Hello my name is Triska. I am working with DrAngry and ProfB and was due to do my student Lab project on anti-drug antibodies in MS. I have been told that the subject matter is top secret. However, things have changed and I have been doing a COVID-19 related study.
You may know that you can detect the virus is you are infected. However, after you have been infected, you will make an anti-COVID-19 antibody response. This will help you to get rid of the virus andmay stop you from getting re-infected again.
Soon we will be offered an antibody test to see if we were infected. I will be back to explain more about the tests. However, you may hear alot about “sensitivity and specificity” when these tests arrive.
It is not only important to anti-COVID tests, but also to the anti-drug antibody tests we are developing. I have been asked to explain them so here goes.
Sensitivity vs. Specificity
‘Sensitivity’ measures how often a test correctly identifies a positive result for people who have the condition that is being tested for (also called the ‘true-positive’ rate).
This means that if a test is ‘100% sensitive’, the test correctly identifies every individual who has the condition and will not produce false-negative results. For example, if a test has 90% sensitivity, this test can identify 90% of individuals that are being tested who have the disease correctly but will have a false-negative result for 10% of individuals who are actually meant to be positive.
‘Specificity’ measures the ability of a test to correctly identify a negative result for people who don’t have the condition that is being tested for (also called the ‘true-negative’ rate).
This means that if a test is ‘100% specific’, the test correctly identifies every person who does not have the target disorder. For example, if a test has 90% specificity, this test can identify 90% of individuals who do not have the disease correctly as negative but will have a false-positive result for 10% of individuals who are actually meant to be negative.
Accuracy vs. Precision
Both accuracy and precision measure how reliable a test is. An ideal test can deliver 100% accurate and 100% precise results. However, a test can be precise without being accurate, and vice versa.
Accuracy reflects whether a test can measure what it is supposed to measure. This means it is able to measure the true amount of what is being tested for in a sample.
The precision of a test reflects whether a test can give similar results every time that the test is repeated on the same sample. This means that the test can give ‘reproducible’ results
Here is an example
Comparison of four new commercial serologic assays for determination of SARS-CoV-2 IgG. Krüttgen A, Cornelissen CG, Dreher M, Hornef M, Imöhl M, Kleines M. J Clin Virol. 2020 ;128:104394. doi: 10.1016/j.jcv.2020.104394. [Epub ahead of print]
BACKGROUND:Facing the ongoing pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), there is an urgent need for serological assays identifying individuals with past coronavirus disease 2019 (COVID-19).
STUDY DESIGN:Our study is the first to compare four new commercially available assays using 75 sera from patients tested positive or negative by SARS-CoV-2 PCR: the anti SARS-CoV-2 ELISA (IgG) (Euroimmun, Germany), the EDI New Coronavirus COVID-19 IgG ELISA, (Epitope diagnostics (EDI), USA), the recomWell SARS-CoV-2 IgG ELISA (Mikrogen, Germany), and the SARS-CoV-2 Virachip IgG (Viramed, Germany).
RESULTS: We found a sensitivity of 86.4 %, 100 %, 86.4 %, and 77.3 % and a specificity of 96.2 %, 88.7 %, 100 %, and 100 % for the Euroimmun assay, the EDI assay, the Mikrogen assay, and the Viramed assay, respectively.
CONCLUSIONS:Commercially available SARS-CoV-2 IgG assays have a sufficient specificity and sensitivity for identifying individuals with past SARS-CoV-2 infection.
However, you can see they are not 100% specific and sensitive. Therefore it may be possible to improve things
Remember SPIN & SNOUT
SPIN for, ‘Specific test when Positive rules IN the disease’
SNOUT for ‘Sensitive test when Negative rules OUT the disease’,