Dr. Peter Attia

this is the probability of this test that we do giving a false positive. This is the probability of it giving a false negative. And again, we know all of this stuff. Like we know for every test we do, there are these two mathematical terms. One is called sensitivity and one is called specificity. So if you do that liquid blood, so what you're referring to, I assume is a liquid biopsy.

So it's a blood test that's doing a pan screen for cancer. That test has a sensitivity, which is the probability that if you have cancer, it will pick it up. The sensitivity for a liquid biopsy is very low. For a stage 1 or stage 2 cancer, it's probably on the order of 30%. That's it? That's it. For all cancers, it's probably on the order of 50%, sensitivity.

So it's a blood test that's doing a pan screen for cancer. That test has a sensitivity, which is the probability that if you have cancer, it will pick it up. The sensitivity for a liquid biopsy is very low. For a stage 1 or stage 2 cancer, it's probably on the order of 30%. That's it? That's it. For all cancers, it's probably on the order of 50%, sensitivity.

So it's a blood test that's doing a pan screen for cancer. That test has a sensitivity, which is the probability that if you have cancer, it will pick it up. The sensitivity for a liquid biopsy is very low. For a stage 1 or stage 2 cancer, it's probably on the order of 30%. That's it? That's it. For all cancers, it's probably on the order of 50%, sensitivity.

Conversely, the specificity, which is the probability that the test comes back negative if you are free of cancer, is very high. The specificity on those tests typically runs about 99.5%.

Conversely, the specificity, which is the probability that the test comes back negative if you are free of cancer, is very high. The specificity on those tests typically runs about 99.5%.

Conversely, the specificity, which is the probability that the test comes back negative if you are free of cancer, is very high. The specificity on those tests typically runs about 99.5%.

Now, when you know those two numbers, sensitivity and specificity, and you know the probability that you have cancer out of the gate, what's called the pre-test probability, which says you're a 42-year-old man, you don't smoke, but maybe you have a slightly higher risk because of your exposure to chemicals, blah, blah, blah, blah, blah. Your pre-test probability is 3%.

Now, when you know those two numbers, sensitivity and specificity, and you know the probability that you have cancer out of the gate, what's called the pre-test probability, which says you're a 42-year-old man, you don't smoke, but maybe you have a slightly higher risk because of your exposure to chemicals, blah, blah, blah, blah, blah. Your pre-test probability is 3%.

Now, when you know those two numbers, sensitivity and specificity, and you know the probability that you have cancer out of the gate, what's called the pre-test probability, which says you're a 42-year-old man, you don't smoke, but maybe you have a slightly higher risk because of your exposure to chemicals, blah, blah, blah, blah, blah. Your pre-test probability is 3%.

Knowing the pretest probability, the sensitivity and specificity allows us at any point in time to calculate what's called positive and negative predictive value, which means if this test comes back positive, how likely is it you have cancer? And it's going to be very low. The whole takeaway of that whole spiel is the PPV, or positive predictive value, is going to be like 10%.

Knowing the pretest probability, the sensitivity and specificity allows us at any point in time to calculate what's called positive and negative predictive value, which means if this test comes back positive, how likely is it you have cancer? And it's going to be very low. The whole takeaway of that whole spiel is the PPV, or positive predictive value, is going to be like 10%.

Knowing the pretest probability, the sensitivity and specificity allows us at any point in time to calculate what's called positive and negative predictive value, which means if this test comes back positive, how likely is it you have cancer? And it's going to be very low. The whole takeaway of that whole spiel is the PPV, or positive predictive value, is going to be like 10%.

So even if that test came back positive, there's a 90% chance you don't even have cancer. The negative predictive value is going to be very high. The negative predictive value is going to be above 99%. So if it comes back negative, you can feel really comfortable if you're negative. Okay. Comes back positive, and this is what I got to earlier.

So even if that test came back positive, there's a 90% chance you don't even have cancer. The negative predictive value is going to be very high. The negative predictive value is going to be above 99%. So if it comes back negative, you can feel really comfortable if you're negative. Okay. Comes back positive, and this is what I got to earlier.

So even if that test came back positive, there's a 90% chance you don't even have cancer. The negative predictive value is going to be very high. The negative predictive value is going to be above 99%. So if it comes back negative, you can feel really comfortable if you're negative. Okay. Comes back positive, and this is what I got to earlier.

I don't even let people do these tests if they're not willing to live with the consequences of a false positive because the likelihood of that happening is actually pretty high.

I don't even let people do these tests if they're not willing to live with the consequences of a false positive because the likelihood of that happening is actually pretty high.

I don't even let people do these tests if they're not willing to live with the consequences of a false positive because the likelihood of that happening is actually pretty high.

Well, I'll tell you. I'll give you a really horrible story of a false positive. I was just talking to somebody the other day who went and got a whole body MRI and it found something in his thyroid that looked a little suspicious. And to be clear, the thyroid gland is notoriously difficult to image, notoriously difficult.