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Chapter 8 - Quantifying Treatment Effects Using Randomized Trials

Published online by Cambridge University Press:  02 May 2020

Thomas B. Newman  and
Michael A. Kohn
Thomas B. Newman
Affiliation:
University of California, San Francisco
Michael A. Kohn
Affiliation:
University of California, San Francisco
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Summary

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.

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Evidence-Based Diagnosis
An Introduction to Clinical Epidemiology
 , pp. 205 - 230
Publisher: Cambridge University Press
Print publication year: 2020

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