Statistical Approaches to Analyzing HIV-1 Neutralizing Antibody Assay Data

Abstract

Neutralizing antibody assays are widely used in research toward the development of a preventive HIV-1 vaccine. Currently, the neutralization potency of an antibody is typically quantified by the inhibitory concentration (IC) values (e.g., IC50), and the neutralization breadth is estimated by the empirical method. In this article, we propose the area under the curve (AUC) and the partial area under the curve (pAUC) measures for summarizing the titration curve, which complement the commonly used IC measure. We present multiple advantages of AUC over IC50, which include no complications due to censoring, the capability to explore low-level neutralization, and improved coverage probabilities and efficiency of estimators. We also propose statistical methods for determining positive neutralization and for estimating the neutralization breadth. The simulation results suggest that the AUC measure is preferable in particular as IC50s get closer to the highest concentration of antibodies tested. For the majority of the assay data, the AUC method is more powerful than the IC50 method. However, since these methods test different hypotheses, it is not unexpected that some virus–antibody combinations are AUC positive but IC50 negative or vice versa.

Key Words:

• AUC
• Breadth
• HIV-1
• Neutralization assay
• Polynomial model
• Titration curve

Acknowledgments

This work is supported in part by the Bill & Melinda Gates Foundation, the Statistical Issues in AIDS Research Grant (R01: 5 R37 AI029168-21), NIH AI36085, and Research Funds from the Department of Veterans Affairs.