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The mammography wars heat up again

PRELUDE: THE PROBLEM WITH SCREENING

If there’s one aspect of science-based medicine (SBM) that makes it hard, particularly for practitioners, it’s SBM’s continual requirement that we adjust what we do based on new information from science and clinical trials. It’s not easy for patients, either. To lay people, SBM’s greatest strength, its continual improvement and evolution as new evidence becomes available, can appear to be inconsistency, and that seeming inconsistency is all too often an opening for quackery. Even when there isn’t an opening for quackery, it can cause a lot of confusion; some physicians are often resistant to changing their practice. It’s not for nothing that there’s an old joke in medical circles that no outdated medical practice completely dies until a new generation of physicians comes up through the ranks and the older physicians who believe in the practice either retire or die. There’s some truth in that. As I’ve said before, SBM is messy. In particular, the process of applying new science as the data become available to a problem that’s already as complicated as screening asymptomatic people for a disease in order to intervene earlier and, hopefully, save lives can be fraught with confusion and difficulties.

Certainly one of the most contentious issues in medicine over the last few years has been the issue of screening for various cancers. The main cancers that we most commonly subject populations to routine mass screening for include prostate, colon, cervical, and breast cancer. Because I’m a breast cancer surgeon, I most frequently have to deal with breast cancer screening, which means, in essence, screening with mammography. The reason is that mammography is inexpensive, well-tested, and, in general, very effective.

Or so we thought. Last week, yet another piece of evidence to muddle the picture was published in the New England Journal of Medicine (NEJM) and hit the news media in outlets such as the New York Times (Mammograms’ Value in Cancer Fight at Issue).

Before I discuss the study, let’s look at the background. As I’ve written about over the last couple of years, evidence has been accumulating that is muddying the picture regarding the benefits of screening mammography, So let’s be clear on what we are discussing here: screening mammography is different from diagnostic mammography in that it is performed at regular intervals in asymptomatic women in order to detect cancer at an earlier stage and thereby allow earlier intervention, resulting in the saving of more lives than if we waited until breast cancer produces symptoms (such as a lump) that lead to diagnosis. If a woman feels a lump or some change in her breast and undergoes mammography, that is not screening. In that case, mammography is being done for diagnostic purposes. We are not discussing diagnostic mammography. We are discussing screening mammography. I can’t emphasize that distinction enough.

What we’re discovering is not that screening mammography is ineffective, but rather that it is probably not as effective as advertised in preventing death from breast cancer, which, let’s face it, is the primary reason we subject women over age 40 to mammographic screening. The reason is that phenomena such as overdiagnosis and overtreatment, coupled with lead time and length time bias, conspire to confound what conceptually is very simple but in practice is very complex indeed, catching breast cancer at an earlier stage and thereby saving lives. Overdiagnosis, for instance, is the diagnosis of cancer that, for whatever biological reason, would never threaten the life of the patient because it either progresses so slowly that the patient dies of natural causes before it ever reaches the point of endangering the patient’s life, never progresses at all, or possibly even spontaneously regresses. Because we do not yet have reliable methods to distinguish indolent tumors from those that will grow and metastasize, we as cancer doctors have the moral obligation to treat all tumors discovered by screening as though they could potentially kill the patient. These treatments are often not benign, and can include surgery, radiation, and even chemotherapy. Overdiagnosis leads to overtreatment, and overtreatment is not a benign thing either. Unfortunately, until recently we haven’t always taken into account the potential harm from overtreatment into account or the biology of the various cancers and the very nature of screening itself, which preferentially detects more indolent disease.

