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767 Cerebral metastastases in gynaecological oncology: the Charité-experience
  1. Julia A Steinle1,
  2. Klaus Pietzner1,
  3. David Wasilewski2 and
  4. Jalid Sehouli1
  1. 1Department of Gynecology European Competence Center for Ovarian Cancer, Campus Virchow-Klinikum, Charité Medical University, Berlin, Germany
  2. 2Charité Universitätsmedizin Berlin – Department of Neurosurgery, Berlin, Germany


Introduction/Background Although gynaecological cancers are rarely causing brain metastases (BM), these lead to a significant reduction in quality of life (QoL) and prognosis. With the growing focus on long-term survival and QoL, the aim of this study was to find out more about BM in gynaecological oncology in order to improve care algorithms for this group of patients.

Methodology From 2020 to 2023, all patients treated in our comprehensive cancer centre with gynaecological cancer and BM were analysed. Medical records were retrospectively reviewed for clinical characteristics.

Results Of 33 patients included, 61%(20) had ovarian, 21%(7) endometrial, 6%(2) cervical and vulva, 3% (1) vaginal cancer. BM occurred 1 (Vagina and Vulva Cancer) to 5 years (Ovarian Cancer) following initial diagnosis. 17 (52%) had FIGO stage III, 2 (6%) stage I and II and 7 (21%) stage IV. Most (52%; 17) had multiple BM, 24% (8) a single metastasis, 9% (3) meningeosis carcinomatosa (MC) and 15% (5) both MC and BM. In 67% (22), symptoms led to the diagnosis of BM, while 33% (11) were diagnosed by routine imaging. Most common symptoms were motor disturbances (33%;7), headaches (25%; 6), dizziness (18%;4), impaired vigilance (15%; 3) and visual disturbances (15%; 3). Symptoms occurred most frequently in MC (100%) or MC+BM (80%). Patients with single metastasis were most likely to remain symptom-free (50%). Most patients (38%;13) received whole brain radiotherapy, followed by local radiotherapy and best supportive care (18%; 6).

Conclusion Patients with MC appear to have the greatest burden on QoL, as 80–100% experience symptoms. A multi-disciplinary designed registry can help to identify predictive and prognostic markers and to define an adequate management algorithm.

Disclosures Nothing to disclose.

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