False-Positive Test Results: Ramification and Prevention
March 25, 2009 at 12:02 am 1 comment
A false-positive test result is one that appears to detect a disease (analyte) when in fact it is not present. A false-positive test result may thus suggest that a person has the disease when he or she does not.
False-positive results that result in medical errors occur in a wide variety of laboratory assays. In an enzyme-linked immunoassay (ELISA), false positive can occurs from the interferences caused by heterophilic antibodies (antibodies that are able to bind to animal antibodies used in immunochemistry assays) present in patient samples. The most common heterophilic antibodies are know as human anti-mouse antibodies (HAMA).
A person can develop HAMA for different reasons. The clinical use of monoclonal mouse antibodies (e.g., for radioimaging, in the treatment of some cancers) often produces HAMA. HAMA may also arise because of incidental or occupational exposure to foreign proteins (e.g. veterinarians, farm workers, food preparers) or due to the presence of domestic animals in the home environment. Blood transfusion and dialysis are among other sources of heterophilic antibodies.
Assay developers (scientists) at Calbiotech are very much aware of this phenomenon and all our immunoassay products are extensively screened with previously identified panels of heterophilic samples before releasing them into market.

Figure 1. (A) Showing the formation of sandwich complex in the presence of an analyte (true positive) and (B) in the absence of an analyte (false positive).
Modern laboratories use highly specific, sensitive methods that generally result in reliable results. Because of this, clinicians place great faith in the results that they receive, and false-positive results frequently result in a cascade of unnecessary testing and treatment. One widely publicized example involved a 22-year-old woman who underwent both surgery and chemotherapy on the basis of multiple false-positive human chorionic gonadotropin (hCG) results.1 The methodology employed was a sandwich immunoassay that utilized two specific monoclonal antibodies. In this assay, the target protein (analyte) forms a link between the capture and detection antibodies (Fig. 1, A). The assay is known for its high sensitivity and specificity. Unfortunately, the presence of high titers of these antibodies may lead to analytical errors in commonly used “sandwich” immunoassays by cross-linking the capture and detection antibodies (Fig. 1, B) in the absence of a specific analyte.2,3
At Calbiotech different kinds of blockers are employed to prevent the occurrence of this type of phenomenon. Contrast
The following figure demonstrates the sharp contrast between an assay with and with out heterophilic blockers. A previously identified heterophilic serum sample (ID # D29) was tested in CA 125 ELISA kit with and without blockers.

Figure 2. Showing the action of three different Calbiotech heterophile blockers in CA 125 ELISA kit testing a donor with heterophilic serum sample.
Think of what would happened to this innocent donor if, by any chance, the sample was tested by other immunoassay kit in the market that do not employ any heterophilic blocker reagent. This false positive could have lead to unnecessary treatments like surgery, chemotherapy and radiations. False positive test result has a psychological cost too.4
Calbiotech blockers are special type of active reagents that block the heterophilic interaction by binding to the heterophilic antibodies.
References
1. White GH. Trusting numbers: uncertainty and the pathology laboratory. MJA. 2002, 177, 153-155.
2. Levinson SS, Miller JJ. Toward a better understanding of heterophile(and the like) antibody interference with modernimmunoassays. Clin Chem Acta 2002, 325, 1-5.
3. Marks V. False-positive immunoassay results: a multicenter survey of erroneous immunoassay results from assays of 74 analytes in 10 donors from 66 laboratories in seven countries. Clin Chem 2002, 48, 2008-16.
4. McNaughton-Collins M, et al. Psychological effects of a suspicious prostate cancer screening test followed by a benign biopsy result. Am J Med 2004, 117, 719-25.
Entry filed under: Calbiotech Services, Tips. Tags: customized immunoassays, ELISA, lumELISA, Research.
1.
Gautam | March 25, 2009 at 12:55 am
From a clinical point of view, it is very important to understand the concept of sensitivity and specificity of a test and how it ties in with false positives and false negatives –
Sensitivity: Suppose 20 subjects were screened for a test. In reality all 20 did have the disease but the test came out positive for only 16 people. (This test failed to catch 4 people who had the disease). We would say that the test showed 4 False Negative tests. Therefore this test was only 80 % Sensitive.
Sensitivity =
(True Positives) / (True Positives + False Negative)
So obviouslya good diagnostic test must have a high sensitivity – otherwise one will “miss” diagnosing those with disease. Imagine informing a person with HIV – that they are free of disease!
Specificity:
Now suppose 20 people were tested for a disease and all 20 tested positive for that disease in the test. But lets assume that in reality, only 16 people had the disease. The other 4 might have some other condition, eg heterophilic antibodies – that gave False Positives. So this is also not a very pleasant situation eithe. If a test has a low Specificity, it is not reliable because it will give False Positive results.
Specificity =
(True Negatives) / (True Negative + False Positive)
An example of a test that is not very specific is VDRL and RPR (syphilis diagnostic tests) because it has been clinically observed that these tests show positive results even for patients with SLE (systemic lupus erythematosus).
In general
Sensitivity = probability of a positive test among patients with disease
Specificity = probability of a negative test among patients without disease
Clinical tests need to be carefully balanced to give an optimal range of Sensitivity and Specificity. It is important to learn about Reciever Operator Characteristics (ROC) curves that link false positives and false negatives in a clinical test. A good description for ROC can be obtained from
http://en.wikipedia.org/wiki/Receiver_operating_characteristic