Most cancer screenings don’t extend life, study finds
cnn.com
cnn.com
> “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 is just a matter of terminology in public health not necessarily aligning with our intuitive understanding. I presume most people would think that preventing a shortening of lifespan is prolonging your life, but the article makes clear that they are different.
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.
What if some people in the group that didn't get screening had fewer high-quality years? It might simply be that the last 5 years of life for people who are screened positive early on and who subsequently receive treatment is a better 5 years than the last 5 years of life for people who aren't screened positive early on and who subsequently have to undergo brutal hail mary treatments at the last minute.
Claiming that there are missing elements that could possibly turn the equation in favor of screening is cause for further research and analysis. You can't just claim that they fall in your favor; some diagnostic and exploratory processes due to false positives are painful and/or dangerous in and of themselves.
> What if
"What if" is right. You can't just conjure these people into existence to justify current policies, you have to find them and do the statistics.
You're 100% wrong here, this is not a given. Prostate cancer screenings, which are very common, can have both false positives as well as findings of cancer that is and would remain completely benign. These can both lead to unnecessary treatments that cause serious negative health effects, including incontinence and erectile dysfunction.
https://www.cdc.gov/cancer/prostate/basic_info/benefits-harm...
An ultrasound of the thyroid often leads to finding a nodule. Which leads to a biopsy. Which comes out indeterminate. Which leads to a thyroidectomy and life long dependence on thyroid hormones.
Another one is ductal carcinoma in situ. Read somewhere there is a 1% chance that will evolve into cancer. And yet you have women having double mastectomies and chemo for it.
This is by far the most inaccurate medical claim I've ever seen on HN. Where on earth did you get this from?
The whole point of diagnosing DCIS on screening mammography is that it avoids systemic therapy and mastectomy. It also wouldn't be bilateral.
The math is easy. If we don't have the numbers for it, then get them. Plenty of people get prostate cancer and some of them choose to just monitor. We should have plenty of information to make a rational decision. This seems preferable to blinding ourselves out of fear that we'll do something stupid with the information we might get.
This isn't a simple problem of calculating EV. Telling somebody that there's a 40% chance that the positive test is actually wrong and in the 60% case that it's right, 40% of the time it's going to be benign, but if it's not benign it might kill them but if it is benign and they do surgery they might be left wearing diapers is not a simple thing for a person to evaluate. Add to that the fact that people have a bias towards action, so doctors tend to overindex on treatment vs. just ignoring something, and you have an incredibly complex problem.
> The math is easy.
No, it's not. It's a series of probabilities combined with extremely subjective outcomes (getting erectile dysfunction may have a very different impact on your life if you're 40 vs. 80).
> If we don't have the numbers for it, then get them.
You're just trivializing medicine and medical research here. Why don't you just go ahead and build some AI that'll solve this whole problem by diagnosing cancers based on a blood sample? That seems easy enough.
> This seems preferable to blinding ourselves out of fear that we'll do something stupid with the information we might get.
Ironically what you're describing here is the opposite of everything you've just talked about. If we understand the numbers well, and from those we can conclude that tests are highly prone to false positives and thus that treatment based on positive results is more likely to be harmful than helpful, then we shouldn't take those tests. That's not blinding ourselves, it's acting appropriately based on understanding the math.
Risk of death: X% with treatment, Y% without treatment.
Risk of side effect A: X% with treatment, Y% without treatment.
Those numbers take into account the rate of false positives and false negatives. They are clear and understandable.
There are definitely situations in which you shouldn't test: where the rate of the cancer is low, the false positive rate is high, and the risk of treatment is high. In that case, the numbers can show that risk of death is higher with treatment than without, so while (noninvasive) testing doesn't make things worse if we're giving clear numbers, it doesn't help either; we might as well not test at all. But that's not true for everything. As for side effects, we should give patients clear numbers like this so they can make informed decisions.
Adding up the number of false positives and negatives, and the number of patients with various outcomes, is not comparable to using AI.
As I said above, with a positive test, work out the numbers for death and other unpleasant outcomes, with or without treatment, and let the patient decide. If those numbers would say not to treat regardless of test results, then don't test.
