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Dilution Protocols for Detection of Hook Effects/Prozone Phenomenon

  1. Anthony W. Butch
  1. University of Arkansas for Medical Sciences, Department of Pathology, 4301 West Markham, Little Rock, AR 72205

To the Editor:

The prozone or (high-dose) hook effect, documented to cause false-negative assay results >50 years ago (1), still remains a problem in one-step immunometric assays (2)(3)(4)(5)(6)(7)(8)(9), immunoturbidimetric assays (10), and immunonephelometric assays (11) for immunoglobulins. To detect the prozone effect, samples are often tested undiluted and after dilution (9). If the result on dilution is higher than for the undiluted sample, then the undiluted sample most likely exhibited the prozone effect. Unfortunately, this approach increases labor and reagent costs for assays that may only rarely encounter extremely high analyte concentrations. An alternative approach involves pooling patient samples and measuring the pool and a 10-fold dilution of the pool (12). If one or more of the samples in the pool is falsely low because of the prozone effect, then the results from the undiluted and diluted pools (after correcting for the 10-fold dilution) will differ significantly (12).

Other approaches to eliminate the prozone effect include using two-step immunoassays that have a wash step between the addition of sample and labeled antibody (7) and the use of neural network classifier systems that analyze reaction kinetics (13).

Serum immunoglobulins can be markedly increased in patients presenting with large myeloma tumor burdens and may lead to falsely low results in nephelometric assays (11). We combine 50-μL aliquots from each of 10 samples to dilute each sample 10-fold and eliminate any prozone effect. The concentrations of IgG, IgA, and IgM in the pool are measured using a nephelometer (BNII; Dade Behring, Inc.) and compared with the mean values when all samples in the pool are analyzed (calculated value). When the two values for an immunoglobulin differ by a specified quantity, all samples in the pool are reanalyzed after a 10-fold dilution.

Criteria for detecting the prozone effect are based on data obtained from routine samples during a 10-day period. Measured immunoglobulin concentrations for 27 pools (10 samples per pool) were compared with the mean values of samples in the pools. The range of values for the measured serum pools and the differences between the measured pool value and the value derived from the mean of individually measured samples in the pool (calculated value) for each immunoglobulin were as follows: IgG, range 10.20-32.50 g/L, mean difference 4.6%, SD 4.1%; IgA, range 0.31-17.90 g/L, mean difference 12.6%, SD 8.6%; and IgM, range 0.27-5.96 g/L, mean difference 13.2%, SD 8.2%. The small SD indicated that none of the samples exhibited the prozone effect. A percentage difference less than the mean plus 2 SD was considered acceptable and was determined to be 15% for IgG, 30% for IgA, and 30% for IgM. Large differences were considered suggestive of a prozone effect.

The ability of this approach to identify samples exhibiting the prozone effect during routine analysis was evaluated during a 6-month period. Approximately 750 samples/month were received, and 460 pools were analyzed. Ten samples from five different myeloma patients were identified as being falsely low because of the prozone effect (Table 1 ). Four samples were from patients with IgA myeloma, and one was from a patient with IgG myeloma. The discrepancy between the measured and calculated pool was 62-88% (initial difference; Table 1 ). When the sample generating the erroneous value was identified and the “correct” result (obtained after dilution) was used in the calculation, the difference between the measured and calculated pool was within the established limits of 30% for IgA and 15% for IgG (corrected difference; Table 1 ). The falsely low values differed from the actual results by as much as 11-fold for IgA and 40-fold for IgG (Table 1 ). The prozone effect is not restricted to IgA and IgG because we identified samples exhibiting this phenomenon when measuring IgM (data not shown).

Table 1.

Detection of the prozone effect in nephelometric assays for immunoglobulin (Ig) by monitoring the percentage of difference between measured and calculated pool values.

A 2% incidence (1 of 46 pools) for the prozone effect when measuring immunoglobulins may be higher than at institutions not specializing in the treatment of multiple myeloma. However, the incidence of multiple myeloma over the age of 25 is 30 per 100 000 (14), and most laboratories will eventually encounter a sample exhibiting the prozone effect when measuring immunoglobulins by nephelometry. Reporting of an erroneous result can have serious medical implications, and sample pooling is a simple method for detecting falsely low concentrations attributable to the prozone effect. Although this screening approach increases reagent costs by 10% and involves additional labor to prepare and analyze pools, it is considerably more cost-effective than analyzing all samples undiluted and after dilution, which doubles reagent costs. Furthermore, this simple prozone detection method can be adapted to other nephelometric assays with the potential for erroneous results from antigen excess.

Footnotes

  • 1 Result was obtained for either IgA or IgG depending on the myeloma class.

  • 2 Samples were diluted 10-fold before re-analysis.

  • 3 An aliquot (50 μL) from 10 samples was combined and assayed. The measured value for the pool was compared with the sum of the 10 individual measurements divided by 10. The percentage of difference between the two values is shown.

  • Address correspondence to this author at: UCLA Medical Center, Department of Pathology and Laboratory Medicine, 10833 Le Conte Ave., Mailroom A2-179 CHS, Los Angeles, CA 90095-1713. Fax 310-794-4864; e-mail abutch{at}mednet.ucla.edu

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