时间对历史红线和乳腺癌存活率之间的关联的影响
Sarah M Lima1,2, Tia M Palermo1,3, Lili Tian4
1Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, New York, USA.
Cancer
|February 9, 2026
概括
乳腺癌存活率的历史红线差异随着时间的推移而缩小,特别是在早期瘤中. 然而,激素受体阳性病例的生存差距扩大,这表明获得治疗进展的机会不平等.
科学领域:
- 在瘤学瘤学.
- 公共卫生 公共卫生
- 健康差距 研究 研究 研究 研究
背景情况:
- 从20世纪30年代开始的歧视性住房政策 - - 历史性的红线划定,与较差的乳腺癌生存结果有关.
- 目前尚不清楚这些生存差异是否随着乳腺癌治疗的进步和红线实施以来的时间流逝而演变.
研究的目的:
- 这项研究旨在调查从1995年到2019年的历史红线和全因乳腺癌存活率之间的关系的时间变化.
主要方法:
- 分析了135,827名乳腺癌患者的队列,这些患者在1995年至2019年期间在纽约州被诊断出乳腺癌.
- 根据诊断时的人口普查通道,患者根据历史红线分级 (A-D) 分类.
- 根据阶段,激素受体状态和种族/种族分层的Cox比例危险模型被用于评估生存率和测试红线级别和诊断时间段之间的相互作用.
主要成果:
- 观察到历史红线和乳腺癌存活时间之间的显著相互作用 (p < .0001).
- 在最高 (D) 和最低 (A) 降红等级之间的生存差异在1995-1999年是最明显的,并在2005-2009年减少.
- 虽然差异在局部和区域瘤中普遍缩小,但随着时间的推移,它们在激素受体阳性瘤中扩大. 在所有种族/民族群体中都注意到时间效应.
结论:
- 历史红色和乳腺癌存活率之间的关联随着时间的推移而变化,整体差异倾向于减少.
- 这些发现表明,不同时期和不同患者亚组对乳腺癌治疗进展的差异性访问有助于观察到的生存差距.
相关概念视频
Cancer Survival Analysis
774
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...
774
Survival Curves
726
Survival curves are graphical representations that depict the survival experience of a population over time, offering an intuitive way to track the proportion of individuals who remain event-free at each time point. These curves are widely used in fields such as medicine, public health, and reliability engineering to visualize and compare survival probabilities across different groups or conditions.
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
726
Survival Tree
433
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
Building a Survival Tree
Constructing a...
Building a Survival Tree
Constructing a...
433
Associative Learning
1.4K
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
Classical conditioning, also known...
1.4K
Association Areas of the Cortex
9.5K
Association areas are regions of the cerebral cortex that do not have a specific sensory or motor function. Instead, they integrate and interpret information from various sources to enable higher cognitive processes such as memory, learning, and decision-making. Some key association areas include the following:
Prefrontal Association Area: This area is located in the frontal lobe and is involved in planning, decision-making, and moderating social behavior. It connects with primary motor areas,...
Prefrontal Association Area: This area is located in the frontal lobe and is involved in planning, decision-making, and moderating social behavior. It connects with primary motor areas,...
9.5K
Introduction To Survival Analysis
812
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...
812