The study just says that most, not all, cancer screenings don't extend life. And it doesn't say whether doctors are giving patients the numbers I described. I suspect they aren't, which likely means that sometimes they treat even when these numbers would say they shouldn't.
I like your idea of working these things out statistically but by your phrasing it's not necessarily what's being done (as in there are no reliable enough numbers for odds that matter).
But even if those odds were available, no matter what patient chooses, once you tell then there is a positive result, the fact that false positive is possible and odds are not in favor of treatment so they make a choice to do nothing does not mean they get to live a normal life from now on. Patients are not pure bayesian choice machines. The choice you make will affect you in big unknown ways and the existence of such choice already affects you until your EOL and has repercussions. That cancer was detected in your body cannot be "unheard" or "unread" back. Maybe you manage to deal with it, maybe you will live in constant stress. and of course chronic stress is connected to tissue inflammation, sleep disruption and other issues.
Therefore your argument that screening is automatically good does not seem to be convincing to me
As I said above, I don't think that screening is automatically good because in some cases, working out the above numbers will tell you not to treat even if you had a positive test. Those cases should not be tested since they're not actionable anyway. That would likely be the case for a rare cancer.
I agree that a false positive is not great. But if you have the data, then the impact of false positive tests is already included in your data. You're comparing the total rates of death and other unpleasant outcomes for a tested population vs. an untested population.
If two statistical people both get cancer, one gets screened and potentially treated, and the other doesn't and they both live to 80, I would rather be the person that doesn't get treated.
A regular schedule of treatments is only better than a hail mary if you actually get more longevity from it, otherwise it's just more pain for the patient. At least with the hail mary, I only spend a short time feeling horrible before dying. This is most likely why doctors don't opt for treatment more than the average.
https://slatestarcodex.com/2013/07/17/who-by-very-slow-decay...
1. You have an aggressive (i.e. non-treatable) cancer, maybe you feel slightly off, but you go on with your life, until you finally got worse and die. Or you performed screening, focus on treatment, bankrupt your family and ... die anyway,
2. You have a slow growing cancer (e.g. prostate), live your life and die of some other causes. Or you performed screening, got surgery, got tons of problems and die of myocardial infarction (yes, that's one of complications after prostate surgery).
If you read the original JAMA publication you would notice that there is a research on quality of life metric. That metric for breast cancer is higher among non-screened women.
https://youtu.be/yNzQ_sLGIuA?si=fUttSVFQjsrIqc-p
I guess the main gist is that screening is not completely benign and a positive screen might lead to more interventions for what in the end could just be a benign tumor. Then there's the other point of detecting it late in life. Like treatment for cancer might not make much sense if you are already 89 years old
- Medical screenings themselves have iatrogenic effects,
- the false positives interventions resulting from screenings have further negative effects and
- finally the true positive interventions don't necessarily prolong life.
All in all very difficult (confounding) tradeoffs that are impossible to quantify and understand especially when the cultural pressure is to do something.
But that was 20 years ago. He lives a normal life now and has a family. I'm pretty sure chemo was worth it.
Specifically, medical interventions for cancer AS A RESULT of some types of screening do not prolong life.
Medical interventions for symptomatic cancer, and some types of screening, certainly do prolong life, and quality of life.
There are so many confounding factors in this it's hard to do something like a pareto breakdown, but it would certainly be interesting to see.
I actually do and most of it based on what I have have directly experienced with what, especially older doctors, counsel their patients.
There is a lot of literature on how doctors die [1], which also drives my beliefs.
I am also influenced and how weak the statistical significance is on evidence based literature on interventions and how often the interventions are difficult to replicate.
As always, please do your own research :)
1- https://www.thehappymd.com/blog/bid/295228/how-doctors-die
The paper is indeed presenting strong evidence that regular screenings have minimal value.
[1] - https://jamanetwork.com/journals/jamainternalmedicine/fullar...
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.
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?
If we take your theory at face value, on average the screened people would have an 8 month increase.
