Evaluation of Diagnostic Tests Flashcards
tests
anything used to distinguish health from disease
“gray area” of test results
overlap in titer levels in healthy vs disease animals creates a “gray area” for how to determine test cutoff values
healthy animal: high titers can be caused by vaccination, maternal Ab, and field exposure
diseased animals: low titers can be caused by early stage of infection, immunosuppression, and individual variation
single test cutoffs
classifies a test result as positive or negative
two test cutoffs
classifies test results as positive, negative, or suspect/indeterminate (gray area values)
sensitivity
proportion of diseased animals that test positive
high sensitivity tests: catch ALL disease positive animals
- high rate of false positives
- low rate of false negatives
have confidence in the NEGATIVE result
sensitivity = TP / TP+FN
specificity
proportion of healthy animals that test negative
high specificity tests: catch ALL disease negative animals
- high rate of false negatives
- low rate of false positives
have confidence in the POSITIVE result
specificity = TN / TN+FP
predictive properties
used when we do not know the disease status of the animal but we do know the test result
- can determine disease status
what are predictive properties affected by
- prevalence
- diagnostic test properties
how does prevalence affect PPV and NPV
high prevalence = increase PPV, decrease NPV
low prevalence = decrease PPV, increase NPV
how do diagnostic test properties affect predictive properties
high sensitivity = low PPV, high NPV
high specificity = high PPV, low NPV
positive predictive values
proportion of test positive animals that are infected
most predicted by SPECIFICITY
PPV = TP / TP+FP
negative predictive values
proportion of test negative animals that are healthy
most predicted by SENSITIVITY
NPV = TN / TN+FN
prevalence
total # disease / total population
P = (TP + FN) / (TP+FN+TN+FP)
influences how we interpret gray area titers
what test is best for screening/disease surveillance
high sensitivity tests
rule out tests -
will capture ALL disease positives and can be confident that the test negative animals are truly negative
has a LOW false negative rate - have confidence in the negative result
what test is best for confirmatory testing
high specificity tests
rule in tests -
will capture ALL disease negatives and can be confident that the test positive animals are truly positive
has a LOW false positive rate - have confidence in the positive result
if a test has a low sensitivity, how can it be used in a herd setting
test many animals - more likely to find a true positive animal within a herd if there is a larger sample number
parallel/simultaneous testing
requiring two different diagnostic tests to confirm/rule out diagnosis
ex. Johne’s disease
- animal is considered positive if tests positive on ELISA, PCR or both
- animal is considered negative if tests negative on ELISA and PCR (both)
net GAIN in sensitivity
net LOSS in specificity
series/sequential testing
doing additional testing not hose that test positive on initial screening test
ex. EIA
- animals that test positive on ELISA are then tested on AGID
- AGID has higher specificity –> confirmatory test
net LOSS in sensitivity
net GAIN in specificity
