英国利益相关者对癌症替代终点的看法,以及英国现实世界数据集在决策中验证其使用的潜力
David Baldwin1, Jonathan Carmichael2, Gordon Cook3
1Department of Respiratory Medicine, Nottingham University Hospitals NHS Trust and the University of Nottingham, Nottingham, UK.
Cancer management and research
|July 24, 2024
概括
癌症研究中的替代终点可以加速新药批准. 使用现实世界英国数据验证这些终点对于临床实践和患者获得创新治疗至关重要.
科学领域:
- 在瘤学瘤学.
- 临床试验 临床试验
- 卫生经济学 卫生经济学
背景情况:
- 癌症的生存率有所提高,需要新的方法来评估早期治疗.
- 作为主要终点的总生存率延迟了创新的癌症治疗方法的采用.
- 患者报告的结果和生活质量是关键因素,通常被忽视的总体存活率.
研究的目的:
- 探索替代终点在英国癌症治疗评估中的相关性.
- 评估现实世界英国数据在验证代用终点方面的潜力.
- 为了加快患者获得新型癌症药物和治疗策略.
主要方法:
- 审查当前的做法和替代终点在癌症药物批准中的监管使用.
- 对将发现推断到不同患者群体的挑战进行分析.
- 在英国探索现实世界的数据收集和证据生成.
主要成果:
- 替代终点越来越多地被考虑,但缺乏明确定义的评估证据标准.
- 目前,使用替代终点的药物的监管批准是根据具体情况进行的.
- 现实世界的英国数据为验证代用终点提供了潜在的途径.
结论:
- 替代终点可能会加速引入新的癌症治疗方法.
- 需要明确的证据标准来接受医疗技术评估中的代用终点.
- 利用现实世界的英国数据可能会提高瘤学中代用终点的验证和临床实用性.
相关概念视频
Cancer Survival Analysis
336
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...
336
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
125
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
125
Kaplan-Meier Approach
119
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,...
119