As a result of the accumulation of evidence suggesting less benefit from mass screening programs than we had hoped and more potential harm than we had feared, the oncology world has been rethinking screening for cancer, in particular for prostate and breast cancer. Clearly, the most problematic cancer to screen for has been prostate cancer, because the common blood test used to detect it, prostate-specific antigen (PSA) is fraught with false positives, leading to morbid surgery (prostatectomy) or somewhat less morbid radiation therapy to treat early lesions that probably would never develop into life-threatening cancer. After all, autopsy series have shown that approximately 75% of men over the age of 80 have small foci of cancer in their prostate glands, but nowhere near 75% of men die of prostate cancer. In other words, more men die with prostate cancer than from it, and most are asymptomatic. That is why the American Cancer Society no longer recommends routine PSA screening.

Screening for breast cancer is less problematic, because mammography has a lower incidence of false positives, but, as we have been discovering, it’s still problematic. As many as one in three breast cancers may be overdiagnosed by mammography; as many as one in five mammographically-detected breast cancers in asymptomatic women might spontaneously regress. As a result of accumulating evidence, last fall the United States Preventative Services Task Force (UPSTF) revised its recommendations for screening mammography to recommend that it begin at age 50 rather than age 40. The resulting kerfuffle led to emergency meetings at various cancer centers regarding how to reassure women. From my perspective, it was depressing how much we seemed to concentrate on “damage” control and protecting the current recommendations, rather than explaining the new recommendations.

Enter this new Norwegian study, hot off the presses.

DECREASED BREAST CANCER MORTALITY: DUE TO SCREENING OR BETTER TREATMENT?

I first became aware of the new study from a Google News Alert that led me to a NYT story by Gina Kolata entitled Mammograms’ Value in Cancer Fight at Issue:

A new study suggests that increased awareness and improved treatments rather than mammograms are the main force in reducing the breast cancer death rate.

Starting in their 40s or 50s, most women in this country faithfully get a mammogram every year, as recommended by health officials. But the study suggests that the decision about whether to have the screening test may now be a close call.

The study, medical experts say, is the first to assess the benefit of mammography in the context of the modern era of breast cancer treatment. While it is unlikely to settle the debate over mammograms — and experts continue to disagree about the value of the test — it indicates that improved treatments with hormonal therapy and other targeted drugs may have, in a way, washed out most of mammography’s benefits by making it less important to find cancers when they are too small to feel.

Previous studies of mammograms, done decades ago, found they reduced the breast cancer death rate by 15 to 25 percent, a meaningful amount. But that was when treatment was much less effective.

It should come as no surprise to regular readers that the commonly accepted estimate of how much mammographic screening of a population reduces the death rate from breast cancer is around 20-25%. These numbers are based on randomized clinical trials, most of which were carried out more than 20 years ago. Based on these trials, many countries instituted mass screening programs using mammography. Because it would violate clinical equipoise, given that it is generally accepted that screening mammography decreases deaths from breast cancer, there will likely never be another randomized, controlled clinical trial of mammography, even though technology has progressed and we have better treatments that may affect the outcome. That leaves observational studies, a less rigorous form of evidence, to investigate the issue. However, it is still quite possible to obtain useful data from such studies, and that is what this Norwegian group did when they examined the effect on breast cancer mortality of introducing mammographic screening programs. The results, published in the September 23 issue of the NEJM, provide an unexpected, even startling, answer.

This study, Kalager et al, was performed in a very clever manner. To understand how it was carried out, it’s necessary to know a bit about Norway first. Norway is a nation of 4.8 million people that, because it has a centralized public health care system, has records far more complete and centralized than anything we have in the United States. In brief, this is a study that could never have been done in the US:

Norway, with a total population of 4.8 million, has a public health care system. Patients generally receive treatment in their county of residence, and there is no private primary care for breast cancer.8 The nationwide Cancer Registry of Norway is close to 100% complete.9,10 Patients are identified in the registry by their individually unique national registration number, which includes the date of birth. The registry runs the Breast Cancer Screening Program, which began as a pilot project in 4 of the 19 Norwegian counties in 1996. Two years later, the government decided to expand the program, and over a period of 9 years, the remaining 15 counties were enrolled in a staggered fashion11 The rollout of the program followed no specific geographic pattern. Since 2005, all women in the country between the ages of 50 and 69 years have been invited to participate in screening mammography every 2 years.

