Prognostic significance of systemic inflammatory response markers NLR, PLR, and MLR in advanced high-risk endometrial cancer following radiotherapy.

OBJECTIVE

This study aims to evaluate the relationship between systemic inflammatory response markers and the short-term prognosis of patients with endometrial cancer after comprehensive treatment.

METHODS

This retrospective study analyzed the baseline data from 156 endometrial cancer patients who received postoperative radiotherapy at the gynecology department of ChangZhi People Hospital Affiliated to ChangZhi Medical College. Optimal cutoff values for preoperative hematological indicators were determined using receiver operating characteristic (ROC) curves. The Kaplan-Meier method was used for univariate analysis to describe survival time and the 5-year overall survival rate of patients, as well as to plot the survival curve for endometrial cancer. Multivariate regression analysis was employed to identify independent risk factors for patient survival prognosis and to establish a multivariate prediction model.

RESULTS

By the end of the follow-up period, 42 patients (26.9%) were alive, and 114 patients (73.1%) had died. The shortest survival period was 21 months, the longest was 73 months, and the median survival time was 51 months. The 5-year survival rate was 39.3%. The prognostic nomogram model for endometrial cancer included 7 risk factors: age, pathological stage, interval time to postoperative chemotherapy, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR). The Hosmer-Lemeshow test result for this model showed that the area under the ROC curve was 0.995 (95% CI: 0.989-1.000), with an optimal cutoff value of 0.485, a sensitivity of 0.951, and a specificity of 0.71616. The internal validation results of the model showed a C-index of 0.995, indicating a good fit and high predictive value of the model.

CONCLUSION

Pre-treatment peripheral blood levels of PLR, NLR, and MLR were higher in deceased patients who received postoperative radiotherapy for advanced endometrial cancer compared to survivors. A multivariate prediction model based on preoperative and intraoperative baseline data can effectively predict patient prognosis.