EligibleTrials

Development and Validation of an Ovarian Cancer Risk Prediction Model for Family Members of Ovarian Cancer Probands

Recruiting · NCT07039552 · Observational (researchers observe without assigning treatment) · Lead sponsor: Peking University Third Hospital

View the official record on ClinicalTrials.gov →
Breast cancer

Interventions studied

risk-reducing salpingo-oophorectomy (RRSO)

What this trial is about

Ovarian cancer is the gynecological malignancy with the highest fatality rate, seriously threatening the life and health of women. One of the main reasons for its high fatality rate is that approximately 70% of patients are diagnosed at an advanced stage. Fortunately, about 1/5 of ovarian cancers are associated with genetic factors, providing us with an opportunity to screen high-risk populations and thereby prevent and diagnose the disease at an early stage and reduce the disease burden. Currently, research related to hereditary ovarian cancer in China is still very scarce, and clinical practice relies on data from foreign studies. However, hereditary tumors have distinct regional and ethnic characteristics, making it urgent to conduct clinical research based on the Chinese population to guide clinical practice in China. Current research suggests that approximately 50% - 60% of hereditary ovarian cancers are closely related to the BRCA1/2 genes. Therefore, accurately assessing the risk of ovarian cancer in BRCA1/2 germline mutation carriers is of great significance for the prevention and treatment of hereditary ovarian cancer.

Who can take part

Age range
18 Years and older
Sex
Female
Healthy volunteers
No - a diagnosis or condition is required
Phase
Not specified
Study type
Observational (researchers observe without assigning treatment)

Inclusion criteria

Exclusion criteria

Where it is running

1 location listed.

Read the full protocol, contacts and eligibility on ClinicalTrials.gov →

Get notified when new trials open

One email when new recruiting trials are added. Unsubscribe anytime.