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Progress against Economicitis?
Jason Shafrin, the Healthcare Economist, has a nice post explaining how a statistical illusion can make early screening for disease appear much more effective than it really is.
Here is an example using the dreaded disease economicitis. Let us divide people into 3 groups.
- Healthy: You live forever.
- 1st stage economicitis is asymptomatic. Life expectancy when 1st stage economicitis begins is 10 years. One half of economicisits cases are 1st stage.
- 2nd stage economicitis appears when individuals mysteriously grow a third or possibly fourth hand. Life expectancy with second stage economicitis is 2 years. One half of economicitis cases are 2nd stage.
Before any screening was developed, individuals would learn they had economicitis when they started growing extra hands. Thus, documented life expectancy for those with economicitis was 2 years, since all individuals who were recorded as having economicitis were in the 2nd stage.
Let us assume that a screening technique is now available. If the screening device is able to detect 100% of stage 1 and stage 2 economicitis cases, then we will see that life expectancy will increased to 6 years (10/2+2/2=6). Statisticians looking at the data may claim the following: “The economicitis screening test has increased life expectancy after diagnosis from 2 to 6 years!”
This claim, however, is false since there is no effective treatment for economicitis. The increase in average life expectancy is not due to any improvement in health care, but only because the relatively healthier individuals with 1st stage economicitis are now being detected by the test.
Many years ago, David Plotkin had a article in The Atlantic dealing with this issue and others with respect to breast cancer. The statistics are somewhat out of date but the article remains of real value.
Posted by Alex Tabarrok on December 13, 2008 at 07:40 AM in Medicine | Permalink
Comments
individuals mysteriously grow a third or possibly fourth handAnd those third and fourth hands are invisible.
Posted by: brec at Dec 13, 2008 10:15:45 AM
I don't get it. All victims go through both stages, spending 10 years in the first stage and 2 years in the second stage. How can there be the same number of stage I and stage II victims alive when screening begins? And when screening begins many of the stage I victims will be nearing stage II, so their life expectancy will be less than 10 years.
Posted by: puzzled at Dec 13, 2008 3:40:18 PM
If you assume everyone passes through both stages, the numbers don't seem to add up in the steady state. However, suppose that in any given year, there is a small risk of getting first-stage economicitis and a larger risk of getting second-stage economicitis? Most people don't benefit from early screening since they skip the first stage, but those who do can drive up the average life expectancy once it becomes known how early they get it and how long they live with it.
Posted by: Brian Slesinsky at Dec 13, 2008 5:20:02 PM
So it looks like the old adage really is true: figures don't lie, but liars figure.
Some things never change. :-)
Posted by: Doh-San at Dec 13, 2008 6:45:11 PM
the analysis misses a further "statistical illusion" which would also appear to increase the life expectancy. since those with the advanced disease die sooner, there are fewer of them around, so in fact more than half of those diagnosed with the disease will have the less advanced version.
Posted by: at Dec 13, 2008 9:01:40 PM
How is it possible that half the cases are stage 1 and half are stage 2, given that there is no effective cure and stage 1 is longer? Or, is my assumption that stage 1 is followed by stage 2 incorrect? Should these be called "type 1" and "type 2"?
Posted by: zbicyclist at Dec 13, 2008 10:56:16 PM
If you want to make the example work with "stages", then change the life expectancy of stage 2 to 10 years. Then pre-screening the life expectancy of someone diagnosed with the disease was 10 years. But now post-screening it is up to 20 years (call it 15 on average, perhaps).
From the way it is described it seems these should be called "type 1" and "type 2". But then if type 1 is asymptomatic why is it even classed with the other one?
Posted by: Andy at Dec 13, 2008 11:26:58 PM
You've got to be kidding. Surely, when medical journals compare the stats from before (when only stage 2 was detectable) to after (when both stage 1 and 2 are detected), they understand that to make a valid comparison in life expectancy, they have to compare life expectancy *from stage 2-onset* in both cases.
RIGHT?
If medical journals were really fooled by this, and if Shafrin is presenting it accurately, that I'm truly appalled at the scientific illiteracy of modern medicine.
Needless to say, I'm pretty sure Shafrin is leaving something out.
