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The goal of this observational study is to develop an exosome-based scoring model for post-treatment surveillance of recurrence in ovarian cancer. The main questions it aims to answer are:
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Ovarian cancer is the most lethal gynecologic malignancy with the lowest survival rate among the three major gynecological malignancies. Over 70% of ovarian cancer patients experience recurrence within three years after initial treatment, making treatment response prediction and recurrence monitoring during treatment phases and follow-up visits particularly crucial. CA125 remains the primary recommended biomarker for ovarian cancer recurrence surveillance in current national and international guidelines, while its suboptimal performance necessitates further improvements.
Clinical trial data demonstrated that an exosome-based scoring model, Ovarian Cancer Score (OCS), outperformed CA125 in sensitivity for detecting FIGO stage I ovarian cancer. Notably, OCS results correlated well with FIGO stage and demonstrated improved sensitivity over CA125, particularly in early-stage ovarian cancer, suggesting its potential for recurrence surveillance. This study proposes to develop and validate a new exosome-based scoring model for post-treatment surveillance of recurrence in ovarian cancer, aiming to explore the potential of exosomal biomarkers in cancer recurrence monitoring and ultimately provide clinicians with an effective surveillance tool for ovarian cancer recurrence management.
The study consists of two stages and plans to prospectively enroll 200 patients with epithelial ovarian cancers. In stage I, enrolled patients will be categorized into relapse and non-relapse groups based on their imaging-confirmed recurrence status. Serum exosomal protein profiles obatined from their blood samples will be used for model development. In stage II, patients in the relapse group will undergo standard clinical management with follow-up visits every 3 months. Serum exosomal protein profiles obatined from them will be used for model validation. Overall, blood samples will be collected at enrollment (baseline), after surgery prior to adjuvant chemotherapy (if applicable), during adjuvant chemotherapy or systemic chemotherapy, after adjuvant chemotherapy prior to follow-up visits, and at several time points during follow-up visits. Follow-up visits will continue until either patients experience an ovarian cancer recurrence or the predetermined endpoint of follow-up visits (18 months) is reached. In stage I, logistic regression model will be used to draw a ROC curve and the Youden index will be used to select the most suitable cutoff value. In stage II, sensitivity, specificity, PPV and NPV will be calculated based on results of the model and imaging-confirmed recurrence status. All data will be processed via SPSS 23.0, GraphPad PRISM version 8.0, and R version 4.4.0.
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200 participants in 1 patient group
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Zheng Feng
Data sourced from clinicaltrials.gov
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