It also makes me wonder that if some cancers are rare enough to average to 0 months (rounded down) that could still work out to a 1/500 chance of living to 80 vs 40. Long odds it matters, but big difference if it does.
He did regular screening, nothing came up in it. When suddenly in one blood report, his counts were low that's when we did some extensive testing. Even with extensive testing, the diagnosis kept changing. From Myelofibrosis to MDS to AML to AEL.
Whole aspects around testing and related studies are very confusing. Tests are not at all accurate and testing is very expensive.
It seems like a scam when it comes to testing industry and pharma industry for such disorders. Bottomline is nothing helped in my father's case and we lost him after spending tons of money.
The fact that medical system remains such an inefficient system till date indicates to me that world leaders doesn't want to solve for health problems. It's an industry for them with lots of money. Everyone seems to be motivated to keep population seek and be subscribed to their drugs.
Sorry for the rant.
If we say that cancer screening has no effect of life expectancy, that's exactly the same as saying that it doesn't prevent premature deaths.
If cancer screening effectively prevents premature deaths, but the effect on the population's life expectancy is small, that effect is the wrong thing to be focusing on, potentially resulting in a harmful takeaway message.
That's what they've found with PSA--it kills (via treating things that wouldn't actually have killed the patient) as many as it saves.
I'm not sure what PSA you're referring to. The Prostate-Specific Antigen PSA is something secreted by the body, and not a treatment, so it can't be that one.
Are you referring to overdiagnosis (via PSA or any other screening), resulting in overtreatment?
And, yes, it's treatment of things that weren't actually going to kill the patient. It's been known for quite a while that doing the test for screening produces no increase in life expectancy.
What this study is saying is that the same problem seems to apply to most other cancer screenings.
Yes, life expectancy should count premature deaths
Saying it "doesn't extend live" goes against that, because it absolutely does increase life expectancy
Science communication is bad
The main purpose of screening for early disease or genetic condition detection regardless of the diseases or illness, cancer, heart attack, stroke, etc, is not really to prolong longevity, even though that's a wonderful side effect, but the main thing to prevent complication(s) that may arise from the late detection.
Apparently death does not incurs extra and massive medical bills, on the other hand complications will certainly do. If you connect the dots, this suddenly become a really good and plausible conspiracy theory.
It's a shame that most of the health organizations, I'm looking at you American Heart Association (AHA), are really against any form of routine screening [1],[2].
[1] American Heart Association 14-Element Screening (Maron, BJ Circulation 2014):
https://med.stanford.edu/content/dam/sm/ppc/documents/HSuper...
[2] ACC/AHA Release Recommendations For Congenital and Genetic Heart Disease Screenings in Youth:
https://www.acc.org/latest-in-cardiology/articles/2014/09/15...
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 die in a car accident on the way to or from the doctor's office. More likely the screening crowds out other more net-beneficial medical testing or is taken as some false comfort to continue an unhealthy lifestyle.
Modern cancer treatment, especially for the most common types (i.e. the most likely to be screened for) is very good, even if the cancer is caught later due to lack of screening. So even the folks who catch it early due to screening don't incur a benefit in many cases, further pushing down the life-expectancy win on average.
Still: This is like saying home insurance is a bad deal because on average the insurance companies make money. Screening is an insurance policy (not a free one, to be sure) against a catastrophic outcome.
If you're a public health authority in a utilitarian and budget-constrained mindset, sure, don't encourage screenings by the logic and findings of this analysis. But I don't think individuals should consider on-average-LE-negative screenings as something to avoid.
I'd say this depends on the nature of the diffuse negative effects you mention - if it's car accidents on the way to the doctor's office that's one thing, but if it's people dying during surgery they actually didn't need that's another
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.
Imagine you test early and often for a condition in country A much more often than country B which waits until some more late stage easier to detect symptoms occur. Now compare survivor rates. Much higher in country A! We should clearly also be testing in country B, right?
Depends. If the condition is something that doesn’t often actually kill and typically remains at a non lethal but detectable state then all you might have done is treat a lot of extra non fatal conditions that usually only is detected in country B once it evolves to a more advanced and dangerous state. You may have put many people in country A through an unnecessary, expensive, and frightening treatment regime.
