Laboratory Results That Should Be Ignored

Dirk M. Elston, MD


October 11, 2006

False-Positive Clinical Pathology Results

Although most laboratory errors relate to the pre- and postanalytic phases, the analytic phase should not be ignored as a source of errors. 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 results.[15] The methodology employed was a sandwich immunoassay that utilized 2 specific monoclonal antibodies. In this assay, the target protein forms a link between the capture and signal antibodies. The assay is known for its high sensitivity and specificity. Unfortunately, heterophilic antibodies can also form links between the capture and signal antibodies, resulting in a false-positive result. Despite test modifications to minimize antibody interference, heterophilic antibody interference still occurs in a wide variety of immunoassays, and false-positive results have led to bad clinical outcomes.[16,17,18,19,20] Because this type of interference is patient-specific, it usually escapes detection by quality assurance systems that focus mainly on the analytic phase of testing. A broader system that addresses the entire testing cycle can improve quality.

False-positive results that result in medical errors occur in a wide variety of laboratory assays. A study of 6370 specimens analyzed by a widely used bacterial latex agglutination test found that only 11 pathogens were accurately detected, whereas there were 13 false negatives and 59 false-positive results. In this study, none of the true positives had a measurable effect on patient outcomes, but several of the erroneous reports resulted in unnecessary treatment.[21] Nonculture tests for detection of Chlamydia trachomatis have advanced the detection of this serious sexually transmitted disease, but have also been complicated by false-positive results. Implicated assays include both enzyme immunoassays and DNA probe tests.[22] The issue of false-positive nucleic acid detection tests for Neisseria gonorrhoeae has prompted recommendations for the reporting of such tests.[23] A major source for such errors is horizontal genetic exchange among Neisseria, resulting in commensal Neisseria acquiring N gonorrhoeae genes.[24] As with other studies, false-positive results are more likely in populations with low disease prevalence.[25] Published recommendations with regard to reporting of nucleic acid detection tests for N gonorrhoeae include the following: Assays for the cppB gene should not be used; all positive screening assays should be confirmed by a reliable supplemental assay before a positive result is reported; and the test combination should yield a positive predictive value of at least 90% in a population with a 1% prevalence.[26] Polymerase chain reaction (PCR) assays offer sensitivity and specificity similar to culture and can be used as confirmatory tests, but may not be suitable for pharyngeal specimens.[27,28,29]

A falsely reported outbreak of methicillin-resistant Staphylococcus aureus was linked to spurious results with an automated test system. Independent laboratory testing with oxacillin agar screen plates, broth microdilution minimal inhibitory concentrations, and assays for the presence of the mec A gene proved that almost three quarters of the organisms initially identified as methicillin-resistant S aureus were actually susceptible to oxacillin. The misclassification resulted in unnecessary vancomycin use.[30] An apparent outbreak of typhoid fever was related to false-positive tests with a hemagglutination method. Most laboratories issuing spurious reports performed the rapid slide agglutination test as opposed to the tube agglutination test.[31] Each of the above examples shares one important feature: Quality improvement programs that focused on the analytic phase of testing failed to detect unacceptable rates of false-positive results. Analysis of patient outcomes ultimately uncovered the errors.


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