23andMe is exploring splitting the DNA company in two
bloomberg.com
bloomberg.com
Everyone I know regrets sending off their DNA to them for ancestry parlor tricks and other non-relevant information.
I can believe that some cancers could be detected early via nucleotides found in the blood.
However, Elizabeth Holmes might like a word here. Testing people's blood is a highly regulated activity. One does not simply jump into it.
so is my arithmetic correct, in that it's a 60% false positive rate?
I am surprised that they were approved based on their study results, it will be interesting to see the results from PATHFINDER 2, which is running now.
Detecting early stage cancer in a liquid biopsy is extremely difficult so it's impressive that they made it work at all.
Yes, early cancer tests are fantastic. However, tests need to have extremely good sensitivity and specificity for exactly the reason you said.
It's just not the right arithmetic for computing the false positive rate. :-)
What you computed is the false discovery rate.
Let
FP = number of false positives
TP = number of true positives
FN = number of false negative
TN = number of true negative
What you computed is FP/(FP+TP). The false positive rate is FP/(FP + TN). To compute that we need to know TN.Example. Suppose 1000 people were screened, with 985 true negatives, 5 false negatives and 10 positives, and of those 10 positives only 4 were true positives. Then the false positive rate would be 6/(6+985) = 0.605%.
That names for some of the various things you can compute from FP, TP, FN, and TN are given here [1].
With medical screening you are often have the case that only a small fraction of the people being screened have the condition. Even if a test is wrong only a small fraction of the time, (large fraction of people without the condition) x (small chance of them getting a false positive) can easily be as big as (small fraction of people with the condition) x (large chance of getting a true positive).
Continuing with the example from above, what screening does is take you from "We've got 1000 people and probably around 10 have the condition" to "here's 10 people and probably around 4 have the condition". You can then use more expensive tests that wouldn't be feasible to do on 1000 people on those 10 to find the ones who really have it.
However, the inverse but highly relevant questions the patient asks are:
Given that I got a positive result, what's the chance that I actually have cancer?
Given that I got a negative result, what's the chance that I actually have it anyway?
I could attempt this, but right now I have something else to do. Will check back later and probably find that someone's answered those!