Posted by: Silas Barta at Dec 13, 2008 11:35:33 PM
This analysis ignores the fact that wide scale screening is only done if we have 1) a cure or 2) effective treatments to prolong life or 3) treatments that only work in earlier stages.
if you could cure economicitis in stage I, then a screening program would make sense and would truly increase life expectancy. however, in the real world, if no cure/treatment existed then there would be no screening program.
Posted by: BK, MD at Dec 13, 2008 11:46:06 PM
Another variable involves whether there's any difference in seriousness of economicitis cases. Otherwise, your screening program may detect a lot of the not-very-serious cases (where your additional hand grows so slowly that you usually don't transition to stage II before something else kills you).
Orac at Respectful Insolence did a really wonderful couple of posts on this and related ways in which improved detection of cancer often makes cancer treatments look like they're improving when they're not.
The link is http://scienceblogs.com/insolence/2008/06/the_paradox_of_screening_mammography_and.php
That post also has links to other posts he's made, explaining some of the underlying concepts in more detail.
Posted by: albatross at Dec 14, 2008 12:22:54 AM
This is RIDICULOUS! Everybody knows that you can live for up to 12 years after being diagnosed with Economicitis by a simple treatment of reading Paul Krugman columns faithfully ever month. Once you lose your ability to do economics (as has Paul Krugman), you can live a relatively normal life like most people. You'll still grow the extra hands eventually, but you won't need them once you've adopted to Krugman Cure.
Posted by: Russell Nelson at Dec 14, 2008 1:25:10 AM
I don't see how this makes any sense at an individual level. Say you are a woman in your 40's and you either have breast cancer or you do not. If you have it then obviously it is good for you to have a mammogram, and if it doesn't find the cancer then you have not made your chances of survival worse. If you don't have cancer then unless the X Rays are giving people cancer then nothing is made worse by having a mammogram.
If the mammogram finds cancer then it is either treatable or it is not. If it is not treatable then you have not been harmed by the mammogram. If it is treatable then the mammogram improved your chances of surviving. So for the mammgram to not significantly help people in these studies there are 4 possibilities:
1. The mammogram is hurting people about as much as it is saving people, perhaps with radiation causing cancer. This would be an amazing coincidence that different schedules of mammograms and different machines exactly counterbalance detection with increasing cancer through radiation.
2. The statistics are so flawed in some way that nonsensical results are obtained.
3. Breast cancer is always incurable so detecting it is pointless. We know this is not true.
4. The tests are so incompetent they are hardly worth doing.
Detection through mammgrams cannot hurt and can only help if you have cancer. So what they are really saying is that breast cancer is sufficiently rare that it is not worth the trouble to check for it. But in hindsight it was worth the trouble if you get cancer. In hindsight most women would agree that if they had gotten cancer then the mammogram might have saved them. Therefore mammograms are worth getting and the statistics are nonsense.
Posted by: RCH at Dec 14, 2008 9:22:14 PM
RCH,
your analysis is based on a faulty assumption. you are assuming that mammograms are 100% accurate. they are not. mammograms will occasionally (IIRC, 3-5% of the time) find cancer where none exists. this does lead to harm to the women as she had to undergo invasive tests (e.g. biopsy, lumpectomy, mastectomy) that she would otherwise have not undergone. these tests carry non-negligible complication rates.
the question then turns into, do mammograms help more women than it hurts? this only holds true for women between 40 or 50 to about 70 or so. in the earlier ages the rate of false positives is too high and in the later ages the likelihood of the woman dying from newly found breast cancer is so much smaller than dying from other causes that the test does not lead to increased survival.
Posted by: BK, MD at Dec 15, 2008 2:24:28 AM
"in the earlier ages the rate of false positives is too high and in the later ages the likelihood of the woman dying from newly found breast cancer is so much smaller than dying from other causes that the test does not lead to increased survival."
Sorry, I don't agree with this. Doctors often have this line about how some tests for cancer, heart disease, etc are not worth doing, but the statistics don't measure the pros and cons for an individual. For a person cancer is a big thing, and the idea of a mammogram finding cancer in early stages can be worth much more than the equivalent money spent on say pizza night.
Also the test *must* lead to increased survival if the mammogram find early breast cancer that is treatable. On the average perhaps not, but for those it helps it makes sense for them to have it. A single event is said to make poor statistics, and a single life doesn't measure well against large samples of the population. If a person is terrified of cancer it might make sense of them having peace of mind by having tests, while some others might be happier to save money and take the chance of dying from cancer, and spending the money on something they enjoy.
