Cancer survival rates are misleading
allendowney.com
allendowney.com
the economist put out a piece a few months ago providing just that. Specifically it compares overall cancer mortality rates (and more interestingly, mortality rates adjusted for age) and shows that cancer deaths have been dropping.
https://www.economist.com/briefing/2025/07/17/the-world-is-m...
Putting people into a control group so you can observe the effects of not treating them might not make it past the ethics committee.
In the current trials a part of the subjects get the new experimental drug and the control group get the current state of the art treatment.
This is a real problem when the Minister wants to know if it’s worth spending money on treatments, because all you have is a disjointed set of trials, none of which are necessarily representative of the population at large, or the population wide incidence of the disease (assuming there is even data on that (notifiable illnesses are the exception).
That's not what happens.
Is this just a hypothetical?
Everything will be compared to one standard of care, or perhaps two which will have been compared to each other. If a new treatment is much better, then it will become standard of care.
Trials cost a lot of money, so they are conducted rationally.
Suppose D is only slightly less effective than C, but more effective than A, and B, but 100x cheaper, and/or has less bad side effects. If you only compare with C, all you know is it's not as good as C.
Can you point to particular drugs or are you also making up examples?
I admittedly do not know of every trial that happens everywhere but this is exactly the sort of thing that a layman expects would occur but which does not happen.
I don't see how stem cells relate to the idea of trials for successive standard-of-care treatments. Can you explain your thinking?
https://www.bmj.com/content/363/bmj.k5094
But seriously: this is a recognized problem in medicine and there's already a widely used solution. Whenever you're doing trials of an intervention for a condition which already has an accepted treatment, you run a trial to compare your new intervention to that, and see if your test group has better outcomes. After all, the question shouldn't be whether your treatment is effective; it's whether it's better than existing treatments.
Trials against a placebo have a purpose, but they aren't the only way to run a trial.
If you're talking about a treatment for The Common Cold, the null hypothesis is "the subject got better after awhile because people get better after awhile", and you can't disprove that's what's happening without a very rigorous study with a well designed control.
If you're talking about "here's some robot eyes that cure blindness", you don't really need a control group to test if it works. The null hypothesis is they're blind; you just need to demonstrate they can see to disprove the null hypothesis and prove efficacy.
"better" is not a total order, one treatment may be better in some ways and worse in other ways. Especially if you include things like cost and availability.
There has never been an RCT to show that smoking causes lung cancer but doctors now all recommend that their patients not smoke.
So for example, if you have (hypothetically) an untreatable cancer that would take six years to kill you, if it is diagnosed right away, you would be counted as a survivor, but if you are diagnosed at year five, you'll only survive a year.
Diagnosis is complex too, you don't want the test to have low specificity. False positive is sometimes tolerated.
Weirdly enough that's the same mechanism hypothesized to play a partial role in why breast feeding is also associated with a reduced cancer risk.
Fascinating, weird, stuff.
Aldous Huxley was correct, we truely are amusing ourselves to death. The new meta glasses are really scaring me.
Sorry for the doomerism. There's lots of other stuff to be optimistic about. Maybe this is just an evolutionary filter. Those that fit into these new circumstances will survive.
No idea if it'll have an impact on his lifespan but it definitely bought him years of health and changed his day to day life
That's a great argument in the abstract, but it ignores the fact that there are effective treatments for colon cancer. The fact that we can reproduce real survival rates in a counterfactual world where there are no effective treatments for colon cancer does not actually give us a model of the real world because the counterfactual explicitly contradicts known scientific facts.
What you have to do in order to make this argument is to show that there are Markov models where early detection does not work despite the fact that some cancers will cause death if untreated and not if treated. You cannot simply rely on models that have clearly impossible transition probabilities. You need possible models. Or you have to show that the absolutely massive amount of scientific literature and clinical experience about how to treat colon cancer is somehow flawed.
Some people are defending this because the blog post is attacking a specific argument, but I don't see how that can work. I am pretty sure that Nassim Taleb and most other people who are capable of putting together a coherent statistical argument (even a flawed one) understand that colon cancer can be treated sometimes.
One point in the article is that early detection would give you more years to live even if there were no treatment. Because "early" means "more years". This wasn't obvious to me right away.
