Testing Olaparib for Ovarian Cancer
This study is testing two different lengths of treatment with olaparib (one year versus two years), and whether adding bevacizumab makes a difference, for people with newly diagnosed, advanced ovarian cancer. You might be eligible if you have Stage III or IV ovarian cancer that is high-grade serous, high-grade endometrioid, or another epithelial ovarian cancer with a specific change in your BRCA1/2 genes. Olaparib works by blocking enzymes that help cancer cells grow, and bevacizumab aims to stop blood vessel formation that feeds tumors. The main goal is to see if one treatment plan helps people live longer without their cancer getting worse.
- Study design
- This is a phase III interventional study aiming to enroll 880 participants. It compares different treatment durations of olaparib, with or without bevacizumab.
- What's involved
- You would undergo blood sample collection, CT scans, and MRI scans. Olaparib is given by mouth, and bevacizumab is given intravenously (into a vein).
- Compensation
- Not stated in the trial record.
- Follow-up
- Your progress will be assessed for up to 5 years after completing 360 days of maintenance therapy.
AI-generated from the public study record. Only the study team can confirm whether you're eligible — confirm details with them before making decisions.
Testing Olaparib for One or Two Years, With or Without Bevacizumab, to Treat Ovarian Cancer
At a glance
Conditions
Where it's being run
695 sites across 58 statesStudy leadership
- Ying Liu · PRINCIPAL_INVESTIGATOR · NRG Oncology
Who to contact
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Do you actually qualify for this trial?
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Inclusion
What this trial measures
- Progression free survival (PFS) at least 360 days after randomization (PFS360)From completing 360 days of maintenance therapy to disease progression (per Response Evaluation Criteria in Solid Tumors [RECIST] version [v]1.1) or death, whichever occurs first, assessed up to 5 years
PFS will be tested using a one-sided, alpha = 0.05 level logrank test. Treatment hazard ratios and their 90% confidence intervals will be estimated using a Cox proportional hazards model specified with a main effect for the randomized treatment assignment and stratified using the stratification factors applied at randomization.