What is the benefit of using a higly specific autoimmunity test?

Results of highly specific tests are more useful for the clinicians due to the higher positive predictive value.

Example: Celiac Disease (CD)

Celiac disease is characterized by a life-long intolerance to gluten from wheat, barley or rye. The overall prevalence of CD in the general population is approximately 1%. However, there is a high number of non-diagnosed patients because about 2/3rd of the patients do not show the typical gastrointestinal symptoms and have so-called silent or latent CD.

In contrast to other autoimmune diseases, celiac disease has the advantage of having very sensitive and specific serological markers. A simple blood test can virtually rule out or confirm celiac disease with almost 100 % certainty. A positive screen test result usually leads to a confirmatory biopsy. This invasive diagnostic method is unpleasant, may be painful and is expensive. Particularly in children, unnecessary biopsies should be avoided whenever possible.

Therefore, high specificity of the screen tests for celiac disease is particularly important. Due to the prevalence of CD of only about 1% in a screening population, most of the suspected cases will turn out not to have celiac disease. Therefore even a slight decrease in specificity will result in a dramatic increase in unnecessary intestinal biopsies.

Example: 1000 school children are screened with a serological test for celiac disease, the anti-tissue transglutaminase (tTG) test. An anti-tTG test with a specificity of 97 % finds 3 % = 30 children false positive. A specificity of 99.4 % (reported for Phadia's (now Thermo Fisher Scientific) anti-tTG test Celikey) finds 6 children false positive. A specificity decrease of 2.4 % results in 5 times more biopsies of non-celiac children, most of which could be avoided by using the assay with the higher specificity.

All Phadia, now Thermo Fisher Scientific, autoimmunity tests are designed for highest specificity and thus are of most valuable help for the clinician in diagnostic decisions.