The point is that these things are complex and need thorough analysis.
The risks are not 'car crash from doctors visit' they are 'got cancer from imaging', 'unnecessary surgery and complications', etc - the risks are directly related to the screening.
This is an active topic in medical ethics as well which you seem ignored of (no offense intended), given that you are framing this in terms of insurance or public health from the perspective of a beaurocrat - the bottom line is that if your screening is more likely to kill or maim you than the thing being screened for then that screening shouldn't be standard practice, and when it is less clear cut than that you still have to make a determination about which screenings make sense to perform on a population level.
That is something that a caring doctor has to think about as part of their duty, there is the very real potential to do much more harm than good by being thoughtless about the interventions you perform.
I’m arguing that this specific analysis has very little to tell individuals about how they should perceive the value of any particular test. A different analysis—looking at the particular negative outcomes of the testing itself or the reaction to false positives—would be a different story entirely.
What do you think the individual patient should take away from this analysis in actionable terms?
But to answer your question; 'nothing'. This is interesting but it isn't actionable.
Most cancer screenings don’t ultimately give someone extra time beyond their regular lifespan, according to a new review of clinical trials involving more than 2.1 million people who had six kinds of common tests for cancer.
This is trivially misreadable as “an individual with cancer who catches it early via screening doesn’t see appreciable lifespan benefits”, which is decidedly not what the analysis purports to show.
The use of “someone” makes me question whether the author of the CNN article understood the analysis in the first place. The phrase “extra time” is also particularly strange, since it’s something of a loaded term in the world of serious disease. I don’t get a cancer screening because I want “extra time”. I look to get on the early-access list for an unapproved chemo drug because I want “extra time”. The article goes on to frame the results in a way that easily could be misunderstood to be the benefits for sick patients to early detection rather than the average benefits across the entire population, sick and healthy.
I dunno about all types of cancer (and screening methods), but mammograms definitely are not helpful and this has been known for a long time [0]
[0] https://www.vox.com/2015/7/6/8900751/breast-cancer-overdiagn... (2015)
> I often wonder how different public attitudes would be towards treatment and prevention if the US healthcare system wasn’t profit driven.
i seem to also remember seeing they offer incentives like first screening only 700 yen (about 5 bucks) etc
so, yea, different systems, different incentives i guess
Open: https://simplecast.econtalk.org/episodes/vinay-prasad-on-can...
Apple: https://podcasts.apple.com/us/podcast/econtalk/id135066958?i...
Highly recommend the episode and show. The gist is that cancer is only 4% of deaths, and screening only reduces those 4% by 20% (so it does not help whatsoever 80% of cancers). But there is a lot more to the episode.
The most important thing you need to do to prevent early death is reduce heart attack and stroke, and that requires better diet and exercise. Really the best drug of all is diet and exercise.
Also cancer screenings happen in the US. Thus 750k deaths without screenings and 80% of that = 600k deaths with screenings and 150k deaths postponed.
Are they using some unusual definition or something?
I'm having trouble finding numbers, but the comment by Vinay was basically saying that each screening is testing for something that has 1-4% chance of killing you. Not that 4% of all cause mortality is cancer, which is incorrect. In the context of individual screenings per cancer, the numbers roughly make sense based on what I could find, but I am by no means an expert.
The specific video/content they are rehashing is the one by Vinay here - https://www.youtube.com/watch?v=-9hQO7X1bmU
I'd highly recommend listening to the Econtalk conversation as there is a lot of nuance behind why screenings (at least as they are done today) could potentially be a net negative at the individual level and don't seem to have improved all-cause mortality in a significant way (according to Vinay).
Critically, these studies are backward looking they can tell you want taking such a test in 2017 followed by getting treatment in 2017 might do, but that doesn’t directly translate to what taking a test in 2024 would be worth.
As to changing all-cause mortality, when you’re talking 8 billion people even moving the needle by a single day represents another 5 years for 4 million people. That’s a big deal.
