Dr David Howdijam MD
While many of today’s diagnostic tests are accurate, false positive or false negatives in results do occur at times and are very much a part of a laboratory’s normal output.When the result of a screening test comes back as positive, there are protocols in place to follow it up with a confirmatory test. Noscreening test is totally accurate (with 100% sensitivity and specificity), and false negative or false positive results will occur despite the best laboratory practices.
What is a false positive test result?
A false positive is where a patient receives a positive result for a test, when he should have received a negative result. This almost bizarre result is called a “false positive” error. The false alarm can be somewhat unsettling for a patient, but one needs to understand why such results occur. Some examples of false positives are:
· A pregnancy test is positive, when in fact you aren’t pregnant.
· A screening test for HIV, Hepatitis B or Hepatitis C virus comes back positive, when you don’t have the virus.
· A cancer screening test comes back positive, but you don’t have the disease.
· A prenatal test comes back positive (or high risk) for Down’s syndrome, when there’s no abnormality with the foetus.
What is a false negative test result?
A false negative is where a negative test result is wrong. In other words, you get a negative test result, but you should have got a positive test result. Examples of false negatives are:
· A pregnancy test comes back as negative (not pregnant) when in fact, you are pregnant.
· A screening test for cancer comes back as negative when in reality, you already have the disease.
· A screening test for HIV, Hepatitis B or Hepatitis C virus comes back negative, when you already have the virus.
Just about every medical test comes with the risk of a false negative result. However, there are problems created by false negative results because of false reassurance leading to diagnostic delay and subsequent treatment.
What causes false positives?
Depending on what a person is being tested for, false positives can occur for several reasons. For instance, with tests used to diagnose syphilis (such as the rapid plasma reagin test), common causes of false positive include acute viral and bacterial illness and pregnancy status of the person. Further, some vaccinations and prescription drugs can occasionally cause a person to test positive for a disease when he does not have it.
What causes false negatives?
Due to certain reasons, some tests can have false negative results. For instance, a rapid pregnancy test might give a false negative result because it was conducted too early or because the urine wasover-diluted. In infectious diseases like HIV or Hep C, most false negative results occur during the “window period” – the time after the infection but before the immune system has developed antibodies. During this period, an ELISA test to detect antibodies will come out negative because there are no antibodies to detect. The crux of a false negative scenario is that in most cases, an ELISA test will be conducted for screening purposes and thus missing the chance to detect the virus accurately. Hence, if a person had been exposed to risks, then it makes sense to repeat the test after a few months or to conduct a more conclusive, confirmatory test.
Double checking protocols: Because tests differ, the reason behind an inaccurate result and the rate at which they happen depend on the test and on the follow-up protocol used to double-check test results. This is the reason why all screening tests always have confirmatory tests to double-check the results. Both screening and confirmatory tests need to give similar results, in order for a person to be given positive or negative result.
Sensitivity and specificity of tests: The usefulness of a diagnostic test or the ability to detect a person with disease or exclude a person without disease is described by its sensitivity and specificity. The sensitivity of a test is defined as the proportion of people with disease who will have a positive result. For example, if in a hypothetical population, 8 out of 10 with disease A throws up positive result, then the sensitivity of the test is 8/10 or 80%. This means that the sensitivity of a test only tells us how good the test is for identifying people with disease when only looking at those with disease. The specificity of a test is the proportion of people without the disease who will have a negative result. If in a population of 90 people who do not have disease A, only 85 people show negative result, then the specificity of the test is 85/90 = 94%. Specificity tells us nothing about whether or not some people with disease would also have negative result and, if so, in what proportion.
Conclusion: No screening test is cent percent accurate. Because of the unique nature of most infectious diseases, there is a need for an increased awareness level among people of the nature of the diagnostic test involved and the potential faulty result it might throw up. This is to prevent misinformation from spreading and also to stress upon the need for a follow up test for persons already exposed to risk situations.
(The writer is Consultant Pathologist, BABINA Diagnostics, Imphal)
Dr David Howdijam MD