A Nomogram for Preoperative Prediction of Ovarian Cancer Risk: A Single-Center Study from Vietnam.

Objective: To develop and validate a nomogram for preoperative prediction of ovarian cancer risk using biochemical and hematological markers. Methods: A retrospective analysis was conducted on 250 patients who underwent surgery for ovarian masses at the National Hospital of Obstetrics and Gynecology (Hanoi, Vietnam). Variables included age, menopausal status, CA125, HE4, neutrophil count (NEU), lymphocyte count (LYM), and neutrophil-to-lymphocyte ratio (NLR). A nomogram was developed using multivariate logistic regression. Model performance was assessed via AUC, ROC analysis, and Decision Curve Analysis (DCA). Results: The final nomogram included CA125, HE4, NEU, LYM, and NLR. It demonstrated superior discrimination (AUC = 0.956) compared to CA125 (AUC = 0.815) or HE4 (AUC = 0.799) alone. DCA confirmed greater net clinical benefit across the 20%-60% threshold range. Conclusion: The proposed nomogram offers a reliable, accessible tool for malignancy risk stratification in women with ovarian tumors. Further validation is warranted.