Issues in the Use of Existing Data: As Controls in Pre-Market Comparative Clinical Studies

Abstract

Randomized, well-controlled clinical trials have been viewed as the gold standard in the evaluation of medical products, and observational comparative clinical studies also play an important role in the evaluation in both premarket and postmarket settings. Such observational comparative studies could be concurrent or nonconcurrent depending on the timing when patients get treated. A nonconcurrent control group could be formed from patients with existing data, when indeed appropriate. For example, a control group could come from patients with historical data collected from earlier investigational device exemption (IDE) studies of previously approved medical products or selected from a well-designed and executed registry database. However, the construction of a control group from existing data presents extra challenges compared to the formation of a concurrent control group. In this chapter, some of the design challenges, such as validity of study design, historical control group selection and treatment group comparability, and identification of a control group from an applicable registry database, are discussed and illustrated with examples from regulatory perspectives.

No official support or endorsement by the Food and Drug Administration of this presentation is intended or should be inferred.