Yunfeng Zheng

Incidence, risk factors, and a prognostic nomogram for distant metastasis in endometrial cancer: A SEER‐based study

AbstractObjectiveTo evaluate the metastatic pattern, identify the risk factors, and establish a nomogram for predicting prognosis of endometrial cancer (EC) with distant metastasis.MethodsA retrospective cohort study of women diagnosed with EC was conducted according to the Surveillance, Epidemiology, and End Results (SEER) database during 2010–2017. Multivariate logistic analysis and Cox analysis were performed to identify the risk factors in promoting distant metastasis and predictors associated with overall survival (OS) in this particular subpopulation. A nomogram was then constructed and validated by the concordance index (C‐index), the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis.ResultsA total of 2799 cases of distant metastasis in EC patients were identified, with an overall incidence rate of 3.74% from 2010 to 2017. Black race, unmarried status, non‐endometrioid histologic types, and grade IV were significant risk factors for distant metastasis in EC patients. Meanwhile, race, histology, grade, metastasis status, surgery, lymphadenectomy, and chemotherapy were identified as independent prognostic factors for OS. A nomogram to predict 1‐, 3‐, and 5‐year OS was established, and presented favorable accuracy and clinical applicability. Patients were further divided into high‐ and low‐risk groups according to the model.ConclusionThe nomogram was developed as a highly accurate, individualized tool to better predict the prognosis of EC patients with distant metastasis, which would help clinicians to identify high‐risk patients, and adjust and tailor their treatment strategies.

Comparing survival outcomes between surgical and non-surgical treatments in patients with early-onset endometrial cancer and developing a nomogram to predict survival: a study based on Eastern and Western data sets

Abstract Background Surgery is the preferred approach for treating endometrial cancer (EC). However, the prognosis of young women undergoing surgery has not been thoroughly evaluated. This study aims to establish a prognostic nomogram for predicting overall survival (OS) in postoperative patients with early-onset endometrial cancer (EOEC), facilitating risk stratification for high-risk patients. Methods Patients diagnosed with EOEC during 2004–2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The nomogram of OS was established according to the multivariate Cox regression analyses. The prediction accuracy and clinical net benefit of the model were assessed by the concordance index (C-index), receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Additionally, external validation was performed with 230 EOEC patients who underwent primary surgical treatment at the First Affiliated Hospital of Chongqing Medical University from 2013 to 2018. Results The mean survival period in the surgical group of EOEC was 87.62 months (range: 86.92–88.32), compared to 64.00 months (range: 55.05–72.96) in the non-surgical group. Compared with the non-surgical group, patients who underwent surgery had better outcomes. A total of 4345 eligible postoperative patients with EOEC were identified and enrolled in this study. Multivariate Cox analysis showed that age, race, grade, T stage, tumor size, and lymphadenectomy were significantly associated with the prognosis of EOEC, which were further incorporated to construct a nomogram. C-index and DCA showed the predictive capability and the clinical applicability of the nomogram was superior over the TNM stage and SEER stage. Furthermore, the external validation using the FAHCQMU cohort consistently demonstrated good predictive accuracy. Conclusions Generally, we developed a novel nomogram model by comprehensively integrating multiple risk factors, which accurately predicts the clinical prognosis of EOEC patients after surgery.

LRP1B mutation is associated with lymph node metastasis in endometrial carcinoma: A clinical next-generation sequencing study

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 LRP1B mutation was observed in 19 patients (20.2%). Our results revealed that LRP1B mutation frequencies were significantly different between endometrial cancer with or without LNM ( P  = 0.038). Multivariate analysis indicated that LRP1B mutation was a favorable predictor (odds ratio 0.09; 95% confidence interval 0.01–0.95; P  = 0.045) for LNM in endometrial cancer. Further analysis revealed that combination of LRP1B mutation with clinical variants (LVSI and histological subtype) yielded a higher area under the curve value of 0.871) and patients harboring LRP1B mutated-type were less likely to develop LNM. On integrated analysis, the concordance between LRP1B NGS and LRP1B IHC was 73.3%. Conclusions This study utilizes targeted NGS to uncover the relationship between LRP1B mutation and LNM status, contributing to the development of primary prevention and proactive treatment strategies.