Skip to content

Study on the Dynamic Changes of Metabolic Biomarkers and Their Prognostic Relationship in Ovarian Cancer

Study on the Dynamic Changes of Metabolic Biomarkers and Their Prognostic Relationship in Ovarian Cancer

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT06019923
Enrollment
100
Registered
2023-08-31
Start date
2023-10-26
Completion date
2027-09-10
Last updated
2025-07-17

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Ovarian Cancer

Brief summary

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

Detailed description

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.

Interventions

OTHERNo intervention

No intervention

Sponsors

Women's Hospital School Of Medicine Zhejiang University
Lead SponsorOTHER

Study design

Observational model
CASE_ONLY
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
FEMALE
Age
18 Years to 75 Years

Inclusion criteria

* Age between 18 and 75 years; * Pathological diagnosis of high-grade serous ovarian cancer; * Newly diagnosed ovarian cancer case without prior neoadjuvant therapy.

Exclusion criteria

* Non-primary (recurrent) patients; * Ovarian cancer patients who have not undergone surgical treatment; * Patients with a history of other malignancies.

Design outcomes

Primary

MeasureTime frameDescription
Progression-Free-Survival36 monthsthe length of time after surgical treatment for ovarian cancer that a patient lives without any signs or symptoms of the disease getting worse

Countries

China

Contacts

Primary ContactHongyu Xie, phD
xiehongyu@zju.edu.cn+86-15244773429

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026