Use of Historical Data in Design

Christopher Kim (), Victoria Chia () and Michael Kelsh ()
Additional contact information
Christopher Kim: Amgen Inc.
Victoria Chia: Amgen Inc.
Michael Kelsh: Amgen Inc.

Chapter 49 in Principles and Practice of Clinical Trials, 2022, pp 877-890 from Springer

Abstract: Abstract The goal of clinical research of new disease treatments is to evaluate the potential benefits/risks of a new treatment, which generally requires comparisons to a control group. The control group is selected to characterize what would have happened to a patient if they had not received the new therapy. Although a randomized controlled trial provides the most robust clinical evidence of treatment effects, there may be situations where such a trial is not feasible or ethical, and the use of external or historical controls can provide the needed clinical evidence for granting conditional or accelerated regulatory approvals for novel drugs. Data from previous clinical trials and real-world clinical studies can provide evidence of the outcomes for patients with the disease of interest. However, many methodologic considerations must be considered such as the appropriateness of data sources, the specific data that needs to be collected, application of appropriate inclusion/exclusion criteria, accounting for bias, and statistical adjustment for confounding. This chapter reviews the settings in which the use of historical controls or comparators may be appropriate, as well as study designs, limitations to using real-world comparators, and analytic methods to compare real-world data to clinical trial data. When these considerations are appropriately handled, use of historical controls can have immense value by providing further evidence of the efficacy, effectiveness, and safety in the development of novel therapies and increase efficiency of the conduct of clinical trials and regulatory approvals.

Keywords: Real-world comparators; Real-world evidence; Clinical trials; Controls; Historical comparator; Statistical methods; Propensity score (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-52636-2_69

Ordering information: This item can be ordered from
http://www.springer.com/9783319526362

DOI: 10.1007/978-3-319-52636-2_69

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().