在老年人群中对骨底部和骨-骨带瘤的基于人口生存分析:2000-2021年
Taylor Furst1, Muhammad I Jalal1, Suyash Sau1
1Department of Neurological Surgery, University of Rochester Medical Center, 601 Elmwood Ave, Rochester, NY 14642, USA.
概括
外科手术可能不会改善老年冠状腺瘤患者的生存率. 老年患者的存活时间比成年人要短得多,在20多年中所观察到的改善很小.
科学领域:
- 在瘤学瘤学.
- 老年医学 老年医学
- 手术瘤学手术瘤学
背景情况:
- 胆瘤是一种具有攻击性的骨瘤,通常会影响神经骨区域和骨底部.
- 手术切除是标准的,但会造成显著的生理压力,特别是对于老年患者.
- 由于伴随性疾病和治疗耐受性,老年人胆瘤的管理存在独特的挑战.
研究的目的:
- 分析老年冠状瘤患者 (65岁以上) 的生存趋势和结果.
- 为了比较老年和成年chordoma队伍之间的生存率.
- 评估手术干预对这一群体生存的影响.
主要方法:
- 使用了监测,流行病学和最终结果 (SEER) 数据库 (2000-2021).
- 包括380例冠状瘤病例 (128例头骨底部,252例骨-骨) 在65岁以上的患者中.
- 进行了卡普兰-梅尔生存分析和多变量考克斯回归,包括老年人与成人队列的子组分析.
主要成果:
- 不进行手术与改善的瘤特异性存活率相关 (HR=0.49,p=0.016).
- 外科手术没有显著影响全因生存率或初级特异性全因生存率.
- 与成年患者 (187.6个月) 相比,老年性心脏瘤患者的生存时间 (89.2个月) 显着较短.
结论:
- 在过去的20年里,老年性心脏瘤存活率的微小改善发生了.
- 老年人手术后生存率的恶化可能与疾病在呈现时的晚期或延迟治疗不那么晚期的病例有关.
- 进一步的研究至关重要,以加强医疗和手术疗法,以改善老年患者的冠状腺瘤结果.
相关概念视频
01:21Cancer Survival Analysis
311
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...
311
01:20Actuarial Approach
49
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,...
49
01:20Comparing the Survival Analysis of Two or More Groups
99
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
99
01:18Introduction To Survival Analysis
142
Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time...
The primary goal of survival analysis is to estimate survival time—the time...
142
01:24Kaplan-Meier Approach
62
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,...
62
01:15Assumptions of Survival Analysis
75
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.
75