Tips on Managing
the Quality of ImmunoassaysThe following examples demonstrate how to apply these tools and thought processes. In each case, the assay is stable, and has a very low frequency of large errors (< 2%). These are real assays from the laboratory, and the QC data represent precision over a period of about 4 months. PT specifications were used for allowable error.
Since there is a single CV criterion for all
concentrations, look for the control with the highest CV. Our
worst CV is 3.34%. Since allowable error (25%) is large relative
to the CV (remember the Westgard-Burnett rule?), it should be
pretty easy to control this method even with 2 control measurements
per run. However other tests on this system are not so easily
controlled and require us to analyze 3 different control materials.
Because people may get confused if you have different numbers
of controls for different tests on the same analyzer, I used the
automatic rule selection feature for 3 materials. As shown by
the OPSpecs chart, even the 13.5s rule has Ped
over 90% for errors which could cause PT failure. I actually chose
the 13s rule because our laboratory computer software
does not allow us to choose the 13.5s. Pfr
is still very low, only 1% or so.
Cortisol also has a fixed PT limit of target value +/- 25%. Our worst CV (low control) is 9.97%. The CV is greater than one third of allowable error.
| The OPSpecs® chart shows that there is very little ability to detect errors that would cause PT failure. The 13s/(2of3)2s/R4s/31s rule with 6 controls barely achieves Ped = 25%. It is critically important to minimize bias in the low concentration range. [Note that this OPSpecs chart is for 25% AQA(SE).] |
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| For three controls in daily runs, Ped for the 13s/(2 of3)2s/R4s rule is 58%, which is acceptable for a method with a low frequency of large errors. |
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In summary, we are OK for cortisol on the average with 3 controls, but we could have problems with PT samples at low concentrations if bias exceeds 0.86 SD, and we have little ability to tell if bias has become too large.
The limit for thyroxine is target value +/- 1.0 mcg/dL for concentrations up to 5.0 mcg/dL, and +/- 20% for concentrations above 5.0 mcg/dL. Cumulative statistics from four months data are shown below for our current lot of tri-level Immunoassay control:
| Level | Mean, mcg/dL | SD, mcg/dL | CV,% |
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Consider performance at low concentrations first. I converted the allowable error of 1.0 mcg/dL to a percentage by dividing it by the concentration of the low control (3.96 mcg/dL) to give 25.2% allowable error. Since the CV is about one-fourth of allowable error, we should be OK here with multirule. I use multirule with N=3, with Ped of 0.70. For an assay with a low frequency of errors, Ped of 0.70 is satisfactory. Even the 13s with Ped of 0.53 would be acceptable. The fixed limit of 1.0 mcg/dL for thyroxine lessens the odds for trouble at low concentrations.
| At higher concentrations, the CV is less than 25% of allowable error, and performance of these QC rules would be even better. |
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When the limit is target value +/- 3 SD, the PT limit is calculated from recent PT data for the method. Group the PT results for a recent period by concentration ranges that correspond roughly to the concentrations of the control materials you are using and/or where you see patterns of similar CVs in the PT data. We used PT data from the 1996 College of American Pathologists K series for Bio-Rad Quantaphase II. The CVs were relatively constant, ranging from 9.3% to 11.1%. The average CV was 10.2%. The PT allowable error is calculated by multiplying the average CV by 3 to give 30.6%. Cumulative control data for folate are as follows for our tri-level immunoassay controls:
| Mean, ng/mL | SD, ng/mL | CV, % |
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Our worst CV is only 14% of allowable error. With 3 controls, the 13.5s rule has Ped exceeding 90% for the critical error.

