Defining ELISpot cut-offs from unreplicated test and control wells

Area of Science:

• Immunology
• Statistical analysis
• Assay development

Background:

• Current enzyme-linked immunospot (ELISpot) positivity criteria lack replication.
• Empirical criteria rely on fixed differences or ratios for spot forming units (SFU) counts.
• A need exists for robust statistical methods in ELISpot data analysis.

Purpose of the Study:

• To propose an alternative statistical approach for determining ELISpot assay positivity.
• To identify an optimally variance-stabilizing transformation for SFU counts.
• To derive a positivity threshold using between-plate distribution functions.

Main Methods:

• Utilized Bland-Altman plots to identify the optimal variance-stabilizing transformation of SFU counts.
• Derived a positivity threshold from the difference in between-plate distribution functions of transformed SFU counts.
• Applied the method to 1309 assay results from an influenza cohort study in Vietnam.

Main Results:

• The proposed method provides an alternative to fixed empirical criteria for ELISpot positivity.
• Demonstrated the application of the statistical approach using real-world assay data.
• Illustrated the method's utility in analyzing immune responses in a cohort study.

Conclusions:

• The developed statistical method offers a more robust approach to defining ELISpot positivity.
• This technique enhances the reliability of immune response data interpretation.
• The findings contribute to improved statistical practices in immunological assays.