Two common metrics used to compare diagnostic tests are sensitivity and specificity. Sensitivity is the probability a patient with a disease tests positive, while specificity is the probability a patient with the disease will test negative.
Sensitivity = TP/(TP+FN)
Specificity = TN/(TN+FP)
Sensitivity and specificity are static values for any given application.
Raising a cutoff value will favor specificity in exchange for a poorer sensitivity. Lowering a cutoff value (or coming up with a new high-sensitivity troponin assay, for example) does the opposite.
A brief aside:
- Analytical sensitivity: the limit of detection (LOD) is the lowest concentration the assay can detect 95% of the time. This is different from the limit of quantification (LOQ) which is higher.
- Clinical sensitivity: the ability of an assay to correctly identify patients with the disease of interest. In this case, this means correctly identifying an acute MI.