Treatments for the young tend to move the needle more because the young are likely to live longer. However in the developed world we’ve mostly plucked the low hanging fruit. That’s more or less the definition of a developed country, the obvious routes for development have already happened.
https://jamanetwork.com/journals/jamainternalmedicine/fullar...
and I do not like it. It suffers from what I consider an extremely common problem in statistics: if you define the question poorly, then your output is garbage no matter how fancy or careful your analysis is.
We can start with the beginning of the abstract:
> Importance Cancer screening tests are promoted to save life by increasing longevity, but it is unknown whether people will live longer with commonly used cancer screening tests.
I have never heard of a doctor suggesting a cancer screening by saying "this might save your life by increasing your longevity." What does that even mean?
So let's try to figure it out. The paper uses the terms "lifetime" and "longevity" somewhat interchangeably, and it does not define either term. The best I can figure out is that, for an individual deceased person, they have a certain lifetime in days from when they were screened to when they because deceased. (Or a certain lifetime in days from birth to death, and I'm not sure this distinction matters.)
Great, but this is only for one patient. What about for a sample of patients or for a population in general or for the probability distribution of lifetimes of a given patient conditioned on whether they do or do not get screened? The article does not say, and a single "lifetime" number is not a probability distribution. Is it an expected value or a mean? A median? A mode? No comment.
One of the headline conclusions is:
> Based on the observed relative risks for all-cause mortality and the reported follow-up time in the trials, the only screening test that significantly increased longevity was sigmoidoscopy, by 110 days (95% CI, 0-274 days) (Table 2, Figure 2)
Figure 2 is useless. Table 2 is somewhat informative, and it has a column for relative risk of all-cause mortality and a column for lifetime gained and its 95% CI. But WAIT A MOMENT! The only way you can know the lifetime of an individual patient is if they're dead. If they're dead, their risk of all-cause mortality by the time they died is 100%. That's not 100% plus or minus something with some relative risk thrown in -- they are dead enough to have a date of death so that someone could compute their lifetime! Or maybe "lifetime" means something else, and the authors didn't bother to figure it out and say what they meant. So what exactly is this paper even analyzing?
So I suspect this is a meta-analysis of studies, of which some may or may not have been high enough quality to define their terms, and probably several of which used "lifetime" to mean some estimated property of a distribution, and this meta-analysis completely failed to figure out what the included studies were talking about.
So I rate this meta-analysis as almost entirely useless, on account of it failing to actually analyze anything that makes sense.
So I don't think any conclusions can be drawn. Although... ACS puts the lifetime risk of colorectal cancer at 1:25 or so. So one might naively translate a 110-day lifetime extension for everyone to a 110 day · 25 = 2750 day = ~7.5 year expected lifetime extension for people who actually get colorectal cancer. Sign me up -- 7.5 more expected years of life and presumably more than that of quality life years in the event I contract a not-particularly-rare disease sounds like a pretty good deal. (Colorectal cancer screening is not all that unpleasant, and I apparently only have a 96% chance of the screening being unnecessary.)
Also not that harmless as you think. Only you suggest to perform it on 24 other patients who won't ever have a colon cancer. And that might be you, right? With the real risk (albeit small, but you need to multiply it by 25) of having a serious complication which eventually may result in a premature death.
This statement makes it clear what's going on. In ML terms: class imbalance. 99.9% of people won't ever get colon cancer, and therefore won't ever benefit from a colonoscopy. It won't make any statistical difference in overall population survival. But for the 0.1%? It will save their lives.
The lifetime risk of being diagnosed with colorectal cancer is ~4%. (With the odds trending higher for the younger generation.) The risk of _death_ from this cancer is ~1%.
But they may have complications from a colonoscopy, that's the idea. No test is completely harmless, even a blood work. You save some lives but may loose others, that's the point of the paper. And of course you waste resources that can be used to find a cure.
So, while I see the "statistically" part, asking everyone to get zero screenings until you start coughing up blood (or whatever happens when the cancer starts showing very obvious signs)... it just seems weird on the individual level. Nobody knows (nor can they know) if you're the person who would be cured with treatment, or if you're the person whose outcome wouldn't have changed a bit with treatment (for better or for worse). That question matters individually, and while "statistically you're slightly more likely to be in the second group" according to these studies, that doesn't make me feel great about just declining all screenings.
