Specificity is defined as the proportion of people without the disease who have a negative test. So the second term, the fraction of positive tests in the group without the disease, is 1 - specificity. Take Helicobacter pylori infections as an example. 1.1 Using examples from the paper on spectrum bias gives a series of results with NND values up to about 4. Thus using CEA as a diagnostic screening test for colon cancer in patients with the disease would yield a NND of 4.4 in early cancers, but as low as 1.6 in late cancers - a clear case of spectrum bias.
Similar differences exist for other examples.
Interesting is the effect of NND calculations on the authors' own data on urine testing. Because sensitivity goes down but specificity increases in patients with few symptoms of UTI, the NND of 2.9 remains the same whether the clinical suspicion is high or low. Their best result was the overall NND of 1.8, because of a combination of relatively high sensitivity and specificity. Perhaps this emphasises the need to consider sensitivity and specificity combined in a single term. Choosing which test There are occasions where different tests can be used to make the same diagnosis.