Mammograms often find cancer if it is there, and if someone has cancer or will have eventually they won't care about false positives or risks of dying from other things. If they don't have the test they will rue the day their doctor told them it wasn't worth having a mammogram.
What you are saying really only applies to people who never get breast cancer anyway, so the mammogram is an unemotional issue. It's like fire insurance, calculating that it isn't worth buying looks pretty bad after your house burns down.
Posted by: RCH at Dec 15, 2008 3:21:32 AM
RCH you are still neglecting that the treatment itself has quality of life costs and carries significant risks.
Sometimes the treatment will kill or seriously injure you and it has some unpleasant side effects, so some patients will die or suffer significant reduction in quality of life from treatment for cancer which they did not need. What you have to do is balance the injury suffered by patients who received unnecessary treatment against the benefit to those patients who received needed treatment they would otherwise have missed.
Posted by: Brett Dunbar at Dec 15, 2008 3:56:00 AM
Brett I agree with you, but what you are saying is not what the trials were about. Say for example you like pork sandwiches a bit more than chicken sandwiches. Someone does a trial with a million sandwich eaters over 10 years and finds that chicken is 51% better for heart disease compared to pork, though it may be the crackling is worse than the chicken skin in other studies. This is a statistical decision because someone can just change to chicken. Each time a new trial comes out then people can change their lives in trivial ways and eventually find an optimum diet and lifestyle, and this is a good way to use statistics.
However cancer is not statistical it is chaotic, which is why it doesn't mean much to use trials this way. If you have cancer it is a catastrophe, and a person who gets breast cancer feels a thousand times worse than someone who doesn't get breast cancer feels good spending the mammogram money on pizza night. Cancer destroys that persons life and the lives of their friends and family to a significant degree. In the sandwich analogy it would be like comparing eating chicken sandwiches to eating live frogs. One is so unpleasant that it means little whether one choice is marginally better than the other statistically.
So it is not valid to decide mammograms are not worth having because they have a 49% mortality versus a 51% mortality to spend the money on something else. When a doctor tells a woman not to have a mammogram, and then she gets cancer and realises the mammogram could have saved her life, she realises it was not a 49% decision.
In society people overprotect themselves. They build bridges, cars, planes, etc far more safe than they need to be because engineers understand a catastrophe costs far more than just building shoddy planes and paying extra insurance premiums. It is the same with food additives, prescription drugs, toxins in food, etc, it is accepted that it is not the same to allow these to kill more people because it is cheaper to pay for more funerals, etc.
But these studies are evaluating breast cancer like a kind of sandwich, tell women not to have tests and maybe die because on balance it saves a small amount of money on medical insurance, or some tests are a waste, or some people get false positives for a short time. The real balance here should be how often are tests needed to protect women from catastrophe in the most optimum way, and I don't see this issue addressed in these studies at all.
A small percentage of women would receive a priceless gift of extra life from mammograms and a lot of other women would be inconvenienced, and perhaps a few even die early from radiation. Somehow that needs to be weighed up in the choice, whether saving a small statistically marginal group is worth it or not.
Posted by: RCH at Dec 15, 2008 5:03:43 AM
RCH,
your comments don't make much sense in the context. we are talking about a screening program. by definition that includes a large number of people. whether or not a screening program is beneficial or not depends on whether or not it helps more people than it hurts.
no one is going to stop an individual from getting a test she desires. the doctor may tell you it's not worth it, that more harm will come from it than good (on average) etc, etc. yet if you are willing to pay for the test yourself and assume the risks (i.e. absolve the doctor of all responsibility when the contrast dye in the CAT scan you demanded destroys both of your kidneys) then there will always be some doctor out there who will do the test.
you are still underestimating the false positives. breast cancer may be one of the most common female cancers, yet overall it is still fairly rare. that means the number of people who undergo invasive tests as a result of a false positives dwarf the number of people whose lives are saved. how would you feel if you underwent a modified radical mastectomy as result of a falsely positive mammogram reading? (i literally saw this happen a few months ago. a woman underwent a MRM for what turned out to be a benign enlarged lymph node that looked just like a cancerous lesion on mammogram). what do you plan on telling all those women? how many women's bodies are you willing to disfigure to lengthen one life?
if someone has cancer or will have eventually they won't care about false positives or risks of dying from other things.