But he is not saying don't get screened! He is not saying there are no cancer treatments! He's saying that the 5-year survival rate, considered alone, is a tricky measure that can fool our intuition. In my case he's right.
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Details.
Dumb toy model. Let Tumor X kill you exactly 8 years after it becomes detectable in screening. Assume screening is 100% accurate with no false positives. Assume X cancer kills you exactly 2 years after it causes symptoms. Imagine that there is no treatment for X cancer.
In this dumb model, everybody dies at exactly the same time after the tumor became detectable. The people who caught it in screening had more warning, but otherwise they didn't get a better outcome. Even though screening boosts the 5-year survival rate from 0% to 100%.
Never mind his like 7-state Markov model. OMG. Why.
The specifics of your case will strongly affect what happens to you. And even for cancers that are a guaranteed death sentence, survival has increased significantly in recent years.
Go ahead, tell them the aggressive mass in their brain, the thing that shortened whatever potential life expectancy they had to, at best, single digit years, isn’t a guaranteed death sentence.
They’ll be so comforted by the idea that maybe their already shortened life expectancy will be further reduced by a car accident or some idiot with a knife.
Your idea that hope is going to lead to a car crash? or murder by knife? is one of the most bizarre and ridiculous things I've ever read.
We're so used to argument that criticizing logic is taken as criticizing the conclusion.
This may be so, but his examples are so poor that one is distracted from any type of subtle claim he would make. They are bad in obvious ways (every cancer patient is staged, but we pretend in the article like staging is ancillary to researching survival rates).
Evidence: https://www.nejm.org/doi/full/10.1056/NEJMoa1301969
Large prospective cohorts (Nurses’ Health Study + Health Professionals Follow-Up Study) with long follow-up - screening colonoscopy was associated with a 68% lower risk of death from colorectal cancer overall (multivariable HR ≈ 0.32, 95% CI 0.24–0.45) and showed significant reduction for proximal colon mortality as well (HR ≈ 0.47, 95% CI 0.29–0.76).
This is the only claim the article makes directly about colon cancer. Otherwise, it's saying that early detection being beneficial isn't supported by survival rates alone.
That claim may be obvious to everybody except me. Anyway it turns out to be true.
This was my key takeaway. In a society organized around statistics, we're struggling through an era where those statistics expire faster everyday, and faster than new data can be generated. I can almost relate to the mindset that devalues "facts" because they're increasingly complicated, rapidly changing and come with too many caveats.
I don't think there is any person who is aware of the idea of cancer mortality who would equate 'Stage IV' to lead to 'average' survival.
So maybe the article's only point (which is very obvious, and does not require Markov modeling) is that if you increase the number of people who live a long time in a sample, then the average of that sample will go up.
This feels like someone saw a fact on the internet and didn't try to read about it before writing a blog post.
like the colon cancer thing. he talks about how it would only be more effective to catch colon cancer early if you assume we have treatments for it that would work early. but we don't need to just assume blindly. we already know we do have those treatments!
Essentially every assertion in the article is either an oversimification, cherry picking a random niche situation to highlight, or just flat out factually inaccurate.
Let's take this paragraph for example:
"Catching cancer early is beneficial only if (1) the cancers we catch would otherwise cause disease and death, and (2) we have treatments that prevent those outcomes, and (3) these benefits outweigh the costs of additional screening. This table does not show that any of those things is true."
To address these one by one:
1. Obviously cancer causes disease and death. The same graphic he references makes that abundantly clear. Sure, there might be some rare exceptions (elderly patients with slow growing colon cancer for example), but we're talking about the general population.
2. All cancers have treatment options available in some form (could be chemo, radiation, surgical resection, etc), so this assumption doesn't even make sense to include. Let's assume for a second though that treatments might not be available. Even if that were true, there ARE treatments that can help treat cancer symptoms, and but may not affect the tumor directly. Often these are specific to the specific type of cancer.
3. This assertion is dumb - is the author really trying to argue that providing symptomatic or other relief to a cancer patient isn't a sufficient benefit to warrant additional screening?
I could go on, but you get the point. Some people just like arguing for the sake of arguing I guess.