经切除术治疗的细胞癌患者随着时间的推移而改善的生存率:一项纵向倾向性得分匹配研究
Kenjiro Kishitani1, Satoru Taguchi1, Koji Tanaka1
1Department of Urology, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Tokyo, Japan.
概括
最近 (2000 - 2018) 接受细胞癌 (RCC) 手术的患者与早期 (1981 - 1999) 接受治疗的患者相比,经历了显著改善的生存结果. 这种改善可能与越来越多地采用微创手术技术有关.
科学领域:
- 泌尿器科 泌尿器科 泌尿器科 泌尿器科
- 手术瘤学手术瘤学
- 腎臟病學 (nephrology) 是一種醫學專業.
背景情况:
- 在过去的三十年中,细胞癌 (RCC) 治疗发生了显著的进化.
- 在接受切除术的RCC患者中,关于时间生存趋势的现实数据有限.
研究的目的:
- 为了评估细胞癌 (RCC) 患者的存活率改善,在不同手术时代接受了切除术.
- 使用倾向分数匹配 (PSM) 分析纵向队列数据,以比较早期和最近的外科手术期间的结果.
主要方法:
- 对960名经过彻底或部分切除术 (1981-2018) 的RCC患者进行了回顾性审查.
- 患者被分为两组:1981-1999年 (早期时代) 和2000-2018年 (最近的时代).
- 倾向性得分匹配 (PSM) 用于比较整体存活率 (OS),癌症特定存活率 (CSS) 和无复发存活率 (RFS).
主要成果:
- 通过使用PSM获得466名患者 (233名每期) 的匹配队列.
- 最近的时代与早期的时代相比 (全部是开放式手术) 发生了向最小侵入性手术 (47.4%) 的转变.
- 最近的时代队列与早期的时代队列相比,显示了显著更长的OS,CSS和RFS.
结论:
- 在近期 (2000 - 2018) 接受RCC治疗的患者与早期 (1981 - 1999) 相比,表现出更高的生存率.
- 越来越多地采用微创手术方法 (镜/机器人) 是导致RCC治疗中观察到的生存率改善的一个潜在因素.
相关概念视频
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
Kaplan-Meier Approach
102
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,...
102
Comparing the Survival Analysis of Two or More Groups
155
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...
155


