Praedictio mortis conturbat me
Q: Did you see scientists have found a way to predict immediate death?
A: What? Lack of pulse?
Q: Very droll. No, it says interleukin-6. What is that?
A: It’s a messenger protein that some white blood cells use to stimulate other white blood cells to do stuff. If there’s a lot of it around, there’s probably inflammation, which is probably bad.
Q: And it’s new?
A: No.
Q: The story says it’s new.
A: Yes. Yes, it does.
Q: So what’s new?
A: Interleukin 6 and another marker of inflammation called C-reactive protein used to be thought of as the best things to measure if you cared about inflammation. Some researchers came up with another, called α1-acid glycoprotein, and said it was better. This research is arguing that, no, α1-acid glycoprotein isn’t better.
Q: Why isn’t α1-acid glycoprotein mentioned in the story?
A: It is: the Herald’s just having font problems and calling it α1-acid glycoprotein.
Q: Are they right? Is interleukin 6 really better than α1-acid glycoprotein?
A: We can’t really tell just from this one study, any more than we could really tell α1-acid glycoprotein was better from the study that liked it.
Q: How accurate is the prediction?
A: Well, suppose you were given the name of a 55-year old and had to guess whether they’d die in the next five years. What would you guess?
Q: Umm. No?
A: Very good. In this study, over 98% of the people didn’t die in the first five years of followup, so you’d be about 98% accurate knowing nothing.
Q: And knowing their interleukin 6 levels?
A: About 98% accurate.
Q: So it’s useless?
A: No, not at all. Comparing people at the top and bottom of the middle 50% of the distribution for interleukin-6 was like comparing smokers to non-smokers for short-term death rate. It’s just that will you/won’t you die in five years is not the right question for reasonably healthy middle-aged people.
Q: So it could be important for insurance, then?
A: In principle, if you wanted to undermine the usefulness of insurance. It’s more useful for science — either understanding how inflammation has its effects, or trying to rule it out as an explanation of a correlation.
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 »