相关实验视频

Updated: May 6, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

针对原发性和复发性乳皮脂瘤的独立预后型号:基于人群的队列研究

Huan Deng^1,2, Zhenhua Lu³, Yajie Wang¹

¹Department of Gastrointestinal Surgery, Peking University First Hospital, Beijing, China.

Frontiers in medicine

|August 22, 2025

概括

独立的预后模型用于原发性和复发性皮脂瘤 (RLS) 的开发. 瘤大小和亚型预测初级RLS,而TNM阶段预测复发RLS,有助于个性化治疗.

科学领域:

癌症学
外科瘤学
癌症的预测

背景情况:

逆皮质脂肪瘤 (RLS) 是一种罕见的软组织肉瘤.
准确的预后对于有效的关键管理RS.
需要独立的预测模型来预测一次性和复发性RLS.

研究的目的:

开发和验证原发性和复发性瘤 (RLS) 的独立预后模型.
确定影响RLS结果的关键临床和病理因素.
为RLS患者提供个性化治疗决策工具.

主要方法:

使用来自SEER数据库的2,429名RS患者的数据进行模型开发.
采用单变量和多变量考克斯回归分析和名图构造.
使用来自CPLAGH的245名RLS患者的独立队列验证模型.

主要成果:

瘤大小和病理亚型 (WDL和DDL) 是主要的RLS预测因素.
TNM 阶段是复发性脊髓炎的一个重要预测因素.
开发的模型在培训和验证队列中显示出良好的预测准确性 (AUC~0.75) 和临床适用性.

结论:

建立了对初级和复发性RLS的独立和临床可用的预后模型.
这些模型有助于准确预测和个性化治疗策略.
这些发现为治疗 retroperitoneal 脂肪瘤的临床医生提供了宝贵的指导.

关键词:

一个名字主要的预后情况经常发生背皮皮质脂肪瘤

更多相关视频

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery

Published on: September 27, 2024

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

相关概念视频

Cancer Survival Analysis

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...