Response definition criteria for ELISPOT assays revisited.
No consensus has been reached on how to determine if an immune response has been detected based on raw data from an ELISPOT assay. The goal of this paper is to enable investigators to understand and readily implement currently available methods for response determination. We describe empirical and statistical approaches, identifying the strengths and limitations of each approach to allow readers to rationally select and apply a scientifically sound method appropriate to their specific laboratory setting. Five representative approaches were applied to data sets from the CIMT Immunoguiding Program and the response detection and false positive rates were compared. Simulation studies were also performed to compare empirical and statistical approaches. Based on these, we recommend the use of a non-parametric statistical test. Further, we recommend that six medium control wells or four wells each for both medium control and experimental conditions be performed to increase the sensitivity in detecting a response, that replicates with large variation in spot counts be filtered out, and that positive responses arising from experimental spot counts below the estimated limit of detection be interpreted with caution. Moreover, a web-based user interface was developed to allow easy access to the recommended statistical methods. This interface allows the user to upload data from an ELISPOT assay and obtain an output file of the binary responses.
Moodie
Z
Z
Statistical Center for HIV/AIDS Research and Prevention (SCHARP), Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
Price
L
L
Gouttefangeas
C
C
Mander
A
A
Janetzki
S
S
Löwer
M
M
Welters
M J P
MJ
Ottensmeier
C
C
van der Burg
S H
SH
Britten
Cedrik M
CM
D005189:False Positive Reactions; D006801:Humans; D007124:Immunoenzyme Techniques / Q000379:methods / Q000706:statistics & numerical data; D012015:Reference Standards; D012680:Sensitivity and Specificity