, Epidemiology, and End Results and National Cancer Database were used only to assess the incidence of brain metastases from endometrial carcinoma. RESULTS: From 911 reports identified, we included 99 reports, identifying 594 cases
  these and the case of a patient with brain metastasis from endometrial carcinoma followed at our center were used for analysis of disease characteristics
  incidence
  and treatment modalities, such as surgery, radiotherapy, chemotherapy, and combinations. Survival outcomes were influenced by treatment type and disease characteristics, with multimodal approaches showing improved outcomes. DISCUSSION: This review underscores the rarity of EC brain metastases and highlights the need for tailored, multimodal treatment strategies. Future research should focus on prospective trials and molecular profiling to optimize management.
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