相关实验视频

Updated: Jun 4, 2025

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

用于预测喉状细胞癌的老年患者早期死亡的诺莫图:基于人口的SEER研究

Qi-Wei Liang¹, Xi-Lin Gao², Jun-Wei Zhang¹

¹Department of Otorhinolaryngology of Longgang Center Hospital, The Ninth People's Hospital of Shenzhen, Shenzhen, China.

|December 19, 2024

概括

这项研究确定了老年喉状细胞癌 (LSCC) 患者早期死亡的风险因素. 开发了预测性名录,以帮助临床医生个性化治疗计划,以获得更好的结果.

科学领域:

在瘤学瘤学.
老年医学老年医学
生物统计学生物统计学

背景情况:

喉状细胞癌 (LSCC) 的死亡率在60岁左右达到顶峰.
在老年LSCC患者中确定早期死亡风险因素对于有针对性的干预至关重要.

研究的目的:

在老年LSCC患者 (≥60岁) 中识别早期死亡 (6个月内) 的风险因素.
开发用于早期死亡风险评估的预测性名录.
帮助临床医生为老年LSCC患者制定个性化治疗策略.

主要方法:

利用来自监测,流行病学和最终结果数据库的10,031名老年LSCC患者 (2004-2015) 的数据.
采用多重物流回归来识别早期死亡的独立风险因素.
使用决策曲线分析,校准和ROC曲线验证的预测名录.

主要成果:

17.0%的患者因各种原因过早死亡;1,129人死于癌症特定原因.
早期死亡的危险因素包括重叠的病变,晚年,未婚状态,高瘤/节点阶段,远程转移和缺乏治疗.
诺米图的AUC为0.796的全因死亡和0.790的癌症特定死亡,表明良好的预测准确度.

结论:

在老年LSCC患者中,T阶段和放射治疗是早期死亡的强有力的预测因素.
婚姻状况和瘤等级显示出最差的预后值.
开发的诺米图准确预测早期死亡率,为老年LSCC患者提供个性化治疗计划.

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

An R-Based Landscape Validation of a Competing Risk Model

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

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...

Actuarial Approach

Actuarial Approach

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,...