About this trial
The subjects of this study are patients with high-grade serous ovarian cancer who have undergone surgical resection. The aim is to construct an artificial intelligence model for predicting postoperative recurrence, metastasis and overall survival of patients based on multimodal data such as surgical pathological images (HE images and IHC images of immune microenvironment-related markers), preoperative baseline imaging data and detailed clinical information of patients. In addition, multi-omics sequencing analysis will be used to deeply explore the heterogeneity of the tumor microenvironment, with the expectation of quantifying the postoperative recurrence risk of patients with high-grade serous ovarian cancer and providing new ideas for the precise diagnosis and treatment of patients with high-grade serous ovarian cancer.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Histologically confirmed high-grade serous ovarian carcinoma using resection specimens.
Well-preserved surgical paraffin-embedded tumor specimens.
Complete clinical information and survival follow-up data.
Disqualifiers
Received preoperative neoadjuvant treatment.
Poor preservation of surgical paraffin specimens.
Incomplete clinical information and survival follow-up data.
With concurrent malignancies other than high-grade serous ovarian carcinoma.
Trial population
Patients with histologically confirmed high-grade serous ovarian carcinoma (HGSOC)
Trial design
Cohort
Retrospective
Treatments tested in this trial
No Intervention: Observational Cohort
Other interventionThis study is an retrospective observational study. There will be no interventions on the participants.
Treatment groups
Trial outcomes
Primary outcomes
Disease-free survival
Locations
Sponsors and contacts
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The Affiliated Hospital of Qingdao University
Lead sponsor
Shandong Provincial Hospital
Collaborator
Yantai Yuhuangding Hospital
Collaborator
Peking University Third Hospital
Collaborator
This trial is not recruiting at the moment. You can still explore other options: