A statistically defined endpoint titer determination method for immunoassays

Abstract

Results of immunoassays for which no positive standards are available are often expressed as endpoint titers. The endpoint titer is defined as the reciprocal of the highest analyte dilution that gives a reading above the cutoff. Unfortunately, there is no generally accepted rule for the determination of these cutoff values. In enzyme-linked immunosorbent assays (ELISA) a value two or three times the mean background or negative control reading is sometimes used. Other investigators set the cutoff arbitrarily at a certain absorbance value. These procedures do not provide statistically meaningful information about the risk of overtitration or false low titers. We have solved this problem by devising a practical method for establishing a statistically valid cutoff. The procedure involves calculating the upper prediction limit using the Student t-distribution. The mathematical formula which defines the upper prediction limit is expressed as the standard deviation multiplied by a factor which is based on the number of negative controls and the confidence level (1 - alpha). Appropriate factors are provided for 2 to 30 negative controls and for confidence levels ranging from 95% to 99.9%. Our new method is more reliable than other nonstatistical procedures yet does not require sophisticated computation. It can be applied to a variety of immunoassays provided that negative controls are available.