Exosome-based OCS Scores for Predicting Ovarian Cancer Recurrence

NCT ID: NCT06558019

Last Updated: 2024-08-16

Basic Information

• Recruitment Status: NOT_YET_RECRUITING
• Total Enrollment: 509 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2024-10-01
• Study Completion Date: 2026-12-31

Brief Summary

Ovarian cancer is the third most common malignant tumor in China's female reproductive system in terms of incidence rate and the first in terms of mortality. Surgery and systemic chemotherapy are the cornerstone of first-line treatment for patients with epithelial ovarian cancer. The efficacy rate of first-line platinum combined with taxus chemotherapy is more than 80%, and more than half of them reach complete remission (CR). However, even if advanced patients reach CR, 50% -70% still relapse, with a median disease-free interval of 16 months. Most patients lack typical symptoms when they relapse. The sensitivity of CA125 in monitoring recurrence is poor (43-74%), which means that more than 25% of ovarian cancer patients cannot detect recurrence in a timely manner during follow-up. Therefore, more sensitive biomarkers are needed for monitoring ovarian cancer recurrence after treatment. More and more studies have explored the application value of extracellular vesicle technology in the diagnosis and treatment of ovarian cancer, including auxiliary diagnosis, prognosis, monitoring, etc. China already has an approved exosome ovarian cancer diagnostic product by the National Medical Products Administration, namely the Ovarian Cancer Diagnostic Score (OCS) product based on exosome technology, which is also the world's first exosome technology diagnostic kit for ovarian cancer. Clinical trial data shows that OCS products have demonstrated excellent performance in distinguishing between benign and malignant ovarian tumors. Under high specificity (90.2%), it has a higher sensitivity than serum CA125, reaching 95.5% (95% CI 92.7% -97.3%), and has a sensitivity of 89.7% in the diagnosis of stage I ovarian cancer. OCS exhibits better sensitivity than CA125, especially in early ovarian cancer, suggesting that OCS may be a better tool for monitoring recurrence in ovarian cancer patients.The main purpose of this study is to establish an OCS scoring ovarian cancer recurrence prediction and monitoring model based on exosome technology, providing an effective tool for clinical ovarian cancer recurrence prediction and monitoring. Secondly, we hope to explore the correlation between OCS score and tumor staging, chemotherapy sensitivity, PFS, OS indicators, etc., and determine the performance of recurrence prediction models in different subgroups, such as different pathological subtypes of ovarian cancer and different treatment methods.

Detailed Description

This research subjects are patients with epithelial ovarian cancer.The training set adopts case-control analysis, using the PASS software Test for Two Related Proportions in a Matched Case Control Design module. Setting α=0.05, β=0.1, assuming P0=10%, OR=4, and a 1:1 ratio between the case group and the control group, 101 cases need to be separately enrolled in the case group and the control group. The case group consists of patients who have achieved response to first-line treatment and experienced imaging recurrence. Therefore, 101 recurrence events need to be observed during the 18 month follow-up period. Assuming that the response rate to platinum based chemotherapy in first-line treatment is 80% and the recurrence rate at 18 months is 50%, they need to be enrolled in group 101 / 80% / 50%=253 cases. The control group consisted of at least 101 patients who achieved CR with first-line treatment and had no recurrence of OCS imaging during follow-up testing. Assuming a CR rate of 70% with first-line treatment, 145 patients need to be enrolled. Therefore, the inclusion of 253 cases can meet the sample size requirements for both the case group and the control group. Considering a dropout rate of 15%, a total of 298 cases need to be enrolled. Evaluate the performance of the validation set in predicting recurrence. Assuming the sensitivity of predicting recurrence increases from 75% to 90%, with α=0.05 and β=0.2, 45 recurrence events are required. Assuming an 80% response rate to platinum based chemotherapy as first-line treatment and a 50% recurrence rate within 18 months, 45 recurrence events observed during the 18 month follow-up period need to be enrolled / 80% / 50%=113 patients. Assuming a specificity of not less than 90%, α=0.05, β=0.2, 179 patients are required for enrollment. Assuming a dropout rate of 15%, a total of 211 patients need to be included. Taking into account both sensitivity and specificity performance evaluation, a total of 211 patients were included in the validation set.

This project will announce the findings and main achievements of this research through the publication of core Chinese papers and SCI indexed articles. In addition, this project will organize experts in the field to explore consensus and write guidelines, announcing the technical routes and application directions related to this research.

Conditions

Ovarian Cancer

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: RETROSPECTIVE

Eligibility Criteria

Inclusion Criteria

• Women over 18 years old
• Pathological diagnosis of stage I-IV epithelial ovarian cancer
• Eastern Cooperative Oncology Group (ECOG) score ≤ 2
• Expected survival period exceeding 6 months
• Within 8 weeks between diagnosis and enrollment
• Sign informed consent form

Exclusion Criteria

• Non epithelial ovarian tumors
• History of cancer in the past 5 years
• Received systematic treatment for ovarian cancer
• Gestation
• Previous bilateral oophorectomy

• Minimum Eligible Age: 18 Years
• Eligible Sex: FEMALE
• Accepts Healthy Volunteers: No

Sponsors

Lei Li

OTHER

Sponsor Role: lead

Responsible Party

Lei Li

Professor

Responsibility Role: SPONSOR_INVESTIGATOR

Principal Investigators

Lei Li, M.D.

Role: PRINCIPAL_INVESTIGATOR

Peking Union Medical College Hospital

Locations

Peking Union Medical College Hospital

Beijing, Beijing Municipality, China

Countries

China

Central Contacts

Lei Li, M.D.

Role: CONTACT

lileigh@163.com

86-139-1198-8831

Other Identifiers

OCS-OvaRPM

Identifier Type: -

Identifier Source: org_study_id