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Study of Endometrial Cancer Using Old and New FIGO Staging Systems Comparing Prognosis and Treatment Decisions Based on Surgical Staging and Histopathology
Led by Assiut University · Updated on 2024-10-15
110
Participants Needed
1
Research Sites
N/A
Total Duration
AI-Summary
What this Trial Is About
This research investigates the changes in staging and risk classification for women with endometrial cancer when moving from the older FIGO 2009 staging system to the updated FIGO 2023 system. It aims to understand how these changes affect survival predictions and influence decisions about additional treatments after surgery. The study focuses on endometrial cancer, which mainly affects post-menopausal women and is usually diagnosed around age 60, with most cases being stage I at diagnosis and having a relatively good prognosis. Participants are women diagnosed with endometrial cancer who have undergone surgical staging, including total hysterectomy and removal of ovaries and fallopian tubes. Their cancer tissue samples are reexamined and restaged using both FIGO 2009 and FIGO 2023 systems to compare classifications. The study excludes patients who had chemotherapy before surgery or have recurrent or multiple cancers. The research evaluates the impact of staging changes on treatment decisions and survival outcomes. During the study, researchers review medical records, histopathological slides, and tissue blocks from diagnosis through at least two years of follow-up. They track how many patients have a change in cancer stage or risk group under the new system one year after starting the study. The study also assesses how these changes affect treatment choices and patient survival. Participant involvement includes data collection from existing records and samples without additional interventions, with a focus on evaluating the accuracy and clinical value of the new staging system.
CONDITIONS
Brief Title
Clinicopathological Analysis of Endometrial Carcinoma in the View of Old and New International Federation of Gynecology and Obestetrics (FIGO)
Research Team
Y
Yousra H Abdelghafour, MBBCH
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