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After reading: "this study, like ~every study, detected no effect on all-cause mortality because that needs a crazy big sample size"
A three-year study where one group magically had zero car crashes would need a sample size of 5,000,000 to detect a difference in all-cause mortality. It's really hard. (80% chance of p < 0.05)
I am skeptical of the implied lesson of this analysis—and it is a meta-analysis of other research, not an original study. Just take as given that the analysis is correct, and screening for rare Disease A on net has no effect on life expectancy. Almost no one actually gets Disease A, but everyone is screened for it, and that has some diffuse cost to life expectancy: Screen enough people enough times and someone will d…
Earlier quoted context omitted.
They are conflating cancer survival rates with longevity. When has someone claimed that treating cancer would increase life expectancy above the average? This is a dangerous article. People don't need more reasons to avoid cancer screenings.
It looks like they were comparing a group that got screening vs a group that didn’t get screening. If the group that got screening didn’t live longer than the group that didn’t get screening, that seems like a lot of wasted dollars.
This is the pertinent quote: > “Cancer screening was never really designed to increase longevity. Screenings are really designed to decrease premature deaths from cancer.” Explained another way, Dahut said, if a person’s life expectancy at birth was 80, a cancer screening may prevent their premature death at 65, but it wouldn’t necessarily mean they’d live to be 90 instead of the predicted 80. Personally I think this…
The paper [1] is more well written and clear than the CNN article. They were comparing the aggregate life expectancies of people who went through regular screenings vs those who did not, and there was near zero difference except for colorectal screenings where the difference was about 4 months of difference. The paper is indeed presenting strong evidence that regular screenings have minimal value. [1] - https://jaman…
That is, putting aside monetary costs for the moment (which I know is not a good idea in reality, but want to focus on another issue), you often hear about how false positives cause "added anxiety and unnecessary treatments, which can cause harm", but if a breast cancer screening saves, say, lets one woman live until 80 instead of dying at 40, how many other people's "added anxiety" would it take to say "OK, that test was worth it". I think a lot of folks would go think that saving that life should be valued a lot more than just, say, comparing 40 years for her vs. time/anxiety "wasted" for false positives.
If you assume all the costs are fungible, then the analysis is straightforward (the costs are not actually fungible -- some things cost money, other things cost patient time, or use resources that are in finite supply -- so it turns into a linear programming problem, and we've been able to solve those since before computers existed).
With fungible costs, for each of the available health care services, you the expected increase of life expectancy and divide it by the cost, and prioritize the things that have the highest benefit/cost ratio.
The article doesn't talk at all about the cost of the screens, which is fairly low (vs. spending time exercising, or a year of exotic chemo). It also doesn't look at patient quality of life.
I am skeptical of the implied lesson of this analysis—and it is a meta-analysis of other research, not an original study. Just take as given that the analysis is correct, and screening for rare Disease A on net has no effect on life expectancy. Almost no one actually gets Disease A, but everyone is screened for it, and that has some diffuse cost to life expectancy: Screen enough people enough times and someone will d…
This is the pertinent quote: > “Cancer screening was never really designed to increase longevity. Screenings are really designed to decrease premature deaths from cancer.” Explained another way, Dahut said, if a person’s life expectancy at birth was 80, a cancer screening may prevent their premature death at 65, but it wouldn’t necessarily mean they’d live to be 90 instead of the predicted 80. Personally I think this…
The paper [1] is more well written and clear than the CNN article. They were comparing the aggregate life expectancies of people who went through regular screenings vs those who did not, and there was near zero difference except for colorectal screenings where the difference was about 4 months of difference. The paper is indeed presenting strong evidence that regular screenings have minimal value. [1] - https://jaman…
That sounds, uh, significant. So to clarify, does that mean people gain 4 months on average by getting this screening? Those who get the cancer gain years, and those that don't gain 0, so the average is 4 months?
I am skeptical of the implied lesson of this analysis—and it is a meta-analysis of other research, not an original study. Just take as given that the analysis is correct, and screening for rare Disease A on net has no effect on life expectancy. Almost no one actually gets Disease A, but everyone is screened for it, and that has some diffuse cost to life expectancy: Screen enough people enough times and someone will d…
Why? Imagine 1 million people get tested. Well we know exactly 1 person (on average) in that group is going to have the disease. But our 99% accurate test will ring a positive 1%, or 10,000 times. So the odds that you really have the disease are the odds that you're that 1 in 10,000 which is 99.99% against! Well just run the test again. Oh no! It turns up positive again! What are the odds it's two false positives? 99%! Same math. Now we know that 1 person has the disease, but our test will show 1%, 100 people, in the 10,000 as being positive. So your odds of having it are 1 in 100, or 99% against.
I'm not especially interested in being tested for rare conditions.
Me before reading: "this study, like ~every study, will detect no effect on all-cause mortality because that needs a crazy big sample size" After reading: "this study, like ~every study, detected no effect on all-cause mortality because that needs a crazy big sample size" A three-year study where one group magically had zero car crashes would need a sample size of 5,000,000 to detect a difference in all-cause mortali…
(The headline is probably technically true, but I think it is intentionally misleading and disingenuous.)