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Ovarian cancer is a highly lethal gynecological malignancy, often diagnosed at an advanced stage, with high rates of recurrence within 1-2 years after frontline treatment. Current guidelines recommend monitoring tumor markers CA125 and HE4 for disease progression, but these markers may not detect recurrence or disease progression when their levels are below the detection limit. Therefore, there is a need to identify new prognostic biomarkers and monitor their dynamic changes for effective risk stratification and personalized treatment in patients with ovarian cancer
Ovarian Cancer is the deadliest gynecological malignancy, with over 70% of patients being diagnosed at advanced stages, and more than 70% experiencing recurrence within 1-2 years after frontline treatment. The recommended tumor biomarkers for monitoring ovarian cancer progression, CA125 and HE4, still pose the risk of recurrence and disease progression when their levels are below the detection limit. Therefore, it is of paramount importance to search for new prognostic monitoring biomarkers for ovarian cancer in order to stratify the prognosis and implement personalized treatment, ultimately improving patient outcomes. Previous research and literature have indicated that metabolic biomarkers can directly reflect the biochemical changes, physiological status, and disease progression in cancer patients. In comparison to studying the relationship between metabolite expression levels at a single time point and disease prognosis, the dynamic changes in metabolite trajectories with multiple time points can better reflect the dynamic patterns of disease progression throughout the entire cancer cycle, providing more prognostic information for patients with ovarian cancer.
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| No intervention | Other | No intervention |
| Measure | Description | Time Frame |
|---|---|---|
| Progression-Free-Survival | the length of time after surgical treatment for ovarian cancer that a patient lives without any signs or symptoms of the disease getting worse | 36 months |
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Inclusion Criteria:
Exclusion Criteria:
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Women who were diagnosed as high-grade serous ovarian cancer
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Hongyu Xie, phD | Contact | +86-15244773429 | xiehongyu@zju.edu.cn |
| Name | Affiliation | Role |
|---|---|---|
| Hongyu Xie, phD | Women's Hospital School Of Medicine Zhejiang University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Women's Hospital School of Medicine Zhejiang University | Recruiting | Hangzhou | Zhejiang | 310000 | China |
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| ID | Term |
|---|---|
| D010051 | Ovarian Neoplasms |
| ID | Term |
|---|---|
| D004701 | Endocrine Gland Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D010049 | Ovarian Diseases |
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The collected plasma samples are used for plasma metabolomics analysis.
| D000291 |
| Adnexal Diseases |
| D005831 | Genital Diseases, Female |
| D052776 | Female Urogenital Diseases |
| D005261 | Female Urogenital Diseases and Pregnancy Complications |
| D000091642 | Urogenital Diseases |
| D005833 | Genital Neoplasms, Female |
| D014565 | Urogenital Neoplasms |
| D000091662 | Genital Diseases |
| D004700 | Endocrine System Diseases |
| D006058 | Gonadal Disorders |