this is just plain false and leads to be question if you have any medical experience at all. a 65 year old male newly diagnosed with prostate cancer isn't going to stop worrying about his congestive heart failure and COPD. it'll take at least 20 years for the prostate cancer to metastasize and kill him. by that time he'll have died twice from his CHF. and yes, they will care about false positives. do you think the person who had a false positive CAT scan indicating rectal cancer is going to be happy that he now has a permanent colostomy as a result of removal of half his colon?
but the statistics don't measure the pros and cons for an individual.
yes, they do. look up the work up of a deep venous thrombosis (DVT) and pulmonary embolism (PE). it may not be cancer, but it is an easily digestible example. the amount of testing that is done is determined based on what risk level you fall into. breast cancer is done the same way...and you can find algorithms online.
Posted by: BK, MD at Dec 15, 2008 5:31:36 AM
Thanks.
I have an exam coming up and I was going to use this example. I read the same idea in a breast cancer book, somewhere. I expect the committee to call B.S., but now I have a good reference.
RCH,
I think the problem is that we don't necessarily know when cancer is deadly and curable versus non-deadly or non-curable.
Posted by: Andrew at Dec 15, 2008 5:33:21 AM
A small percentage of women would receive a priceless gift of extra life from mammograms and a lot of other women would be inconvenienced, and perhaps a few even die early from radiation. Somehow that needs to be weighed up in the choice, whether saving a small statistically marginal group is worth it or not.
isn't this exactly what you disagreed with earlier? when i explained that in young women the rate of false positives is too high mainly because the breast tissue itself is dense which makes differentiating cancer difficult and due to the relatively low rates of cancer in young women. and when i explained how in much older women even if you discovered cancer it would affect their life expectancy because they would die of something else beforehand. why should these women undergo invasive tests and potentially dangerous chemo and radiation for something that isn't even going to kill them?
Posted by: BK, MD at Dec 15, 2008 5:36:54 AM
"the amount of testing that is done is determined based on what risk level you fall into. breast cancer is done the same way...and you can find algorithms online."
BK, I understand the points you are making, but that is not how it is done in the real world. Algorithms for example are currently creating an economic crisis rivalling the great depression. Just because someone can make a plausible statistical argument doesn't mean it is right.
Take AIDS for example. It is well known that if you took the amount of money spent on that research, and spent it more cost effectively on other medical research many more lives would have been saved. Issues like this are utilitarian, as Mills said, money is generally spent to give the greatest happiness in society, which is poorly measured by algorithms.
Generally society was much happier to spend money on AIDS even though more people died of other diseases, because AIDS was so terrifying and threatened to become a much worse epidemic. We allow people to smoke tobacco and ban marijuana even though tobacco kills far more people, if indeed marijuana kills anyone at all. Yet we are happier as a society to allow people to die, including of breast cancer from tobacco, put some taxes on cigarettes and some warnings on the packets.
These are the kinds of solutions a society selects in real life, measuring up the misery of depriving people of freedom to smoke compared to millions of additional deaths from cancer. In a democracy we would vote for this over and over. In the same way issues on breast cancer are not statistical and not based on algorithms but on a political process where overall people are most happy with the system.
Medical insurance companies will agree with you that the most economical way to handle this, to minimise the premiums people pay for health care is as you describe. However in a social context women might prefer to die of complications from mammograms and reduce the fear of cancer. It might cost more in insurance, but that's how the decision will be made. I don't know what the ultimate policy would be but it will certainly not be the optimum based on some algorithms.
Look for example at emergency rooms giving expensive medical care to people that could be done far more cheaply with preventative medicine and national health insurance. Insurance companies have algorithms which demonstrate this is optimal, yet the US spends the most money for the worst medical care in all the developed nations.
Where are the utilitarian studies which show women would rather die from breast cancer than complications from mammograms? Yet someone has some algorithms that assume that the medical history of someone with breast cancer is equivalent in some way from all the different possible complications from mammograms. How do we tell that having kidneys destroyed and perhaps saving a person with a transplant is comparable to someone dying from cancer or the emotional trauma of a masectomy? From adding up the dollars spent.
But all these questions could be answered with the right questions. One could get all the complications from mammograms, examine all the emotional effects on people's families and friends, economic costs, etc and compare them to all of the emotional and economic costs of breast cancer. Then someone could indeed say with some authority that one or the other is preferable. But at this point we don't know what people would prefer, because we don't ask them. We just do statistical trials with no understanding of the effects on society and then we wonder why society almost never follows their advice.
