Incorporation bias occurs when the gold standard uses (or incorporates) the test you are studying. Incorporation bias is more likely when the gold standard test relies on clinical judgement, which can often make use of the the diagnostic test being studied. Incorporation bias will result in an overestimation of the diagnostic test’s accuracy.
For example, when studying high sensitivity troponins, the final diagnosis of MI frequently depends on a measurement of a troponin. The researchers are testing troponin to determine if it predicts MI, but they are also using troponin to define MI. That circularity artificially increases both the sensitivity and the specificity. (Most of the time they will use different troponin assays, but there is still incorporation bias there).
This post is part of a series of posts on bias in medical research. You can find the whole bias catalogue here.