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ORIGINAL RESEARCH article

Front. Oncol.
Sec. Gynecological Oncology
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1525867
This article is part of the Research Topic Prognostic Biomarkers and Gene Signatures in Endometrial, Ovarian, and Cervical Cancer View all 5 articles

Development and Validation of a Nomogram to Predict Recurrence in Epithelial Ovarian Cancer Using Complete Blood Count and Lipid Profiles

Provisionally accepted
Xi Tang Xi Tang 1Jingke He Jingke He 2Qin Huang Qin Huang 1Yi Chen Yi Chen 1Ke Chen Ke Chen 1Jing Liu Jing Liu 1Yingyu Tian Yingyu Tian 1*Hui Wang Hui Wang 1*
  • 1 Department of Gynecology, First Affiliated Hospital of Chongqing Medical University, Chongqing, China
  • 2 Department of Urology, First Affiliated Hospital of Chongqing Medical University, Chongqing, Chongqing Municipality, China

The final, formatted version of the article will be published soon.

    Objective: Ovarian cancer is one of the most lethal gynecological malignancies. This study aimed to evaluate the prognostic significance of complete blood count (CBC) and lipid profile in patients with optimally debulked epithelial ovarian cancer (EOC) and develop a nomogram model to predict recurrence-free survival (RFS).Methods: This retrospective study analyzed patients diagnosed with EOC between January 2018 and June 2022.Results: A total of 307 patients were randomly divided into training and validation sets in a ratio of 7:3. Grade, International Federation of Gynecology and Obstetrics (FIGO) stage, platelet-tolymphocyte ratio, red blood cell distribution width-coefficient of variation, triglycerides, and human epididymal protein 4 were identified as independent prognostic factors. The novel nomogram displayed good a predictive performance, with a concordance index (C-index) of 0.787 in the training group and 0.807 in the validation group. The areas under the curve for 1-, 3-, and 5-year RFS were 0.770, 0.881, and 0.904, respectively, in the training group, and 0.667, 0.906, and 0.886, respectively, in the validation group. The calibration curves exhibited good concordance between the predicted survival probabilities and actual observations. Time-dependent C-index curves, integrated discrimination improvement, net reclassification index, and decision curve analysis showed that the nomogram outperformed FIGO staging.This study established and validated a nomogram combining CBC and lipid profiles to predict RFS in patients with optimally debulked EOC, which is expected to aid gynecologists in individualized prognosis assessment and clinical management.

    Keywords: nomogram, epithelial ovarian cancer, Recurrence, complete blood count, lipid profile

    Received: 10 Nov 2024; Accepted: 15 Jan 2025.

    Copyright: © 2025 Tang, He, Huang, Chen, Chen, Liu, Tian and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Yingyu Tian, Department of Gynecology, First Affiliated Hospital of Chongqing Medical University, Chongqing, China
    Hui Wang, Department of Gynecology, First Affiliated Hospital of Chongqing Medical University, Chongqing, China

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