When society matures enough to do exactly what doctors say on smoking then I will concede your argument. But currently all doctors are doing is imposing advice on people with no idea as to whether it is really the best for them. First do no harm, remember.
Posted by: RCH at Dec 15, 2008 6:51:07 AM
"isn't this exactly what you disagreed with earlier? when i explained that in young women the rate of false positives is too high mainly because the breast tissue itself is dense which makes differentiating cancer difficult and due to the relatively low rates of cancer in young women. and when i explained how in much older women even if you discovered cancer it would affect their life expectancy because they would die of something else beforehand. why should these women undergo invasive tests and potentially dangerous chemo and radiation for something that isn't even going to kill them?"
No, the difference is here the doctors and statisticians are telling patients what is good for them. Why should doctors advise people that they should prefer to die of one disease instead of another?
And the idea that the patient has the ultimate decision is a copout. The doctor with his authority tells a patient who might get cancer not to have a mammogram that might save them. One what basis do they play God with that patient's life by giving this advice? This is not informed consent, and people who got cancer might well sue doctors with a class action suit over this. People generally believe their doctors and some people will die of cancer who might have had no complications from a mammogram.
I know you can respond that someone has to make this decision or no one could advise anyone. But I am saying experts don't really know how this decision affects people beyond a statistical equivalence in dying from one thing as opposed to another.
As another example look how much money was spent to protect people against terrorism, and if you spent that money instead in research on cancer, designing car safety better, etc. Logically you could argue to people it is better to have terrorists flying planes into buildings occasionally and have less cancer, but no one would vote for you. Why is that if the algorithms are so self evident? People value a freedom from terror more than a lower mortality rate. The real factors people care about are just not represented in these studies.
Say for example a 1000 women in their 40's walk into a doctor's office over a year. Also say that X of them know they will have breast cancer and will die without detection from a mammogram. Y of them will die if they have a mammogram. If you advise the X women not to have a mammogram they will consider the advise to be crazy because it is sentencing them to death, as would the advise to the Y women on having a mammogram.
Once women know their fate then it becomes equivalent to another medical situation that happens all the time. Say the X women know they have breast cancer and will die without an operation, and the Y women will die if they have the operation. In this case the decision to operate will be based on how the patient feels, their family and friends, the chance they might live without the operation, have more time with their family instead of a sudden death in surgery, etc. This is how real medical decisions are made. You don't advise people that it is a toss up whether they prefer to die of an operation or cancer, or that this is somehow presumed to be equivalent in an algorithm. I suspect the doctors might find they had a higher mortality rate than the patients if they told them that.
The lack of knowledge in the case of breast cancer makes it become something else which it never was, a statistical argument better suited to insurance premium calculations.
Posted by: RCH at Dec 15, 2008 7:11:33 AM
BK, I understand the points you are making, but that is not how it is done in the real world.
it certainly doesn't appear that way. you seem to be ignoring everything i am saying. take this point for example which i specifically addressed above: "However in a social context women might prefer to die of complications from mammograms and reduce the fear of cancer." it doesn't seem like you understood my response.
and yes, that is the way it is done in the real world. i know, as a physician working in the real world, i've done it myself. did you even bother to look up the algorithms or are making assumptions based on absolutely zero evidence?
But currently all doctors are doing is imposing advice on people with no idea as to whether it is really the best for them. First do no harm, remember.
i don't think you know what these words mean. you have mixed up the principle of beneficience and the principle of non-malefecence. in order to do no harm, i have to deny people unnecessary test that will harm them.
And the idea that the patient has the ultimate decision is a copout. The doctor with his authority tells a patient who might get cancer not to have a mammogram that might save them. One what basis do they play God with that patient's life by giving this advice? This is not informed consent, and people who got cancer might well sue doctors with a class action suit over this. People generally believe their doctors and some people will die of cancer who might have had no complications from a mammogram.
if you don't want a doctor's advice, don't ask for it. if a doctor gave a 8 year child a pulmonary angiogram because the mother insisted on it, the doctor rightly will be drummed out of the profession. he will have subjected the child to a procedure with a high risk of morbidity and mortality for absolutely no reason. i think you need to take some time, read some books and try to understand how the medical profession really works. read up on just what evidence based medicine is. read on clinical decision making. you appear to be seriously uninformed.
