Scholarlink

Purpose <p>Lymphoepithelioma-like carcinoma (LELC) is a rare tumor. The therapeutic strategies and personalized prediction of prognosis for this tumor remain inadequately defined.</p> Patients and methods <p>Five hundred seventy-four patients from Sun Yat-sen University Cancer Center were recruited and split into a training cohort (402) and a validation cohort (172). Significant variables identified through Cox regression analyses were incorporated to develop nomograms. We assessed the predictive precision and discriminatory capacity of the nomograms by employing various metrics, including the time-dependent receiver operating characteristic (ROC) curve, concordance index (C-index), decision curve analysis (DCA) curve, calibration curve, and Kaplan-Meier curves.</p> Results <p>Multivariate Cox analysis identified that surgery, chemotherapy, radiotherapy, N stage, M stage, platelet-to-lymphocyte ratio (PLR), and lactate dehydrogenase-to-albumin ratio (LAR) were independently associated with overall survival (OS) in LELC patients. For progression-free survival (PFS), surgery, chemotherapy, T stage, N stage and M stage emerged as independent predictors. Nomograms were developed by integrating the factors to provide a comprehensive predictive tool. The C-indices of nomograms for forecasting OS and PFS were 0.786 (95%CI 0.734–0.838) and 0.693 (95%CI 0.651–0.735), correspondingly. ROC curves and calibration curves demonstrated consistency with actual observations. Moreover, DCA curves demonstrated the practicality of nomograms, emphasizing their exceptional capacity to distinguish high-risk individuals compared with the 8th AJCC staging system.</p> Conclusion <p>The newly devised nomograms demonstrated considerable potential in predicting OS. Furthermore, this research is the first to suggest that markers related to inflammation and nutrition, such as PLR and LAR, could be significant predictors for forecasting the outcome of individuals with LELC.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Personalized Prediction of prognosis in ebv-associated lymphoepithelioma-like carcinoma: insights from a Chinese cohort study

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月11日

查看全文
  • Yan Wang,
  • Yuanyuan Liu,
  • Gongming Wang,
  • Songzuo Xie,
  • Jinqi You,
  • Xinyi Yang,
  • Minxing Li,
  • Jingjing Zhao,
  • Desheng Weng

摘要

Purpose

Lymphoepithelioma-like carcinoma (LELC) is a rare tumor. The therapeutic strategies and personalized prediction of prognosis for this tumor remain inadequately defined.

Patients and methods

Five hundred seventy-four patients from Sun Yat-sen University Cancer Center were recruited and split into a training cohort (402) and a validation cohort (172). Significant variables identified through Cox regression analyses were incorporated to develop nomograms. We assessed the predictive precision and discriminatory capacity of the nomograms by employing various metrics, including the time-dependent receiver operating characteristic (ROC) curve, concordance index (C-index), decision curve analysis (DCA) curve, calibration curve, and Kaplan-Meier curves.

Results

Multivariate Cox analysis identified that surgery, chemotherapy, radiotherapy, N stage, M stage, platelet-to-lymphocyte ratio (PLR), and lactate dehydrogenase-to-albumin ratio (LAR) were independently associated with overall survival (OS) in LELC patients. For progression-free survival (PFS), surgery, chemotherapy, T stage, N stage and M stage emerged as independent predictors. Nomograms were developed by integrating the factors to provide a comprehensive predictive tool. The C-indices of nomograms for forecasting OS and PFS were 0.786 (95%CI 0.734–0.838) and 0.693 (95%CI 0.651–0.735), correspondingly. ROC curves and calibration curves demonstrated consistency with actual observations. Moreover, DCA curves demonstrated the practicality of nomograms, emphasizing their exceptional capacity to distinguish high-risk individuals compared with the 8th AJCC staging system.

Conclusion

The newly devised nomograms demonstrated considerable potential in predicting OS. Furthermore, this research is the first to suggest that markers related to inflammation and nutrition, such as PLR and LAR, could be significant predictors for forecasting the outcome of individuals with LELC.