This is a linkpost for https://entropicthoughts.com/full-body-mri-earns-you-a-base-jump
Doesn't cancer risk increase exponentially with age? Scott's article discusses someone around 50 years old as a hypothetical case, but if 50-ish is somewhere around the breakeven point where whole-body MRI might become worthwhile (especially for a rich person or etc), doesn't this mean it's a no-brainer for a 65 year old, but still probably a near-total waste of time for anyone in, say, their thirties?
Scott says something like, let's assume we aren't living in reality when he says "We’ll very optimistically assume that after enough tests, the smartest doctors can distinguish cancers that should be treated and cancers that shouldn’t be treated with 100% accuracy".
We do have studies that looked at how survival rates change after various cancers screenings. To ignore that randomized studies and make arguments based on what spherical cow analysis suggest, is not a good basis for making simplified claims.
We might not have the big studies for full body scanning for cancer detection, but the results of the studies for cancer screening we do have can only be explained with doctors making many bad treatment decisions or there be other negative effects that come from cancer screening tests.
QALYs are a bad measure when it comes to adding up a small amount of time spent by a large number of individuals, because not all hours of life are equally valuable. When you take a small number of hours from a person, the hours come from a less valuable slack pool than if you take a lot of hours, so X number of hours from one person (as in an increased risk from smoking that gives an individual cancer) is not the same as X number of hours spread over many people (as in a lot of people spending time on tests).
I think this goes in the opposite direction from what you're suggesting. For me at least, losing a small number of hours to medical testing (or similar life disruption) doesn't come from a "slack pool". Instead, it disrupts my life out of proportion to the amount of hours involved. For a longer-term predictable time commitment, the disruption scaled sub-linearly with the additional time spent.
As an extreme example, if I have a scheduled phone call that will only take 2 minutes, it effectively wastes 2–3 hours of my day because I can't really do anything significant in the 2–3 hours before the phone call.
As an extreme example, if I have a scheduled phone call that will only take 2 minutes, it effectively wastes 2–3 hours of my day because I can't really do anything significant in the 2–3 hours before the phone call.
Are you claiming this is a typical experience, or are you sharing a fact about yourself that you consider unusual?
I think I lose more time to small interruptions than most people, but the trend is typical—small time losses have a proportionally larger overhead cost than large time losses.
I don't agree. Something that takes away my entire life when I am unlucky is going to take away a number of weddings, graduations, or even smaller things like movies that I can't see because I'm dead. Something that takes away 1 hour of my life that is not completely random won't do this. It won't do this even repeated over enough people to lose the same number of hours as a single person losing his entire life. I'll have to sacrifice something in that hour, but I'll sacrifice a low value part of my life, not an average one. (Perhaps the opportunity cost of taking some extra sick leave from work.)
(Technically, this doesn't mean that QALYs are wrong--QALY means quality adjusted life years. Just adding up the hours under these circumstances is a failure to adjust them for quality, and therefore calculates them wrong.)
You can't ignore the dollar cost of the MRI which could easily run $3000. The dollar value of a QALY is hard to pin down (and would vary widely between individuals) but typically for medical interventions is placed around $100K for cost/benefit analysis. With those numbers, and using your numbers for the benefits, you get a net of -0.005 QALY.
Of course, I'm sure the cost could be brought down, if enough people were pushing for it.
Alternative titles:
These are all about equivalent to the risk of one year of smoking.
I’m skeptical of submitting asymptomatic people to medical tests. Almost any time I look into the evidentiary power of medical tests, I’m struck by how much work is performed by the base rate. The tests only work because we perform them on people who appear sick, i.e. have a higher probability of actually being sick in the first place. If we would perform them on seemingly-healthy people we would get nonsensical results.[1]
Thus it was with interest I read Scott Alexander’s breakdown of the benefits and costs of a routine full-body MRI as a way of screening for cancer. However, I felt like the conclusions weren’t put into an understandable context. Here’s my attempt at doing so.
First, a quick recap of the main points of the article. I’ll ignore the exorbitant financial costs of US healthcare, and focus on the benefit and cost in terms of health. This is measured in quality-adjusted life years, or QALYs. Of the hypothetical thousand people who get scanned, the estimation is that
Tallying up the costs and benefits into an expected value, we get a net benefit of 0.025 QALYs per person, after accounting for medical time.[3] This doesn’t tell me a whole lot, because my intuition for QALYs is weak. How strongly should I prefer an intervention with a net benefit of 0.025 QALYs over other things I might do with my time? No idea!
However! When marketing the effect of global health interventions, a count of 27 QALYs is typically considered “a life saved”. A life also happens to be a million micromorts, and I have a much better intuition for micromorts! When we run that maths in reverse, we get a very cheeky exchange rate between QALYs and micromorts:
One QALY is 37,000 micromorts.[4]
Thus, an intervention that has an expected benefit of 0.025 QALYs – like a routine full-body mri – corresponds to an intervention that has a benefit of 926 micromorts. The alternative titles indicate activities that carry roundly a risk of around 1000 micromorts:
So the same effort you would expend to get out of those activities on account of their risk, the same effort you should be willing to expend to get a full-body MRI.
Note the on account of their risk phrasing. I have no interest in doing any number of BASE jumps and will work hard to get out of doing them, but that’s because I wouldn’t enjoy the activity, not because I’m worried about the risk. If I was put in a situation where it seemed like I had to perform two BASE jumps to reunite with my family, I would spend some effort on finding alternative ways of getting there, but perhaps not all that much before I decide to just eat the BASE jumps and getting it over with.
Note that this is not a criticism of the tests. They are optimised for the thing they need to do.
They would probably have gone through this circus eventually anyway.
This is the figure Scott Alexander reports as “25” in sum across all 1000 people. I just didn’t find its very clear so I had to replicate it to make sense of it.
The equivalence between 27 QALYs and a life saved is based on global demographics. For people in developed countries, where the life expectation is longer, a QALY probably corresponds to a lower number of micromorts – probably around 30,000 or so.