AUTHOR=Sun Xingyu , Li Lan , He Lijuan , Wang Shaohua , Pan Zhiling , Li Dan 

TITLE=Preoperative malnutrition predicts poor early immune recovery following gynecologic cancer surgery: a retrospective cohort study and risk nomogram development

JOURNAL=Frontiers in Immunology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2025.1681762

DOI=10.3389/fimmu.2025.1681762

ISSN=1664-3224

ABSTRACT=BackgroundMalnutrition is prevalent in patients undergoing gynecologic cancer surgery and may compromise postoperative immune competence. However, its specific association with early immune recovery remains unclear, and validated predictive tools are lacking.MethodsThis retrospective cohort study included 1,245 women who underwent curative surgery for cervical, endometrial, or ovarian cancer between March 2021 and September 2023. Preoperative nutritional status was assessed using the Patient-Generated Subjective Global Assessment (PG-SGA), and patients were stratified into well-nourished and malnourished groups. Poor immune recovery was defined as lymphocyte count <1.0 ×109/L on postoperative day 3 (POD3). Multivariate logistic regression was used to identify independent predictors, and a nomogram was developed and internally validated using ROC analysis, calibration curve, and decision curve analysis (DCA).ResultsMalnourished patients had a significantly higher risk of poor immune recovery (36.6% vs. 16.1%, P < 0.001) and postoperative complications. In multivariate analysis, malnutrition (adjusted OR: 2.41; 95% CI: 1.82–3.22), low BMI, anemia, elevated CRP, advanced FIGO stage, open surgery, preoperative lymphopenia, and older age were independently associated with poor immune recovery. The final model demonstrated good discrimination (AUC = 0.821; 95% CI: 0.798–0.845) and clinical utility. The nomogram provides individualized risk estimates to guide perioperative immunonutrition strategies.ConclusionMalnutrition is an independent risk factor for impaired early immune recovery after gynecologic cancer surgery. Our predictive model offers a clinically applicable tool to identify high-risk patients and support personalized perioperative management. Future prospective validation is warranted.