The aim of this study was to investigate the impact of surgical treatment on the survival prognosis of patients with locally advanced cervical cancer (LACC) and to identify factors that may influence the efficacy of surgery. Data from the SEER database (2000–2020) and a hospital (2013–2023) were collected for this investigation. Utilizing multivariable Cox regression analysis, Kaplan–Meier survival analysis, and log-rank tests, we assessed the effects of surgical intervention on overall survival (OS) and disease-specific survival (DSS) in LACC patients. Our results revealed that in the SEER database, the surgical group exhibited significantly better OS and DSS compared to the non-surgical group. Particularly noteworthy was the significantly higher survival rate in the surgical group for patients with tumor diameters less than 6 cm. Furthermore, both OS and DSS were improved in the surgical group regardless of whether the cancer was squamous cell carcinoma or adenocarcinoma. Additionally, patients who underwent surgery combined with radiotherapy had notably better OS and DSS compared to those who received chemoradiotherapy alone. Similarly, our hospital data showed that the surgical group demonstrated significantly better OS than the non-surgical group, especially for patients with tumors smaller than 6 cm in diameter. These findings suggest that surgery combined with radiotherapy may offer more favorable outcomes than chemoradiotherapy alone, particularly for LACC patients with smaller tumors.

Immune checkpoint blockade (ICB) has revolutionized tumour therapy by relieving immunosuppression and restoring effector T cell cytotoxicity. However, its clinical utility is constrained by low response rates and acquired resistance. Tumour‐associated neutrophils (TANs), key players in tumour immunoregulation, have emerged as critical mediators of ICB responsiveness and resistance, highlighting the therapeutic potential of combining TAN‐targeted strategies with immune checkpoint inhibitors (ICIs). This review systematically synthesizes current knowledge of neutrophils in ICB resistance from several dimensions: (1) clinical indicators of neutrophils, such as the neutrophil‐to‐lymphocyte ratio (NLR) and tissue TANs abundance, as predictors of ICI response and patients prognosis; (2) multifaceted TAN‐involved resistance mechanisms, including direct T cell inhibition, antigen presentation impairment, function modulation of other immune cells, promotion of tumour angiogenesis, and elevation of tumour mutation burden (TMB); (3) combination therapeutic strategies targeting TAN generation/ exhaustion, recruitment, phenotypic polarization, activation, proangiogenic functions, and neutrophil extracellular traps (NETs), along with progress in related clinical trials. Combinatorial approaches integrating TAN‐targeted therapies with ICIs hold substantial promise for overcoming resistance by reshaping the immune microenvironment. Elucidating neutrophil‐mediated resistance mechanisms and optimizing combination strategies will pave the way for precision tumour immunotherapy. Key points: TANs drive ICI resistance via antitumour immune remodelling, angiogenesis promotion, and elevation of tumour mutation burden Neutrophil biomarkers (e.g., NLR, TAN abundance) show strong predictive value for ICI response and prognosis. Targeting TAN recruitment, polarization, function and NETosis represents a promising strategy to overcome ICI resistance. Numerous clinical trials are evaluating combination therapies targeting neutrophils to enhance immunotherapy efficacy.

The objective of this study was to develop and validate a metabolic-lipid nomogram that refines the International Federation of Gynecology and Obstetrics (FIGO) 2000 scoring system, thereby enhancing the predictive capacity for primary chemoresistance and informing therapeutic decision-making in patients with low-risk gestational trophoblastic neoplasia. A cohort of 83 consecutive patients with gestational trophoblastic neoplasia receiving first-line single-agent chemotherapy was retrospectively enrolled. Measurements of fasting blood glucose, full lipid profile, and serum beta-human chorionic gonadotropin (β-hCG) were obtained prior to the first cycle and before every subsequent cycle. A logistic nomogram, designated as the novel model, was constructed using 4 baseline variables: total cholesterol, low-density lipoprotein cholesterol, fasting blood glucose, and β-hCG. Its predictive performance was compared to that of the FIGO score alone and a model combining both. Compared to responders, patients with chemoresistance presented with elevated baseline β-hCG (p =.023) and fasting blood glucose (p =.004), reduced total cholesterol and low-density lipoprotein cholesterol (p =.009), and higher FIGO scores (3-6; p =.004). Multi-variate analysis confirmed low-density lipoprotein cholesterol (odds ratio [OR] 0.085, 95% confidence interval [CI] 0.012 to 0.621), fasting blood glucose (OR 3.793, 95% CI 1.359 to 10.588), and β-hCG >5000 IU/L (OR 7.229, 95% CI 1.484 to 35.209) as independent resistance predictors. The resulting nomogram showed superior predictive performance (area under the curve [AUC] 0.81, 95% CI 0.697 to 0.922), which was further enhanced upon integration with the FIGO score (AUC 0.833, 95% CI 0.738 to 0.929), markedly surpassing the FIGO score alone (AUC 0.704, 95% CI 0.55 to 0.858). Our findings indicate that elevated fasting blood glucose, low-density lipoprotein cholesterol, and β-hCG > 5000 IU/L are key risk factors for chemoresistance in patients with gestational trophoblastic neoplasia. The integration of low-density lipoprotein cholesterol and fasting blood glucose into the FIGO framework significantly enhances the pre-therapeutic prediction of treatment failure, representing a readily translatable, cost-effective strategy for personalizing primary chemotherapy. External validation in diverse, multi-center populations should be encouraged.