SnNout and SpPin
Expansion
| Disease present | Disease absent | |
|---|---|---|
| Test positive | True positive (a) | False positive (b) |
| Test negative | False negative (c) | True negative (d) |
- Sensitivity = a / (a + c): the proportion of people with the disease who test positive. It is the ability to detect disease
- Specificity = d / (b + d): the proportion of people without the disease who test negative. It is the ability to exclude disease
SnNout: a highly Sensitive test, when Negative, rules the diagnosis out, because there are few false negatives. This is why a D-dimer is used to exclude venous thromboembolism.
SpPin: a highly Specific test, when Positive, rules the diagnosis in, because there are few false positives. This is why a positive anti-CCP confirms rheumatoid arthritis.
Both are properties of the test, not of the population, so they do not change with prevalence. That is what makes them portable between settings, and it is also why they do not answer the question the clinician actually has, which is what a result means for this patient. That requires the predictive values, which do depend on prevalence.
Trade-off: moving the threshold of a continuous test trades one for the other. Lowering the cut-off for troponin raises sensitivity and lowers specificity. The ROC curve plots this trade-off, and the area under the curve summarises overall discrimination, where 0.5 is useless and 1.0 is perfect.
Screening tests favour sensitivity, because missing disease is worse than a false alarm that a confirmatory test will resolve. Confirmatory tests favour specificity.