Statistical approaches to analyzing HIV-1 neutralizing antibody assay data

Area of Science:

• Immunology
• Vaccinology
• Biostatistics

Background:

• Neutralizing antibody assays are crucial for developing a preventive HIV-1 vaccine.
• Current methods quantify neutralization potency using inhibitory concentration (IC) values (e.g., IC50) and breadth empirically.

Purpose of the Study:

• To introduce and validate Area Under the Curve (AUC) and partial AUC (pAUC) as complementary measures for antibody neutralization assays.
• To demonstrate the advantages of AUC over traditional IC50 for assessing neutralization potency and breadth.

Main Methods:

• Proposed AUC and pAUC measures for summarizing antibody titration curves.
• Developed statistical methods for determining positive neutralization and estimating neutralization breadth.
• Conducted simulation studies to compare AUC and IC50 performance.

Main Results:

• AUC offers advantages over IC50, including handling data censoring, exploring low-level neutralization, and providing improved estimator efficiency.
• Simulation results indicate AUC is preferable, especially when IC50s approach the maximum antibody concentration tested.
• The AUC method demonstrates greater statistical power than the IC50 method for most assay data.

Conclusions:

• AUC and pAUC provide a more robust and informative approach to quantifying antibody neutralization for HIV-1 vaccine research.
• These novel measures enhance the assessment of neutralization potency and breadth, complementing existing methods.
• While AUC and IC50 test different hypotheses, AUC generally offers superior performance in evaluating neutralization data.