If you advise the X women not to have a mammogram they will consider the advise to be crazy because it is sentencing them to death, as would the advise to the Y women on having a mammogram.
how do know which women fall into group X or group Y? how do you even know how big the groups are? everything is easy if you already presume to know which women will get breast cancer. but in the real world you don't know that.
Say the X women know they have breast cancer and will die without an operation, and the Y women will die if they have the operation. In this case the decision to operate will be based on how the patient feels, their family and friends, the chance they might live without the operation, have more time with their family instead of a sudden death in surgery, etc. This is how real medical decisions are made.
this has got to be the first right thing you've said yet. no doctor is going to force someone to undergo a surgery they do not want.
Posted by: BK, MD at Dec 15, 2008 2:34:14 PM
My brother in law, a pulmonologist, called this "lead time bias". Wikipedia has a short article, http://en.wikipedia.org/wiki/Lead_time_bias
Posted by: Charles at Dec 15, 2008 6:01:51 PM
There are a couple different ideas getting tangled up here:
a. It's possible to have medical decisions that are better for the system but worse for individuals affected. For example, if mammograms had no bad effect on the patient and false positives were quickly screened out by some riskless, painless better test (so nobody ever had a biopsy done because of a false positive), then health insurers and medicare and national health systems would be doing a straight cost/benefit analysis--is the small number of added lives saved per year worth the extra dollar cost of giving every woman over 30 a mammogram every year? At some point, the answer has to be "no" for the insurance company or government, just as it has to be for the individual (do you want to spend your whole net worth for a riskless, painless test that has a one in a billion chance of saving your life?) It seems to me that this is the case RCH is hung up on.
b. Risks from the test, or false positives that lead to painful or dangerous further testing or treatment, change the equation for the individual patient and the insurer. Frex, a colonoscopy or a chest X-ray has some risk involved, but there are times when you'd be nuts not to have those done anyway. But it also wouldn't make sense to have every trip to the doctor's office involve a chest X-ray "just in case," because all that X-ray exposure isn't good for you.
And neither fits with the original topic of the thread, which is:
c. Sometimes, better tests can make it look like doctors have gotten better at treating some illness, when really, they've just learned to break the bad news to you earlier. That's important to understand, because otherwise we have a wrong picture of reality--we mistake better tests for better treatments.
Posted by: albatross at Dec 16, 2008 9:36:05 AM
Well put Albatross. I am also making the point that statistics are based on a normal curve and there is a tendency to bias the results on who or what is perceirved as normal. The people on the edges end up being seen as deviates or abnormal.
For example a shoe manufacturer might decide just to make shoes for average sized feet and regard big and small sizes as abnormal. Statistically this looks correct but it ignores the long tail of customers with unusual needs. A small book store might only stock the most popular books on the theory these are what average or normal people want to read. Amazon and Netflix though stock a larger range so people with more abnormal tastes find what they want there, and so they become bigger businesses.
In the same way medicine tends to think of normal disease and normal patients, and makes decisions on such as mammograms like this. However the abnormal patient might have other factors which need mammograms or they are more dangerous. This is seen more and more for example where people with certain genes (predisposing them to breast cancer or being susceptible to radiation) would have had the wrong advice by being treated as average.
Here is an example of this:
http://search.lef.org/cgi-src-bin/MsmGo.exe?grab_id=0&page_id=6929&query=mammogram&hiword=MAMMOGRA%20MAMMOGRAMS%20mammogram
" Japanese study in 2001 looked at the usefulness of combining mammograms with ultrasound during breast cancer screening.16
The researchers evaluated 15,139 women during a five-year period and found that the combination of mammograms and ultrasounds increased a doctor’s ability to detect breast cancer by an impressive 29%. They also found that cancers detected with the addition of ultrasound screening were more likely to be discovered earlier, and therefore were more susceptible to treatment.
An even more recent study published this year examined the ability of sonograms on their own to detect breast cancers in women with dense breasts, as mammograms done on women with dense breasts are less sensitive at detecting cancer. This study, done between January 2000 and January 2002, examined 1,517 women with dense breasts and normal mammograms.17 Sonograms done on these women detected seven cancers, leading the researchers to conclude that “screening breast sonography in a population of women with dense breast tissue is useful in detecting small breast cancers that are not detected on mammography or clinical breast examination. The use of sonography as an adjunct to screening mammography in women with increased risk of breast cancer and dense breasts may be especially useful.”
