在局部晚期或转移性胆道癌的治疗模式和生存率使用SEER医疗保险数据
Mark D Danese1, Kabir Mody2, Ramya Thota3
1Outcomes Insights Inc, Agoura Hills, California.
Gastro hep advances
|August 12, 2024
概括
晚期胆道癌 (BTC) 的治疗具有挑战性,存活率很低,没有标准的二线治疗. 这项研究分析了BTC患者的治疗模式和结果,突出了生存差异.
科学领域:
- 在瘤学瘤学.
- 癌症研究 癌症研究
- 临床治疗学 临床治疗学
背景情况:
- 胆道癌 (BTC) 是一种罕见的,侵略性的恶性瘤,通常在晚期诊断.
- 目前先进的BTC的第一线治疗是gemcitabine加 cisplatin,但缺乏标准的第二线治疗.
- 不断变化的治疗环境包括针对可操作突变的疗法.
研究的目的:
- 描述局部晚期或转移性BTC患者的治疗模式.
- 分析与高级BTC治疗策略相关的整体存活率.
- 确定影响晚期胆道癌患者生存的因素.
主要方法:
- 对监测,流行病学和最终结果 (SEER) 医疗保险数据库 (2010-2015) 的回顾性分析.
- 包括2063名患有初级晚期或转移性BTC的患者.
- 对患者特征,治疗线和整体存活率的分析.
主要成果:
- 只有45.5%的患者在诊断后90天内开始全身治疗.
- 在一线治疗后,死亡是最常见的事件.
- 平均存活时间有显著的变化,从5.0个月 (二线胺) 到9.7个月 (二线胺).
结论:
- 高级BTC的整体存活率很差,受到各种人口和临床因素的影响.
- 由于缺乏共识标准,高级BTC的二线治疗的治疗模式不一致.
- 需要进一步的研究,以建立有效的二线治疗策略,以治疗晚期胆道癌症.
更多相关视频
相关概念视频
Cancer Survival Analysis
334
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...
334
Targeted Cancer Therapies
7.5K
The targeted cancer therapies, also known as “molecular targeted therapies,” take advantage of the molecular and genetic differences between the cancer cells and the normal cells. It needs a thorough understanding of the cancer cells to develop drugs that can target specific molecular aspects that drive the growth, progression, and spread of cancer cells without affecting the growth and survival of other normal cells in the body.
There are several types of targeted therapies against...
There are several types of targeted therapies against...
7.5K
Kaplan-Meier Approach
115
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,...
115


