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A novel graded prognostic assessment system for patients with brain metastases from uterine corpus and cervical cancer
Author(s): ,
N. Hayashi
Affiliations:
Shizuoka Cancer Center Hospital, Sunto-gun, Japan
,
S. Deguchi
Affiliations:
Shizuoka Cancer Center Hospital, Sunto-gun, Japan
,
K. Mitsuya
Affiliations:
Shizuoka Cancer Center Hospital, Sunto-gun, Japan
,
Y. Nakasu
Affiliations:
Shizuoka Cancer Center Hospital, Sunto-gun, Japan
Y. Hirashima
Affiliations:
Shizuoka Cancer Center Hospital, Sunto-gun, Japan
EANS Academy. Hayashi N. Oct 21, 2018; 225667; EP3127
Nakamasa Hayashi
Nakamasa Hayashi
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Abstract
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Background. The prevalence of brain metastases (BM) from uterine cancer has recently increased. However, little information is available regarding their clinical characteristics and prognosis, because oncologists have encountered BM from uterine cancer on rare occasions.
Methods. Records from 81 patients with uterine BM were collected from 10 institutes. These were used in a multi-institutional study to identify prognostic factors and develop a graded prognostic assessment (GPA) for patients with BM from uterine cancer.
Results. Median overall survival (OS) after the development of BM was 7 months (95% confidence interval, 4 to 10 months). Multivariate analysis revealed that there were survival differences according to the existence of extracranial metastases (EM) and number of BM. In the present uterine-GPA, a score of 0 was assigned to those patients with ≥5 BM and extracranial metastasis, and a score of 2 was assigned to those patients with one to four BM and without extracranial metastasis. The median OS for patients with a uterine-GPA scores of 0, 1, and 2 was 3, 7, and 22 months, respectively. A survival analysis confirmed the presence of statistically significant differences between these groups (p < 0.05). The results were validated by data obtained from the National Report of Brain Tumor Registry of Japan.
Conclusion. Uterine GPA incorporates two simple clinical parameters of high prognostic significance and can be used to predict the expected survival times in patients with BM from UC. Its use may help in determining an appropriate treatment for individual patients with BM.
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