Did you get that?
They took a look at what it really means to give point estimates for lifetime risk of disease comparing with population risk data. In this case they chose breast cancer.......and FGFR2
Their conclusion?
Epidemiologic parameters involved in computation of disease risk have substantial uncertainty, and cumulative uncertainty should be properly recognized. Reliance on point estimates alone could be seriously misleading.
Do you get what they are saying? Let me break it down this way. When I see a patient for BRCA testing they always ask
"How high is my risk?"
I say: "Well.......it is a range."
Most people don't like ranges. In our little rat brains we think a range means uncertainty and probably a little guessing. Most patients don't like to go to doctors who give ranges or guesses.
Nor do people like buying things that don't give them "exacts" People very often, when left to their own devices would choose black and white over gray. They just don't like feeling uncertain.
That's precisely the big problem with how genetic testing has been marketed.
Think about it.
On TV: Maury Povic "You ARE the father of (insert name here)" and cut to a little dance
On 23andMe: Find your Norovirus resistance!!
OR
"The mutation in question is in a gene known as LRRK2 on chromosome 12. The single-letter change in the DNA code dramatically increases a person’s odds of developing Parkinson’s from one or two in a hundred to as much as eight in 10. One recent study found that a person who inherits the mutation has a 28% chance of developing Parkinson’s by the age of 59, 51% by the age of 69 and 74% by the age of 79."
Sounds pretty certain to me.....
Do you get it?
Well, the answer is simple. Nothing in life is certain. Nothing, except death and taxes.
This study shows that if your model relies on too many uncertainties, your risk model fails. This is the biggest problem with the DTC Genomics companies' models. They are based on too much uncertainty and as such fall in the realm of fortune teller rather than risk prognosticator.
This is precisely why I have said "Data is Data, but Data can be Garbage."
And Garbage In = Garbage Out.
The Sherpa Says: with any risk model there is uncertainty, no surprise there. But the real surprise is the marketing of it as CERTAINTY to an unsuspecting and primed for certainty public.
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