[aix1]

> 94.5% is actually terrible.

This statement is quite broad and misses several important factors.

First of all, a test's sensitivity and specificity. The math in your example assumes a balanced test, but on what basis? The math comes out quite different for high-sensitivity or high-specificity tests. (Unfortunately, I could not find the numbers for the test in the linked article.)

Secondly, whom are we testing? The prevalence rate in your example (1%) is unrealistically low even for the general population. But would we screen the general population? No, we'd screen high-risk groups: the elderly, those with certain APOE genotypes etc. Predictive values of a test depend hugely on the prevalence rate.

Lastly, it depends on how the results are used. If it's a high-sensitivity test used to decide whom to send to the next tier in a multi-tier diagnostic system, it could actually be quite effective at that (very rarely missing the disease while greatly reducing the need for more expensive or more invasive testing).