There's a tendency to see mammograms as the normal screening and sonograms and MRI as unusual, and they end up in the long tail of small numbers of doctors using them.
As another example it depends on the level of radiationa dn radioactive materials used with younger women"
http://search.lef.org/cgi-src-bin/MsmGo.exe?grab_id=0&page_id=7124&query=mammogram&hiword=MAMMOGRA%20MAMMOGRAMS%20mammogram
OBJECTIVE: A mammography unit with both a molybdenum anode and a rhodium anode, filtered with molybdenum and rhodium, respectively, was evaluated to determine which types of women would benefit from the dose savings of the rhodium combination despite some loss of contrast. SUBJECTS AND MATERIALS: In 100 women, the molybdenum anode and molybdenum filtration (Mo/Mo) were used to obtain mammograms of the right breast, and the rhodium anode and rhodium filtration (Rh/Rh) were used for mammograms of the left breast. All mammograms were obtained at 26 kVp. All milliampere-second values used to radiograph the breasts of these women were recorded. Mammograms of 54 women (30 with previous mammograms available), representing the four types of breasts as defined by the American College of Radiology, were interpreted by three radiologists. Each mammogram was assigned a grade for breast type, preference (Rh/Rh, Mo/Mo, or previous mammograms), contrast, and sharpness. RESULTS: Overall, mammograms obtained by using the Mo/Mo combination were preferred. However, for images of types 3 and 4 breasts, Rh/Rh was preferred twice as often as it had been for mammograms of types 1 and 2 breasts. The mean glandular dose for all breast types when the Rh/Rh combination was used was 42% of the dose used for the Mo/Mo combination. For a 6-cm-thick dense breast, the Rh/Rh combination required 40% of the dose required for the Mo/Mo combination. CONCLUSION: Mammograms obtained with the Rh/Rh combination carried an overall decrease in contrast and mean glandular dose. However, for young women and some women with large dense breasts, the Rh/Rh mammograms were equivalent to or better than the mammograms obtained with the Mo/Mo combination. Effective use of Rh/Rh units requires careful selection of women based on age or the amount of glandular tissue seen on previous mammograms.
AJR Am J Roentgenol 1994 Jun;162(6):1313-1317
Women who take estrogen are more likely to get breast cancer but less likely to die from it. That's because they are motivated to have more mammograms. So even though a study might encourage women not to take estrogen they live longer by taking it.
http://search.lef.org/cgi-src-bin/MsmGo.exe?grab_id=0&page_id=845&query=mammogram%20cancer&hiword=CANCEL%20CANCERA%20CANCERAN%20CANCERAS%20CANCERI%20CANCERIN%20CANCERIS%20CANCERNET%20CANCERR%20CANCERS%20MAMMOGRA%20MAMMOGRAMS%20cancer%20mammogram
"Another study, The Breast Cancer Detection Demonstration Project, analyzed over 2000 women out of a database of 46,000+ participants before concluding that the risk of breast cancer is increased every year a woman takes hormone drugs. Another study tracked over 10,000 women at risk for breast cancer plus over 8,000 women at risk for endometrial cancer for 5 years. It concluded that women who take estrogen drugs without progestins for at least 6 years have a four-times increased risk of invasive endometrial cancer, with no increase in breast cancer. But women who take estrogen drugs with progestin drugs have about a 50% increased risk of breast cancer over those who don't. The size and consistency of these studies is hard to argue with.
One of the things that has recently emerged from breast cancer/drug studies is that the combination of estrogen and progestins dramatically increases breast density. This may confound the results of mammograms. Yet women who do take drug hormones may have reduced mortality because they are more likely to get a mammogram and have early detection since they are seeing a physician on a regular basis. The answer, of course, is for women to see a doctor regularly whether or not they’re taking prescription drugs."
Dietary factors are probably more important than a genetic predisposition to breast cancer. So whether to have mammograms is also affected by what the patient is eating, but this is ignored in many studies:
http://www.lef.org/magazine/mag2004/oct2004_report_estrogen_02.htm
"According to the Breast Cancer Fund, a woman’s risk of contracting breast cancer was 1 in 22 in the 1940s. Today, it is 1 in 7. There is no end to the theories as to why this risk has increased. “Endocrine disrupters” (chemicals that mimic hormones) are a likely suspect. They are wreaking havoc on wildlife and clearly affect brain cells in the developing embryo.67 So far, however, studies have failed to show a link between breast cancer and blood levels of these chemicals. Still, they remain suspect—especially in combination with other factors.
