As we noted in the Preface and Chapter 1, because the purpose of doing diagnostic tests is often to determine how to treat the patient, we may need to quantify the effects of treatment to decide whether to do a test. For example, if the treatment for a disease provides a dramatic benefit, we should have a lower threshold for testing for that disease than if the treatment is of marginal or unknown efficacy. In Chapters 2, 3, and 6, we showed how the expected benefit of testing depends on the treatment threshold probability (PTT = C/[C + B]) in addition to the prior probability and test characteristics. In this chapter, we discuss how to quantify the benefits and harms of treatments (which determine C and B) using the results of randomized trials. In Chapter 9, we will extend the discussion to observational studies of treatment efficacy; in Chapter 10, we will look at screening tests themselves as treatments and how to quantify their efficacy.