ArticleInternational journal of general medicine2022
Clinical Characteristics Predict Recurrence in Borderline Ovarian Tumor Patients with Fertility-Preserving Surgery.
Article in International journal of general medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 3 citations in OpenAlex.
- A risk prediction model for recurrence in patients with borderline ovarian tumor based on artificial neural network: development and validation study.Journal of ovarian research · 2025Article
- Random forest-based model for the recurrence prediction of borderline ovarian tumor: clinical development and validation.Journal of cancer research and clinical oncology · 2025Article
- The challenging management of borderline ovarian tumors (BOTs) in women of childbearing age.Frontiers in surgery · 2022Review
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Authors and funding
5 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo identify prognostic factors in patients with borderline ovarian tumor (BOT) and establish and validate a nomogram predicting recurrence in BOT patients treated with fertility-preserving surgery. PATIENTS AND
methodsPatients with BOT who underwent surgery at two institutions between January 2000 and June 2017 were included and categorized into training and validation cohorts. Univariate log rank test and Cox regression analysis were performed in the training cohort to identify prognostic factors, and a nomogram was developed to predict the recurrence rate. The model was validated by calculating the C-index and drawing the calibration curve and receiver operating curve (ROC).
conclusionIn the multivariate Cox regression analysis, practice period, past history of benign ovarian disease, past history of benign breast disease, elevated CA125 levels, elevated CA199 levels, surgical methods, greater omentum resection, FIGO stage, postoperative pregnancy, and re-operation were independently associated with recurrence-free survival (p<0.05). The aforementioned prognostic factors were used to develop a nomogram. The nomogram demonstrated a good ability to predict the risk of recurrence (training cohort C-index: 0.866, validation cohort C-index: 0.920). The calibration curve suggested that the predicted recurrence-free survival was closely related to the actual recurrence. ROC analysis showed that the nomogram had a good discriminatory power with the area under curve between 0.776 and 0.956. The nomogram can predict the 1-, 3-, and 5-year recurrence-free survival of BOT patients undergoing fertility-preserving surgery. The predictive model can help guide surgical plans, postoperative monitoring, and prognostic evaluation of BOT patients.
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