一个长期生存风险预测模型,用于患有食道表面状细胞癌的患者
Ruoyun Yang1,2, Min Wei2,3, Xin Yu1,2
1Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Journal of Cancer
|November 8, 2024
概括
这项研究确定了预测食道表面状细胞癌 (SESCC) 患者的存活率的关键因素. 一个新的动态名录模型准确地预测了SESCC的长期疾病特异性生存率 (DSS),帮助个性化后续策略.
科学领域:
- 在瘤学瘤学.
- 医学统计 医学统计
背景情况:
- 表面食道状细胞癌 (SESCC) 的长期预后数据有限.
- 为了有效的患者管理和后续战略,需要准确的预后模型.
研究的目的:
- 为了确定SESCC可靠的预后因素.
- 建立一个高精度的预后模型,用于预测SESCC患者的疾病特异性存活率 (DSS).
主要方法:
- 对1171名SESCC患者进行了回顾性队列研究.
- 利用最佳子集回归,考克斯分析和拉索回归来确定预后因素.
- 开发了一种用于生存预测的动态名ogram模型.
主要成果:
- 确定了10个DSS不良的独立预后因素,包括男性性别,较高的查尔森并发症指数 (CCI),差异化,淋巴血管入侵 (LVI),淋巴结转移 (LNM),额外的治疗,中性粒细胞升高,低红细胞 (RBC) 计数,低血红蛋白 (Hb) 和高的α-fetoprotein (AFP).
- 动态名录显示了有利的区分 (AUC 0.913) 和校准.
结论:
- 成功建立了SESCC的强大,长期预后模型.
- 动态名图可以有效预测生存风险,增强SESCC患者的后续策略.
相关概念视频
Barrett Esophagus-I: Introduction
66
Barrett's esophagus is a medical condition where the esophageal mucosa is significantly damaged by stomach acid or other digestive fluids, often due to long-term exposure associated with gastroesophageal reflux disease (GERD). In GERD, a weakened or abnormally relaxed lower esophageal sphincter allows stomach acid to flow persistently into the esophagus.
This constant acid exposure transforms the esophagus's pink mucosal lining (stratified squamous epithelium) into a type of lining more...
This constant acid exposure transforms the esophagus's pink mucosal lining (stratified squamous epithelium) into a type of lining more...
66
Cancer Survival Analysis
328
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...
328
Actuarial Approach
63
The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
63
Assumptions of Survival Analysis
97
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
97