Before enrollment in the program, each county was required to establish multidisciplinary breast-cancer management teams and breast units.12 As a result, breast-cancer management became centralized for all residents within each county, and dedicated teams of radiologists, radiologic technologists, pathologists, surgeons, oncologists, and nurses managed the care of all patients, regardless of age.

The study followed, in essence, a staggered cohort design. The authors compared rates of breast cancer deaths based on incidence in four groups: one group of women who during the years of the rollout of the mammography screening program (1996 to 2005) were living in counties with screening (the screening group); one group of women who were living in counties without screening during that time (the nonscreening group); and two groups of historical controls who from 1986 to 1995 mirrored the screening and nonscreening group. They then analyzed data from 40,057 women with breast cancer during that period of time. In order to try to isolate the effect of the breast cancer screening program, they calculated mortality in the screening group including only deaths from breast cancer in women who had received the diagnosis after the screening program was implemented. This avoids inclusion of breast cancer deaths that occurred after the implementation of the screening program that were actually diagnoses that were made before the screening program.

In addition, the authors divided up Norway’s 19 counties into six regions, chosen for having entered the screening program at approximately the same time. Death rates were then compared separately for each region, allowing similar followup times for each region. In addition, this strategy allowed for the comparison of trends in mortality from breast cancer over time. They then performed these analyses:

First, we compared women in the nonscreening group with their historical counterparts to determine the temporal change in mortality that was not attributable to the introduction of the screening program and that was likely to reflect improved treatment and earlier clinical diagnosis. Then, we compared women in the screening group with their historical counterparts to determine the change in mortality after implementation of the screening program. In this second comparison, the difference in the rate of death between the two groups can be attributed both to the screening program and to temporal trends in mortality that were unrelated to the screening program. Thus, the reduction in mortality that was related to the screening program was the difference between the rate ratio for death among women in the screening group as compared with their historical counterparts and the rate ratio for death among women in the nonscreening group as compared with their historical counterparts.

To boil it down, using this method, the authors could come up with two numbers for improvement in breast cancer mortality over time, an improvement not attributable to screening, which is therefore attributable to better treatments, and a number that is attributable both to screening and better treatments. The result is a graph (click to enlarge):

Fig1

As can be seen, the estimate for how much of the improvement in mortality due to breast cancer between the two time periods in Norway is due to mammography is attributable to screening mammography is approximately one third of the overall improvement (10% out of an overall improvement of 28%). Moreover, statistically, there is enough uncertainty in this estimate that it could be as little as 2% of the decrease in breast cancer mortality that is due to mammographic screening. Most of this improvement in survival was observed in women with stage II tumors:

Among women between the ages of 50 and 69 years in the screening group, those with stage I tumors had a relative reduction in mortality of 16%, as compared with their historical counterparts (rate ratio, 0.84; 95% CI, 0.63 to 1.11); among women in the nonscreening group, the corresponding reduction was 13% (rate ratio, 0.87; 95% CI, 0.62 to 1.23). Among women with stage II tumors, those in the screening group had a marked 29% reduction in mortality, as compared with their historical counterparts (rate ratio, 0.71; 95% CI, 0.58 to 0.86); among women in the nonscreening group, the reduction was 7% (rate ratio, 0.93; 95% CI, 0.76 to 1.12).

