Nomogram Based on Immune-Inflammatory Score and Classical Clinicopathological Parameters for Predicting the Recurrence of Endometrial Carcinoma: A Large, Multi-Center Retrospective Study. Journal of inflammation research Background:Surgery is the best approach to treat endometrial cancer (EC); however, there is currently a deficiency in effective scoring systems for predicting EC recurrence post-surgical resection. This study aims to develop a clinicopathological-inflammatory parameters-based nomogram to accurately predict the postoperative recurrence-free survival (RFS) rate of EC patients. Methods:A training set containing 1068 patients and an independent validation set consisting of 537 patients were employed in this retrospective study. The prognostic factors for RFS were identified by univariable and multivariable Cox proportional hazards regression analyses, and integrated into nomogram. The C-index, area under the curves (AUC), and calibration curves were employed to determine the predictive discriminability and accuracy of nomogram. Utilizing the nomogram, patients were stratified into low- and high-risk groups, and the Kaplan-Meier survival curve was further employed to assess the clinical efficacy of the model. Results:Cox regression analyses revealed that age (HR = 1.769, = 0.002), FIGO staging (HR = 1.790, = 0.018), LVSI (HR = 1.654, = 0.017), Ca125 (HR = 1.532, = 0.023), myometrial invasion (HR = 1.865, = 0.001), cervical stromal invasion (HR = 1.655, = 0.033), histology (HR = 2.637, < 0.001), p53 expression (HR = 1.706, = 0.002), PLR (HR = 1.971, = 0.003), SIRI (HR = 2.187, P = 0.003), and adjuvant treatment (HR = 0.521, = 0.003) were independent prognostic factors for RFS in patients with EC. A combined clinicopathologic-inflammatory parameters model was constructed, which outperformed the single-indicator model and other established models in predicting the 1-, 3-, and 5-year RFS rates in patients with EC. Conclusion:The nomogram demonstrated sufficient accuracy in predicting the RFS probabilities of EC, enabling personalized clinical decision-making for future clinical endeavors. 10.2147/JIR.S494716

LRP1B mutation is associated with lymph node metastasis in endometrial carcinoma: A clinical next-generation sequencing study. The International journal of biological markers BACKGROUND:This study aims to investigate the mutation status and protein expression of low-density lipoprotein receptor-related protein 1B (LRP1B) in endometrial cancer, and analyze its association with lymph node metastasis (LNM) in endometrial cancer. METHODS:Targeted next-generation sequencing (NGS) was conducted on both tumor tissues and paired blood DNA obtained from 94 endometrial cancer patients, followed by comprehensive analysis. Additionally, immunohistochemistry (IHC) was used to explore the correlation between LRP1B protein expression levels, its gene mutation status, and LNM. RESULTS: mutation was observed in 19 patients (20.2%). Our results revealed that mutation frequencies were significantly different between endometrial cancer with or without LNM (= 0.038). Multivariate analysis indicated that mutation was a favorable predictor (odds ratio 0.09; 95% confidence interval 0.01-0.95; = 0.045) for LNM in endometrial cancer. Further analysis revealed that combination of mutation with clinical variants (LVSI and histological subtype) yielded a higher area under the curve value of 0.871) and patients harboring mutated-type were less likely to develop LNM. On integrated analysis, the concordance between NGS and LRP1B IHC was 73.3%. CONCLUSIONS:This study utilizes targeted NGS to uncover the relationship between mutation and LNM status, contributing to the development of primary prevention and proactive treatment strategies. 10.1177/03936155241304433