Novel Superiority Tests for Anti-Infective Drug Trials: Three Examples

ABSTRACT

Follmann, Brittain, and Powers in 2013 proposed a method for demonstrating efficacy in the context of noninferiority trials of anti-infective drugs by identifying a subset of the population where the new drug is superior to the active control drug. Minimum inhibitory concentration, a pharmacometric value based on a drug’s test tube performance on a patient’s baseline sample (e.g., blood, sputum, etc.), predicts clinical efficacy in that patient for that drug. Using these predictions, the superiority test focused on patients with both high predicted efficacy to the new drug and low predicted efficacy to the control drug. Simulations indicated this can be a powerful approach to demonstrate efficacy. We now apply this strategy to analyze three datasets submitted to the FDA. We incorporated enhancements: (i) another pharmacometric measure, area under the curve of drug concentration, to improve outcome prediction, (ii) different tests, and (iii) analogous analyses based on the pharmacometric parameter in the active control drug alone. Superiority for some patient subset was shown in two of the three datasets. This superiority testing approach can eliminate the need for historical data about the magnitude of the active control drug's benefit, guide drug selection for individual patients, develop drug resistance thresholds, and validate assay sensitivity.

KEYWORDS:

• Anti-infective drugs
• Noninferiority trials
• Pharmacodynamics

Acknowledgments

This work was done as part of a collaborative agreement between NIAID and the Center for Drug Evalution of FDA. The authors acknowledge many at FDA who provided helpful advice: including Lisa LaVange, Daphne Lin, Daniel Rubin, Dionne Price, Kimberly Bergman, Yaning Wang, Thamban Valappil, and Mohammad Huque. The authors are very grateful to FDA providing them the clinical trial data used in their analysis, and allowing them to publish these results. The authors also thank their colleague Michael Proschan for a detailed review of this article.