Real World Data Studies of Antineoplastic Drugs: How Can They Be Improved to Steer Everyday Use in the Clinic?

IF 2.3 Q2 MEDICINE, GENERAL & INTERNAL Pragmatic and Observational Research Pub Date : 2023-01-01 DOI:10.2147/POR.S395959
Gincy George, Beth Russell, Anne Rigg, Anthony C C Coolen, Mieke Van Hemelrijck
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Abstract

There is a growing interest in real world evidence when developing antineoplastic drugs owing to the shorter length of time and low costs compared to randomised controlled trials. External validity of studies in the regulatory phase can be enhanced by complementing randomised controlled trials with real world evidence. Furthermore, the use of real world evidence ensures the inclusion of patients often excluded from randomised controlled trials such as the elderly, certain ethnicities or those from certain geographical areas. This review explores approaches in which real world data may be integrated with randomised controlled trials. One approach is by using big data, especially when investigating drugs in the antineoplastic setting. This can even inform artificial intelligence thus ensuring faster and more precise diagnosis and treatment decisions. Pragmatic trials also offer an approach to examine the effectiveness of novel antineoplastic drugs without evading the benefits of randomised controlled trials. A well-designed pragmatic trial would yield results with high external validity by employing a simple study design with a large sample size and diverse settings. Although randomised controlled trials can determine efficacy of antineoplastic drugs, effectiveness in the real world may differ. The need for pragmatic trials to help guide healthcare decision-making led to the development of trials within cohorts (TWICs). TWICs make use of cohorts to conduct multiple randomised controlled trials while maintaining characteristics of real world data in routine clinical practice. Although real world data is often affected by incomplete data and biases such as selection and unmeasured biases, the use of big data and pragmatic approaches can improve the use of real world data in the development of antineoplastic drugs that can in turn steer decision-making in clinical practice.

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抗肿瘤药物的真实世界数据研究:如何改进它们以指导临床的日常使用?
由于与随机对照试验相比,开发抗肿瘤药物的时间更短,成本更低,因此人们对现实世界证据的兴趣越来越大。监管阶段研究的外部有效性可以通过用真实世界的证据补充随机对照试验来增强。此外,使用真实世界的证据确保纳入通常被排除在随机对照试验之外的患者,如老年人、某些种族或来自某些地理区域的患者。这篇综述探讨了将真实世界的数据与随机对照试验相结合的方法。一种方法是使用大数据,特别是在研究抗肿瘤药物时。这甚至可以为人工智能提供信息,从而确保更快、更精确的诊断和治疗决策。实用试验也提供了一种方法来检验新型抗肿瘤药物的有效性,而不回避随机对照试验的好处。设计良好的实用试验采用简单的研究设计,样本量大,设置多样,可以产生高外部效度的结果。虽然随机对照试验可以确定抗肿瘤药物的疗效,但在现实世界中的有效性可能有所不同。需要实用的试验来帮助指导医疗保健决策,这导致了队列试验(TWICs)的发展。TWICs利用队列进行多个随机对照试验,同时在常规临床实践中保持真实世界数据的特征。尽管真实世界的数据经常受到不完整数据和偏差(如选择和未测量偏差)的影响,但大数据和实用方法的使用可以改善抗肿瘤药物开发中真实世界数据的使用,从而指导临床实践中的决策。
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来源期刊
Pragmatic and Observational Research
Pragmatic and Observational Research MEDICINE, GENERAL & INTERNAL-
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期刊介绍: Pragmatic and Observational Research is an international, peer-reviewed, open-access journal that publishes data from studies designed to closely reflect medical interventions in real-world clinical practice, providing insights beyond classical randomized controlled trials (RCTs). While RCTs maximize internal validity for cause-and-effect relationships, they often represent only specific patient groups. This journal aims to complement such studies by providing data that better mirrors real-world patients and the usage of medicines, thus informing guidelines and enhancing the applicability of research findings across diverse patient populations encountered in everyday clinical practice.
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