<p><pre><code>  &gt; What&#x27;s the argument for not testing in the first place?

  The wider the pool of people being tested, the greater
  the chance of false positives, which is why screening
  guidelines generally limit the population to be screened.
  The more independent tests you do at once, each with its
  own chance of error, the larger the chance that at least
  one of those tests produces an incorrect result, said
  Rebecca Goldin, director of STATS.org and a professor of
  mathematical sciences at George Mason University.
</code></pre>
It&#x27;s not just panic, but that if the false positive rate is too high then untargeted testing becomes overwhelming and counterproductive. There&#x27;s a slim, very slim, chance that as a man I could develop breast cancer. But there&#x27;s little value in testing me as it&#x27;s not present in my family history (male or female).<p>So let&#x27;s say (in this example) that the false positive rate is <i>only</i> 1% in men and the true incidence rate is 0.01%, and we test 100 million men:<p><pre><code>    10,000 men have breast cancer, great we&#x27;ve detected it
   999,900 men don&#x27;t, but are subjected to more testing
</code></pre>
That more testing is likely costly, time consuming, and potentially invasive. This acts as a net drain on medical resources because we&#x27;ve just performed nearly 1 million unnecessary mammograms. They take technician and physician time. They take machine time. And so on.<p>So false positive rates may be low, but when applied to a massive population the total number of false positives can overwhelm the system.