Risk assessment of benign ovarian neoplasms in patients after hysterectomy
Keywords:
hysterectomy, benign ovarian neoplasms, residual ovary syndrome, risk assessment, tumor markers, CA 125, HE4, Interleukin-6, ROC analysisAbstract
DOI: 10.52705/2788-6190-2026-02-3
УДК 618.1-089.87
Hysterectomy remains one of the most frequently performed surgical interventions in gynecological practice worldwide. Current trends in operative gynecology, driven by recent research, have shifted from routine prophylactic oophorectomy to ovarian preservation in women of reproductive and perimenopausal age (under 65 years) absent of genetic oncological risks. This strategy aims to prevent cardiovascular diseases, cognitive decline, and premature mortality associated with surgical menopause. However, preserving the gonads after uterus removal is not without risks: compromised blood supply and anatomical alterations can lead to «Residual Ovary Syndrome» and the formation of benign neoplasms, with incidence rates reaching 9–22 % in the long term. The lack of unified preoperative prognostic models for identifying high-risk patients in this specific cohort necessitates the search for new diagnostic markers and risk assessment tools.
The objective: the aim of this study was to develop and substantiate methods for assessing the risk of benign ovarian neoplasms in women who have undergone hysterectomy, based on a comparative analysis of clinical-anamnestic data and a panel of specific serum biomarkers.
Materials and methods. A clinical study was conducted at the bases of the Shupyk National Healthcare University of Ukraine (2019–2022), involving 83 patients with a history of hysterectomy. Participants were divided into two groups: Group I (Control, n = 63) included women with no detected ovarian pathology during follow-up; Group II (Main, n = 20) consisted of patients diagnosed with benign ovarian neoplasms (cysts, cystomas). The study assessed age, Body Mass Index (BMI), comorbidities, and serum levels of specific biomarkers using enzyme-linked immunosorbent assay (ELISA): Interleukin-6 (IL-6), Epidermal Growth Factor Receptor (EGFR), Cancer Antigen 125 (CA 125), Human Epididymis Protein 4 (HE4), and Cytokeratin 19 Fragment (Cyfra 21-1). Statistical analysis was performed using IBM SPSS 26.0, employing Student’s t-test, Mann-Whitney U-test, and ROC analysis with calculation of the Area Under the Curve (AUC) and Youden index to determine optimal cut-off values.
Results. Comparative analysis revealed no statistically significant differences between the groups regarding general clinical characteristics, such as age (45.98 ± 3.40 vs. 47.00 ± 5.14 years; p = 0.311) and BMI (28.26 ± 4.70 vs. 27.35 ± 6.11 kg/m2; p = 0.488), indicating the low predictive value of these traditional parameters. Conversely, highly significant differences (p < 0.001) were observed in the laboratory biomarkers. Patients with neoplasms exhibited elevated levels of IL-6 (17.02 ± 3.65 pg/ml vs. 11.06 ± 2.51 pg/ml in controls), CA 125 (3.96 ± 0.88 U/ml vs. 1.98 ± 0.51 U/ml), HE4 (1855.62 ± 216.27 pg/ml vs. 1460.09 ± 157.82 pg/ml), and Cyfra 21-1, alongside a significant decrease in EGFR levels (19499.6 ± 1405.9 pg/ml vs. 21999.5 ± 1070.4 pg/ml). ROC analysis confirmed the high diagnostic efficacy of the selected panel. CA 125 demonstrated the highest discriminatory ability (AUC = 0.962; 95% CI: 0.894–1.000) with an optimal cut-off value of > 3.30 U/ml, providing 90.0 % sensitivity and 100 % specificity. HE4 (AUC = 0.922; cutoff > 1629.57 pg/ml) and the pro-inflammatory cytokine IL-6 (AUC = 0.921; cut-off > 14.32 pg/ml) also showed excellent predictive potential.
Conclusions. Traditional risk factors (age, obesity, somatic history) are not effective predictors for the development of benign ovarian tumors in patients post-hysterectomy. A comprehensive evaluation of biomarkers CA 125, HE4, and IL-6 allows for the high-precision identification of at-risk patients. The implementation of the defined screening algorithm (specifically utilizing a CA 125 threshold > 3.30 U/ml) is recommended to optimize postoperative monitoring, facilitate timely diagnosis, and determine appropriate management strategies, thereby minimizing the need for repeated complex surgical interventions in women with preserved ovaries.
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