Impact of Case Definitions on Efficacy Estimation in Clinical Trials-A Proof-of-Principle Based on Historical Examples

Abstract

Efficacy estimations in clinical trials are based on case definitions. Commonly, they are a more or less complex set of conditions that have to be fulfilled in order to define a clinical case. In the simplest variant, such a case is identical with a single positive diagnostic test result. Frequently, however, case definitions are more complex. Further, their conditions often ignore the inherent logical structure of symptoms and disease: A symptom or a set of symptoms may be necessary but not sufficient for the unambiguous identification of a case. After describing the structure of case definitions and its impact on efficacy estimations, we exemplify this impact using data from two clinical trials dealing with the effectiveness of the vaginal application of tenofovir gel for the prevention of HIV infections and with the therapeutic effects of fecal transplantation on recurrent Clostridium difficile infections. We demonstrate that the diagnostic performance of case definitions affects efficacy estimations for interventions in clinical trials. The potential risk of bias and uncertainty is high, irrespective of the complexity of the case definition. Accordingly, case definitions in clinical trials should focus on specificity in order to avoid the risk of bias.

Keywords: case definition; clinical trial; efficacy estimation; specificity.

Figure 1

Adjusted efficacy estimates (y-axis) depending on endpoint specificity (x-axis) applying Equation (7) with 0.95 confidence intervals and using Equation (9) for the primary endpoint of the CAPRISA 004 trial.

Figure 2

Adjusted efficacy estimates (y-axis) depending on endpoint specificity (x-axis) applying Equation (7) with 0.95 confidence intervals and using Equation (9) for the primary endpoint of the study by van Nood and colleagues on the effects of fecal transplantation for the treatment of recurrent Clostridium difficile infections.