Or your screening might have caused that tumor? X-rays are not harmless and they can cause cancer. Other screenings have their respective complications. Aren't you disturbed by a thought that maybe you wouldn't have any cancer if not for screening? Or you would have a healthy colon if not for the intern who perforated it during colonoscopy?
In colonoscopy, the entire colon is examined by using a long flexible tube. In sigmoidoscopy, only the lower portion of the colon is checked, again by using a flexible tube.
The things that come to mind is that sigmoidoscopy may be better tolerated by patients or have fewer complications.
They are also dissimilar in their chances of presenting early with symptoms making screening less useful vs those that don't present early.
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.
That is shockingly bad. An extra three months of life is not nothing, but not exactly a clear win to push people towards the added stress and effort to be screened.
You're conflating this with individual patient decisions.
The real cost of a preventive health scan goes well beyond the price tag - https://news.ycombinator.com/item?id=37266189 - Aug 2023 (254 comments)
- Early testing means more visits to the hospitals/clinics. Those are famously dangerous places to get sick.
- False positives mean unneeded treatment. That can shorten your life.
- Finding things earlier also means earlier treatment. That can kill you. Every trip to a hospital means a non-zero risk of catching MRSA and other nasties.
- Some things would be handled by the immune system anyway. The treatment might provide no benefit over an ignorant outcome.
I also find it easy to believe that among all the oncologists and hospitals, some of them might be at best neutral, or even net-negative in mortality and morbidity. This is about the whole population, not just leading units at famous hospitals. There are doctors out there with the ethics of a bent mechanic.
That can only be that these experts disagree with the study, because if it were properly conducted such that its findings are true, then in fact its conclusions do add up to skipping colonoscopies and mammograms.
The study is saying that the diagnostic procedures have no effect on outcome. You should not waste time on procedures that don't change outcome.
If that's your bar, then most preventative screening is probably not worthwhile.
It's pretty dishonest to be confusing the effect of screening by counting unscreened individuals.
It's like claiming that seat belts don't work by looking only at fatality figures that don't inform to what extent seatbelts were worn.
A diagnostic approach to healthcare can be easily bureaucratized (come collect your stamp after your colonoscopy!). A touchy-feely "million factors" approach cannot.
Quote:
> "Two recent data reviews deserve further mention. The United Kingdom commissioned an independent review after dissenting voices swelled, for the purpose of better informing shared decision making and educational materials about the harms and benefits of screening.6 Unfortunately the review concluded that screening mammography trials were inadequately powered to detect an impact on all-cause mortality, and therefore used breast cancer mortality as a primary outcome. They concluded a 20% reduction and used this in their discussion of harms and benefits. As noted above, cause-specific mortality is both scientifically unstable (conclusion reversal is common when all-cause mortality is considered)7 and disease-centered rather than patient centered (patients would prefer to avoid death altogether). Thus, either screening mammography does not save lives or else we have inadequate data to say whether it does or does not. In neither case can a benefit be scientifically claimed."
> "They concluded a 20% reduction and used this in their discussion of harms and benefits."
We want to do things that will help people. On an individual level, people have the right to make decisions for themselves. At the population level, we should do things that can be proven to be helpful. This leads to decisions that feel heartless - denying people a vaccine during a deadly pandemic while it is being tested; delaying or denying introduction of a new medicine that shows only marginal improvements over an old one.
So their independent review showed benefit by changing the criteria for comparison. We want to help people, and medical interventions feel like helping. Unfortunately, sometimes they can be the equivalent of The Politician's Fallacy: "There was a problem. I did something about the problem. Therefore the problem is fixed"
> "As noted above, cause-specific mortality is both scientifically unstable (conclusion reversal is common when all-cause mortality is considered)7 and disease-centered rather than patient centered (patients would prefer to avoid death altogether)."
People die of /something/. That thing becomes a target to fix; and we deploy resources to fix it. We become emotionally connected to some interventions. (Speaking personally, I'm participating in a bike ride in a few weeks to raise money for breast cancer screenings.) Some of those resources are beneficial, some are not, some may be harmful.
