不准确的临床阶段是常见的,并且与肺癌患者的生存率低下有关
Lauren M Poston1, Aria Bassiri2, Jacqueline Kloos1
1Case Western Reserve University School of Medicine, Cleveland, Ohio.
The Journal of surgical research
|June 27, 2024
概括
不准确的临床分期影响了接受手术的三分之一的肺癌患者,导致生存结果较差. 提高分期精度对于更好的患者预后和治疗计划至关重要.
科学领域:
- 在瘤学瘤学.
- 胸部外科手术 胸部外科手术
- 癌症的分期 癌症的分期
背景情况:
- 准确的临床分期对于肺癌治疗和预后至关重要.
- 临床和病理阶段之间的差异可能会影响患者的治疗结果.
- 了解影响分期精度的因素对于质量改进至关重要.
研究的目的:
- 为了确定非小细胞肺癌 (NSCLC) 患者的不准确临床分期率.
- 确定与临床分期不准确性相关的风险因素.
- 评估分期不准确对NSCLC患者整体存活时间的影响.
主要方法:
- 来自国家癌症数据库 (2004-2020) 的255,598名NSCLC患者的回顾性队列研究.
- 患者根据临床阶段与病理阶段的准确性进行分类.手术后切除.
- 多变量模型分析了不准确性和与整体存活率相关的风险因素.
主要成果:
- 33.1%的患者 (84,543) 的临床分期不准确.
- 较高的T类,N类,评估的淋巴结增加和广泛的切除是不准确的风险因素.
- 机器人手术与较低的不准确率 (OR=0.89) 有关.
- 不准确的分期与更糟糕的整体存活率显著相关 (5年存活率:67.5%准确与55.4%不准确;HR=1.3).
结论:
- 临床分期的不准确性很普遍,影响了手术治疗的三分之一的肺癌患者.
- 低阶段和超级阶段都与较低的生存率有关.
- 质量改善工作应优先提高临床肺癌分期的准确性.
相关概念视频
01:21Cancer Survival Analysis
342
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...
342
01:24Kaplan-Meier Approach
127
The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
127
01:20Actuarial Approach
74
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,...
74