[BostonCard]

Sorry to request a further explanation, but I'm not sure what your answer is to my question about what the true false negative rating is for say a nasal swab being tested by 84% accurate (16% false negative) abbott's fast test. (the comments about false positives, I'm not disputing)



In other words, if you nasal swabbed and abbott tested 100 positive patients, how many results would end up positive (statistically).  At least 16% for sure, but would it be 40% if nasal swabs are only 70% capable of grabbing enough sample to trigger a positive result?



Thanks

The problem is that "false negative rate" is an ambiguous term.  It could represent the sensitivity (technically 1 - the sensitivity).  The sensitivity isis the proportion of patients who are known to have COVID-19 and test positive [in other words, true positives/(true positives plus false negatives); so the "false negative rate" would be false negatives/(true positives plus false negatives)].  However, it could represent the negative predictive value (again, technically 1- NPV); NPV is the proportion of patients who test negative who don't COVID-19 [in other words true negatives/(true negatives plus false negatives), so the "false negative rate" here would be false neagtives/(true negatives plus false negatives).

I don't know how the tests were conducted.  My sense is that they are quoting the sensitivity, and so it depends on what your gold standard being used is.  If you have an imperfect gold standard, the sensitivity of the Abbott test would be chained to the gold standard, if it failed to test positive in false negatives in the gold standard.  It is possible that the Abbott test would catch some proportion of the 30% of false negatives through conventional tests.

BC

[BostonCard]

Sorry to request a further explanation, but I'm not sure what your answer is to my question about what the true false negative rating is for say a nasal swab being tested by 84% accurate (16% false negative) abbott's fast test. (the comments about false positives, I'm not disputing)



In other words, if you nasal swabbed and abbott tested 100 positive patients, how many results would end up positive (statistically).  At least 16% for sure, but would it be 40% if nasal swabs are only 70% capable of grabbing enough sample to trigger a positive result?



Thanks

The problem is that "false negative rate" is an ambiguous term.  It could represent the sensitivity (technically 1 - the sensitivity).  The sensitivity isis the proportion of patients who are known to have COVID-19 and test positive [in other words, true positives/(true positives plus false negatives); so the "false negative rate" would be false negatives/(true positives plus false negatives)].  However, it could represent the negative predictive value (again, technically 1- NPV); NPV is the proportion of patients who test negative who don't COVID-19 [in other words true negatives/(true negatives plus false negatives), so the "false negative rate" here would be false neagtives/(true negatives plus false negatives).

I don't know how the tests were conducted.  My sense is that they are quoting the sensitivity, and so it depends on what your gold standard being used is.  If you have an imperfect gold standard, the sensitivity of the Abbott test would be chained to the gold standard, if it failed to test positive in false negatives in the gold standard.  It is possible that the Abbott test would catch some proportion of the 30% of false negatives through conventional tests.

BC