> "Thus, either screening mammography does not save lives or else we have inadequate data to say whether it does or does not. In neither case can a benefit be scientifically claimed."
If anyone's interested the "Wilson criteria" is the basis of decisions about screening programmes and many run programmes fail it.
I found this comment useful: - https://news.ycombinator.com/item?id=37297963
Several comments noted that a 4 month improvement in life expectancy (for sigmoidoscopy) over the whole population is actually pretty good for a low-incidence cancer. That's several years for the people who actually get it.
But the comments seem naive about the downsides of broad screening: over-treatment, iatrogenic disease, false positives, opportunity cost, etc.
Positive screening result usually leads to treatment of one kind or another. Without screening, treatment would start later, if at all. Is that a corollary of this study?
The last link explains the NCCN rationale and decision making process.
http://www.aapec.org/images/b69a380d-519a-415b-8e8c-8e7f2b02...
https://www.nejm.org/doi/full/10.1056/nejmoa1000727
https://academic.oup.com/jnci/article/106/11/dju261/1496367?...
https://www.bmj.com/content/bmj/352/bmj.h6080.full.pdf
https://jnccn.org/view/journals/jnccn/16/11/article-p1398.xm...
If you are unfortunately talking about a personal experience, sorry, but you can't confuse n=1 stories with large research studies.
"This is an important, though uncommonly discussed, issue in the translation of evidence from cancer screening trials.1 It is known that overdiagnosis (treatment of cancers that would have been no threat), and high false positive rates (misdiagnosis) lead to medical harms and unnecessary surgeries, chemotherapy, and radiation...
...margin of benefit suggested by the analysis above it seems likely that if there is a benefit to screening mammography it is balanced out by mortal harms from overdiagnosis and false-positives"
There is no study powered enough to draw conclusions on all-cause mortality, which may not be the best measure anyway.
Screening mammography unequivocally improves cancer-specific mortality. Making the leap to overall mortality is hard, and even a meta analysis is likely too underpowered given the very low overall mortality to begin with. Recall that the smaller the absolute difference is the larger the study will have to be to detect the difference.
For breast cancer we would probably be talking about something like 10 million patients to be adequately powered to draw any conclusion. The older trials also aren't useful/can't be used because the diagnosis and treatment of breast cancer is dramatically different than it was 10 years ago when BI-RADS was in its nascent stage. Accordingly it's not even possible to conduct such a study as it would be unethical to randomize millions of patients to no screening when we know it has proven benefits.
This also raises the question of which outcome measure matters more? All-cause mortality is a good one but it has both pros and cons. Pros being it captures hidden and misattributed deaths and is the least susceptible to bias. Cons include that it underestimates the impact of diseases that aren't high causes of death (i.e. if the patient population is more likely to die of something else the all-cause mortality won't change).
All of this leads to what are we trying to solve with breast cancer screening? It's unequivocal that a screen detected breast cancer is less advanced (i.e. no systemic therapy required) and is associated with cancer-related mortality benefit. The harms of overdiagnosis have also significantly lessened with modern radiology/histology classifications, biopsy techniques and treatment algorithms. Is cancer-specific mortality good enough? I would argue yes given the significant morbidity with systemic therapy and metastatic disease.
To summarize:
1. Screening mammography has been proven to reduce cancer specific mortality in many studies.
2. The only accurate statement about all-cause mortality is "we don't know" rather than yes/no. None of the studies are powered or controlled enough to draw any conclusions.
3. All-cause mortality may not be the best outcome measure to determine whether an intervention is "saving lives" and certainly is not the only measure to consider when deciding on a screening program.
So let's assume that an annual X-ray caused another cancer in women who would never develop breast cancer (i.e. 87% of them). You are saying "we don't know", but the authors of that paper are trying to answer exactly that. We may have saved lives in 13% group (that would be < 2.5% of those dying from breast cancer), but may have lost some lives in 87% group. According to the paper the net outcome is around 0.
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)
(The headline is probably technically true, but I think it is intentionally misleading and disingenuous.)