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

2. Prevalence 40% Sensitivity 70% Specificity 80% Pravalence 20% Sensitivity 70% Specificity 80% PPV=TP/(TP+FP) TP= FP= PPV= PPV=TP/(TP+FP) TP= FP= PPV= NPV=TN/(TN+FN) TN= FN= NPV= NPV=TN/(TN+FN) TN= FN= NPV=

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

4. 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

5. 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?