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Predictive values prevalence

Predictive values prevalence. CK and acute myocardial infarction sensitivity 70% specificity 80% prevalence - 40% prevalence - 20% PPV and NPV. HIV testing. prevalence in global population 0.5% sensitivity and specificity 99% your test result is positive! should you be concerned? PPV?.

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Predictive values prevalence

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  1. Predictive valuesprevalence • CK and acute myocardial infarction • sensitivity 70% • specificity 80% • prevalence - 40% • prevalence - 20% • PPV and NPV

  2. HIV testing • prevalence in global population 0.5% • sensitivity and specificity 99% • your test result is positive! • should you be concerned? • PPV?

  3. 0,99 • The prevalence of HIV is estimated to be about 0.5% in the general population. • Of 100,000 persons screened 500 will be HIV-infected (prevalence of 0.5%); • 495 of the 500 will have positive screening tests (sensitivity of 99%) ->TP 99% of 500=495 • However, there will be 995 positive tests in those who are not HIV-infected (specificity of 99%) ->FP 1% of 99500=995 • PPV=495/(495+995)=0,33 • Of every three subjects testing HIV-positive, two are certain to be false positive

  4. Example • You are running a mammography screening program in a van that travels around your health district. A 45 year old woman has a mammogram. The study is interpreted as "suspicious for malignancy" by the radiologist. • The patient asks, "OK, I understand that the mammogram isn’t the final answer, but given what we know now, what are the chances that I have breast cancer?".  • Assume that the overall risk of breast cancer in any 45 year old woman, regardless of mammogram result, is 0.1% or one in a thousand. Assume also that mammography is 80% sensitive and 95% specific. What is the probability that this woman actually has breast cancer?

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