Understanding evidence-based medicine in 4 days. Lesson 3: Putting tests to the test
So much of modern medicine is about tests and making diagnoses on the basis of the results, that old school doctors often lament the death of the stethoscope and the traditional clinical skills of the physician. Not only are patients entering hospitals and general practices immediately hit by a battery of X-rays, blood tests, scans and other specialised tests; many tests are available for home use by the patients themselves, e.g. home glucose monitoring, home ultrasound probes for antenatal scans and electronic blood pressure meters. Both patients and doctors often make the mistake of assuming that a test is 100% trustworthy and accurate, but we should always ask how good a test is at picking up OR ruling out what it is meant to. The result from a test is only as good as the test itself, and the person using the test. There have been warnings against the use of home foetal heart monitors this week because the inexperience of parents makes the test less reliable and unsafe.
A positive test result can label somebody with diabetes, cancer and all kinds of other illnesses which have many implications of a person’s life. Therefore, we need to know how good a test is at picking up the people with the disease. The “sensitivity” of a test looks at the proportion of diseased individuals that will have a positive test. That is to say, there will be some people with disease who will get a “false negative”. A negative test result can give somebody reassurance that they do not have a disease, but if the test is unreliable, this may be false reassurance and may lead to the psychological trauma and adverse health effects of a later diagnosis. The “specificity” of a test looks at the proportion of individuals without a disease that will have a negative test. In a test for screening (for example, for colorectal cancer), we want to be confident that we are ruling out the disease; i.e. the test must be very specific. In other settings, picking up a positive might be more important, such as the simple urine dipstick test, which is 90% sensitive for urinary tract infection, but has a specificity of only 60%.
Once we have a positive result, how likely is the patient to have the disease in question? This is called the “positive predictive value” or PPV and tells us what proportion of people with a positive test have the disease (do not confuse with sensitivity). Unfortunately, the PPV is affected by how common a disease is in the population. If there is a high prevalence in the population, then the predictive value will be high, but if the disease is uncommon, the PPV will be low.
If you were paying attention during lesson 2, you will realise that neither sensitivity nor specificity of the monofilament are exact values; they will lie within ranges of values. The monofilament is a special tool, used to test whether diabetics have lost sensation in their feet. A review of all relevant studies showed that sensitivity ranged from 41% to 93% and specificity ranged from 68% to 100%. So next time you ask what the diagnosis is, ask how good the test is first.