Screening for HIV: Can We Afford the False Positive Rate?

Richard Saitz MD, MPH, FACP, FASAM

Editor, Evidence-based Medicine (EBM)

Professor of Medicine and Epidemiology

http://ebm.bmj.com/ 

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PREVALENCE OF INFECTION

What do we know about the prevalence of HIV infection? Perhaps 50 percent of homosexual men in San Francisco have serologic evidence of the infection. The prevalence of seropositivity among intravenous drug abusers and among patients with hemophilia who received factor VIII concentrate pooled before the advent of heat inactivation is similar.3 , 8 At somewhat lower risk are patients who received repeated transfusions of red cells, platelets, and plasma before routine HIV testing of donated blood began in 1985. Antibody testing of one group of patients with leukemia treated between 1978 and 1985 showed that about 5 percent became seropositive. The patients who became seropositive had received an average of 164 units of blood products.26

Other segments of the population are at much lower risk. Screening of military recruits has shown 0.16 percent of the men and 0.06 percent of the women to be seropositive.27 When antibody screening of donated blood began in 1985, 1 unit of blood in 2500 had HIV antibody.28 At that rate, the chance of infection from 2 units of blood donated before antibody screening began would be about 0.08 percent. Among female blood donors, as noted, the reported prevalence of seropositivity is 0.01 percent. Some of these donors may have had sexual contact with members of known high-risk groups; among women without such contact, the prevalence of infection may be even lower than 0.01 percent.

MEANING OF POSITIVE TESTS

Test sensitivity is not the issue here, and to emphasize our concern with the false positive rate, our analysis makes the best-case assumption that the combination of enzyme immunoassay and Western blot testing for HIV is 100 percent sensitive, identifying all persons who are infected. The meaning of positive tests will depend on the joint false positive rate. Because we lack a gold standard, we do not know what that rate is now. We cannot know what it will be in a large-scale screening program. However, we can be fairly sure that without careful quality control, it will rise.

Bayes' rule allows us to calculate the probability that a person with positive tests is infected.29Imagine testing 100,000 people, among whom the prevalence of disease is 0.01 percent. Of the 100,000, 10 are infected; 99,990 are not. A combination of tests that is 100 percent sensitive will correctly identify all 10 who are infected. If the joint false positive rate is 0.005 percent, the tests will yield false positive results in 5 of the 99,990 people who are not infected. Thus, of the 15 positive results, 10 will come from people who are infected and 5 from people who are not infected, and the probability that infection is present in a patient with positive tests will be 67 percent.

From: Evidence based health (EBH) [mailto:[log in to unmask]] On Behalf Of Simon Hatcher
Sent: Wednesday, February 09, 2011 6:22 PM
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Subject: Question about screening and denominators