Most teachers of evidence-based-medicine talk about tests as “positive, or negative”. A positive test is one in which the result of the test is abnormal; a negative test is one in which the test’s result is normal. A problem with this way of teaching about the value of test results is that often physicians and patients think there are only two possible test results, normal or not. However, test results are never just, “normal or abnormal”; test results may take on many values, not just two. ,
Researchers distinguish normal test results by performing the test in people who are well. For example, 100s of normal people will have blood tests done and the test results will vary over a narrow range. A serum potassium test result may be as low as 3.0 and as high as 4.0 in normal people, for example. An abnormal test result for potassium, then, is one whose value is greater than the highest in the range of values in normal people. But, the greater the potassium level, the more the diagnostic and treatment decisions may vary. In tesing, the magnitude of the result matters.
A key concept in testing is that the value of any test result may vary. The more abnormal it is, the more information it “contains” in terms of making a diagnosis. This may seem self evident, but failing to consider the absolute value of a test result is a common cause of missing the correct diagnosis in my experience.
The best way to understand this is to see an example. In the table below, I present a single test’s possible results. The test is PSA, or prostate specific antigen. It is a test used to find prostate cancer, but it is imperfect as the PSA test can be abnormal in diseases other than cancer.
If a physician, or you, just considers the test result as normal or abnormal, you will lose information about the value of the test. In the table, a high value (30, for example, in the first column of the table) means something different to you than a value of 20, or 10, or 5, even though all of those values are abnormal (any value greater than 2 in this example would be abnormal).
In the table, also, note that a test result value as high as 30 only occurs in people with cancer 1% of the time, which is a small percent chance. However, that level of the test never occurs in other diagnoses (in this example). Hence, a value of 30 means you have cancer. It is, in fact, a gold-standard test result at that level.
Any other abnormal test result value less than 30 in this example may increase the likelihood of having cancer, but those values do not mean for certain that you have cancer.
You can see from this table, then, that the actual test result value will have different meanings in terms of making a diagnosis. When we get to actual case examples in future blogs, you will see situations where a diagnosis was uncovered just by considering the information contained in the actual test result value.
My main point to you as a diagnostic decision maker is that you must know everything about your test results, including the exact value of every test’s results. Do not think of tests as just abnormal or not, know your test result values backward and foreword.
Robert McNutt, MD has been an associate editor at the Journal of the American Medical Association for 12 years and before associate editor at the Journal of General Internal Medicine. He is a professor of Medicine at the University of Wisconsin and Rush University Medical Center.
What if your test say abnormal? What does that means
My mother got back abnormal blood work on Just her bloodwork and then today they called and said the test is abnormal what to be expected with this being said?
What mean blood count abnormal n also have flag on my lab test
Thank you for your comments. I am writing to patients with my blogs. I am an informed decision consultant and, hence, patients come to me with test results more often than with questions about if they should have a test. I am also a decision anaylst and understand the desire to “pre-think” testing. However, don’t see much evidence of thinking about whether to test or not. I did a study showing that the types and distributions of tests vary little by diagnosis in a hospital, for example. I see errors, however, when test results are considered “on average” or cut-points rather than as an absoulute value. And, in diagnosis, there is no such thing as a false positive; you either have one disease or another. False positives pertain to screening well people. And even then, screeing tests are misused by not considering the magnitude of abnormalities, in my experience.
Aside from the issue of who pays for the test, patients are much more willing to undergo tests that are not painful or invasive “just to be sure”. Imaging and simple blood draws fall into that category. They are probably much more hesitant to get tests that are painful or uncomfortable or involve unpleasant preparation. Moreover, patients may also think about the consequences of being wrong if they should decline tests like a PSA or mammogram and then find out too late that they have late stage cancer.
There would undoubtedly be less testing if patients were paying more of the bill themselves but how much money would we save when most healthcare costs relate to the management of chronic disease, surgical procedures and oncology treatment? Finally, a lot of marginally useful testing that gets built into the definition of the standard of care in this country probably has more to do with defensive medicine that reflects the litigiousness of our society than the desire to drive revenue for the physician practice or hospital system.
One of my favorite hobby horses. It has been clear for years that much of “testing” has more to do with trolling for business than protecting good health. Better health is, of course, a positive result, but too often the goal is hunting Easter eggs for the practice, courtesy of the insurance company. And besides, what patient will complain about the happy news that “we got (insert favorite target here) just in time”?
How many false positives does it take to yield another case of prostate cancer? And of that number, how many are growing so slowly that the patient will likely die from some other cause before his cancer gets to that point?
How many Mohs biopsies actually save lives?
I could go on, but as I have said before, I’m just a layman. My guess is that there is less evidence of lives saved by over-testing than new business for the doctors. I would not object if actual medical care costs (either via insurance or taxes) were feeding the healthcare system instead of subsidizing insurance corporate profits as well as executive compensation packages, advertising and corporate profits of specialty practices.
Mutual insurance companies converted to stock companies long ago, just as credit unions are at risk of becoming ordinary banks, more focused on corporate returns than the interests of members. (“Members” become “customers,” a very different dynamic.) Something similar has happened with health care, as patients are subject to the wallet test along with whatever other metrics are used to become a “beneficiary” (insurance-talk) or “case” (doctor talk).