Real-world Data for Clinical Evidence Generation in Oncology
Real-world Data for Clinical Evidence Generation in Oncology
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DOI：
10.1093/jnci/djx187
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发表时间：
2017-11-01
影响因子：
10.3
通讯作者：
Pazdur, Richard
中科院分区：
文献类型：
--
作者：
Khozin, Sean;Blumenthal, Gideon M.;Pazdur, Richard
传统的癌症临床试验可能是缓慢和昂贵的，通常产生的结果具有有限的外部有效性，并且患者很难参与。美国最近的技术进步和动态政策环境为使用真实世界数据（RWD）改进当前的临床证据生成方法创造了肥沃的土壤。RWD的来源包括电子健康记录、保险索赔、患者登记和传统临床试验之外的数字健康解决方案。侧重于在床旁收集数据的原始意图的定义可以将RWD与传统临床试验数据区分开来。当在护理点收集数据的目的是研究时，可以使用与传统临床试验中使用的实验设计类似的实验设计生成RWD，但具有几个优点，包括在内部和外部有效性之间保持适当平衡的情况下有效执行研究。RWD可以支持主动药物警戒、对疾病自然史的深入了解以及外部对照组的开发。前瞻性收集RWD可以基于支持随机研究设计的实用临床试验（PCT）生成证据，并将临床研究扩展到护理点。PCTs可能有助于满足对实验性疗法日益增长的需求，同时增加患者对癌症临床试验的参与。进行有效的真实世界研究需要通过可审计的数据提取方法和新的激励措施来保证数据质量，以推动在护理点电子捕获临床相关数据。
Conventional cancer clinical trials can be slow and costly, often produce results with limited external validity, and are difficult for patients to participate in. Recent technological advances and a dynamic policy landscape in the United States have created a fertile ground for the use of real-world data (RWD) to improve current methods of clinical evidence generation. Sources of RWD include electronic health records, insurance claims, patient registries, and digital health solutions outside of conventional clinical trials. A definition focused on the original intent of data collected at the point of care can distinguish RWD from conventional clinical trial data. When the intent of data collection at the point of care is research, RWD can be generated using experimental designs similar to those employed in conventional clinical trials, but with several advantages that include gains in efficient execution of studies with an appropriate balance between internal and external validity. RWD can support active pharmacovigilance, insights into the natural history of disease, and the development of external control arms. Prospective collection of RWD can enable evidence generation based on pragmatic clinical trials (PCTs) that support randomized study designs and expand clinical research to the point of care. PCTs may help address the growing demands for access to experimental therapies while increasing patient participation in cancer clinical trials. Conducting valid real-world studies requires data quality assurance through auditable data abstraction methods and new incentives to drive electronic capture of clinically relevant data at the point of care.