Results gathered during the development and testing of an assay must be analyzed to determine the performance of the assay. In addition, the performance must be gauged by clinical parameters. Key elements include:
- Sensitivity - The percentage of patients who really have the disease and have a positive test.
- Specificity - The percentage of patients who do not have the disease and have a negative test.
- Positive predictive value (PPV)- the probability of disease if the test is positive
- Negative Predictive value (NPV)- the probability of no disease if the test is negative
- Prevalence - How much of a given disease (or test component) is in the population. Note: the PPV and NPV are affected by the sensitivity and specificity of a given assay as well as the prevalence. For example, one would follow up with a patient in a population with extremely low prevalence, where a test is positive.
The table below details a standard 2 X 2 comparison, where assay results are compared to a standard or a specific disease state.
STANDARD (DISEASE STATE)
a = true positive, the patient has the disease and the test is positive
b = false positive, the patient does not have the disease, but the test is positive
c = false negative, the patient has the disease, but the test is negative
d = true negative, the patient does not have the disease and the test is negative
n = total tested
Calculations to assess assay performance:
- Sensitivity % = a/(a+c) x 100
- False negativity % = c/(a+c) x100
- Specificity % = d/(d+b) x 100
- False positivity % = b/(b+d) x 100
- Predictive value positive %: a/(a+b) x 100
- Predictive value negative%: d/ (d+c) x 100