Not 100% accurate
Q: Did you see there’s a new, 100% accurate cancer test?
A: No.
Q: It only uses a bit of saliva, and it can be done at home?
A: No.
Q: No?
A: Remember what I’ve said about ‘too good to be true’?
Q: So how accurate is it?
A: ‘It’ doesn’t really exist?
Q: But it “will enter full clinical trials with lung cancer patients later this year.”
A: That’s not a test for cancer. The phrase “lung cancer patients” is a hint.
Q: So what is it a test for?
A: It’s a test for whether a particular drug will work in a patient’s lung cancer
Q: Oh. That’s useful, isn’t it?
A: Definitely
Q: And that’s 100% accurate?
A: <tilts head, raises eyebrows>
Q: Too good to be true?
A: The test is very good at getting the same results that you would get from analysing a surgical specimen. Genetically it’s about 95% accurate in a small set of data reported in January. In clinical trials, 50% of people with the right tumour genetics responded to the drug. So you could say the test is 95% accurate or 50% accurate.
Q: That still sounds pretty good, doesn’t it?
A: Yes, if the trial this year gets results like the preliminary data it would be very impressive.
Q: And he does this with just a saliva sample?
A: Yes, it turns out that a little bit of tumour DNA ends up pretty much anywhere you look, and modern genetic technology only needs a few molecules.
Q: Could this technology be used for detecting cancer, too?
A: In principle, but we’d need to know it was accurate. At the moment, according to the abstract for the talk that prompted the story, they might be able to detect 80% of oral cancer. And they don’t seem to know how often a cell with one of the mutations might turn up in someone who wouldn’t go on to get cancer. Since oral cancer is rare, the test would need to be extremely accurate and inexpensive to be worth using in healthy people.
Q: What about other more common cancers?
A: In principle, maybe, but most cancers are rare when you get down to the level of specific genetic mutations. It’s conceivable, but it’s not happening in the two-year time frame that the story gives.
Thomas Lumley (@tslumley) is Professor of Biostatistics at the University of Auckland. His research interests include semiparametric models, survey sampling, statistical computing, foundations of statistics, and whatever methodological problems his medical collaborators come up with. He also blogs at Biased and Inefficient See all posts by Thomas Lumley »