Mainstream dogma is that exposure to estrogen causes breast cancer. By “estrogen,” the mainstream means the body’s own estrogens. This line of thinking always links variables (such as having/not having children or the age at which menopause occurs) to estrogen exposure and, hence, breast cancer risk. While this viewpoint appears to have some validity, a few things are wrong with it, including the thorny question of why, all of a sudden, exposure to something that has been a part of the human body for eons would cause cancer. It also skirts the question of why long-term use of birth control pills containing estrogens does not increase the risk of breast cancer.68
Genes are another possible explanation for breast cancer. This depressing theory implies that whether or not people get breast cancer is beyond their control and that nothing can be done about it, except having the breasts removed as a preventive measure.69 New research may put an end to the notion that there is nothing a person can do about “bad genes.”
“Bad genes” do not necessarily come from parents. Sometimes they come from the environment. Eighty-five percent of the “family risk” for breast cancer may come from something besides an inherited gene.70 Moreover, it has now been discovered that there are genes that can modify “bad genes.”71,72 In other words, you may not have to live with “bad genes.”
In addition, a new study shows that even if a person has a genetic predisposition toward breast cancer, the cancer does not necessarily activate unless the person encounters something in the environment that activates it.73 For some women, that “something” could be meat. For the first time, eating meat has been linked to genes and breast cancer.73 Families tend to share not only genes but recipes as well, and it is becoming clear that what you eat may be more important than what you were born with.
In studies that search for the cause of breast cancer, certain things consistently emerge. One is that diets rich in vegetables, soy, and green tea reduce cancer risk, and diets rich in animal fats (especially from red meat) increase risk.73-79 In a study from the Barbara Ann Karmanos Cancer Institute at Wayne State University in Detroit, beef, pork and vegetables accounted for 85% of the alterations to DNA in women, with meat causing damage and vegetables preventing it.80 Damaged DNA lays the groundwork for cancer.
The case of red meat is interesting not only because cooking it creates carcinogens, but also because the use of hormone implants in cows (which dates back about 50 years) coincides with the beginning of a major increase in breast cancer in North America.81 Countries with the highest rates of breast (and prostate) cancer also are the countries that allow such implants. North America’s breast cancer rate is the world’s highest—higher than all of South America and northern and southern Europe combined.82 Australia and New Zealand, which allow hormones to be implanted in cattle, have similarly high rates of breast cancer. In Europe, such implants are banned.
It is not hard to figure out why. Cattle implants contain 17 beta-estradiol and other strong steroids, including synthetic estrogens. Cows are repeatedly implanted, and the implants are in the cows when they are slaughtered. Guidelines published by the US Department of Agriculture and the University of Nebraska advise implanting the strongest drug last, 70 days before slaughter.83 The strongest implants last 90-120 days. Besides being in the cows at the time of slaughter, over time the hormones build up in fat.84 Fifty percent of the hormones contained in a steak may be in the fat.84 Neither the FDA nor the USDA monitors the use of hormone implants, or tests for residues in beef. Testing for the metabolites of estradiol alone would be a major undertaking, as there are more than a dozen such metabolites, and this is just one estrogen. Cows are given other hormones as well, including “male” hormones. Heifers are fed melengesterol acetate, a synthetic progesterone used for birth control and promoting rapid weight gain.
It has been demonstrated that a diet high in beef fat activates hormone-related genes.85 Zeranol, a synthetic estrogen cow implant, causes breast cancer cells to grow in the test tube. The amount of Zeranol needed to cause this growth is 30 times less than the amount that the FDA deems to be safe.86 A follow-up study being conducted at Ohio State University hopes to ascertain how much Zeranol ends up on the dinner plate and in the tissue of women with breast cancer.87 The study, which began in 2002, is still in progress. Data from approximately 200 women have been collected and are being analyzed. This important study may shed some light on at least one hormone implant. Studies on the total amount of all hormones added to American beef have yet to be conducted."
Posted by: RCH at Dec 16, 2008 8:14:43 PM
