Introduction

In the previous chapter we looked at how to interpret diagnostic information such as symptoms, signs, and diagnostic tests. Now we need to consider when such information is helpful in decision making. Even if they reduce uncertainty, tests are not always helpful. If used inappropriately to guide a decision, a test may mislead more than it leads. In general, performing a test to gain additional information is worthwhile only if two conditions hold: (1) at least one decision would change given some test result, and (2) the risk to the patient associated with the test is less than the expected benefit that would be gained from the subsequent change in decision. These conditions are most likely to be fulfilled when we are confronted with intermediate probabilities of the target disease, that is, when we are in a diagnostic ‘gray zone.’ Tests are least likely to be helpful either when we are so certain a patient has the target disease that the negative result of an imperfect test would not dissuade us from treating, or, conversely, when we are so certain that the patient does not have the target disease that a positive result of an imperfect test would not persuade us to treat. These concepts are illustrated in Figure 6.1, which divides the probability of a disease into three ranges:

1. do not treat (for the target disease) and do not test, because even a positive test would not persuade us to treat;

2. test, because the test will help with treatment decisions or with follow-up; and

3. treat and do not test, because even a negative test would not dissuade us from treating.

Treat implies patient management as if disease is present and may imply initiating medical therapy, performing a therapeutic procedure, advising a lifestyle or other adjuvant intervention, or a combination of these. Do not treat implies patient management as if disease is absent and usually means risk factor management, lifestyle advice, self-care and/or watchful waiting.