Among women with more advanced tumors (stage III and stage IV), there was no effect attributable to screening. Although there was still a 30% reduction in mortality in this group, none of it could be attributed to screening. Intuitively, this makes sense; stage III and stage IV tumors are generally detected clinically because of symptoms, not in a screening program. It also intuitively makes sense that the death rate from stage I tumors would be less affected than that from stage II tumors because (1) stage I tumors would be much more likely to be overdiagnosed by screening and (2) the followup time in this study is relatively short (8.9 years for the group with the longest followup), which may not be sufficient time for the full benefit of screening to show for earlier stage tumors; and (3) stage II tumors can still be detected mammographically in asymptomatic women but, because they are more advanced, have already shown themselves to be potentially deadly. It should also be conceded that, because of improvements in imaging and in detection of lymph node metastases (such as sentinel lymph node biopsy), this result might also be partially due to selective stage migration among those who undergo screening. If that were the case, part of the improvement in survival among those with stage II disease could be apparent rather than real.

Being retrospective, this study is, of course, not bullet-proof. As the authors themselves concede, the maximum followup time of only 8.9 years may be too short for a full benefit to have been seen. In addition, because the screening program was rolled out gradually in the counties, diagnoses were made more recently in the screening group, which may actually overestimate the benefit associated with the screening program. Finally, it’s possible that, because the multidisciplinary breast cancer teams were established before the screening program was rolled out, it’s possible that some of the women in the nonscreening group might have undergone mammography associated with this, thus “contaminating” the nonscreened group and lowering the apparent benefit of screening. The authors offer several reasons why they think this latter problem is unlikely to have been significant, including how limited access to mammography was before screening programs were implemented, the fact that there was no financial incentive to providers to order mammography, and because, as expected, the implementation of the screening program in the various counties resulted in a substantial increase in the number of diagnoses of breast cancer, with no similar trend in counties that had not yet joined the screening program.

Overall, because most of the more recent observational studies of mammographic screening use historical controls without an attempt to control for the confounding variable of temporal downward trends in breast cancer mortality, the authors conclude that the benefit of screening in terms of decreasing a woman’s odds of dying from breast cancer is smaller than previously estimated. In aggregate, they estimate that, in Norway at least, approximately one-third of the decrease in breast cancer mortality is due to screening, and two thirds to other factors, which (we hope) includes better treatment.

MAMMOGRAPHY: A LONG RUN FOR A SHORT SLIDE?

Not surprisingly, there was an accompanying editorial. I was, however, rather surprised at who was chosen to write the editorial, namely Dr. Gilbert Welch, a long-time critic of screening mammography, who entitled his article Screening Mammography — A Long Run for a Short Slide? Personally, I was expecting that any accompanying editorial would be written by an advocate of mammographic screening. The crux of his argument is in this paragraph:

The juxtaposition of such a charged medical debate in the face of such an exhaustive scientific investigation is in itself instructive. For context, one trial involving fewer than 150 men who were followed for less than 2 years was sufficient to convince physicians of the value of treating severe hypertension.1 That physicians are still debating the relative merits of screening mammography despite the wealth of data suggests that the test is surely a close call, a delicate balance between modest benefit and modest harm.

Dr. Welch is referring to this study from 1967, which found a marked difference in morbidity and mortality over a relatively short followup period in men with diastolic blood pressures ranging from 115 through 129 mm Hg. The results were so clear-cut that after that study no one could argue against treating someone with a diastolic blood pressure that high. Personally, I viewed this comparison as a bit of a cheap shot by Dr. Welch in that the study he chose looked at men with a severe health condition known to predispose to stroke, myocardial infarction, and other complications. He compared this clinical situation to the screening of an asymptomatic population, where it’s known going in that it will be harder to show benefits, requiring a lot of patients and a lot of followup. That aside, though, Dr. Welch is correct that more recent evidence suggests that the benefits of mammography are more modest than we have traditionally been taught.

That brings us to the question of why this study found results different than the results cited by the USPSTF when making their recommendations. Dr. Welch offers two possibilities. First, this study could be wrong. That is, of course, always possible given that it is not a prospective randomized trial. However, situations change with time, and it is no longer possible to do a randomized trial to determine whether mammography saves lives. Clinical equipoise again. So all we are left with are studies like this Norwegian study, where investigators do the best they can to reduce confounders. Looking at the design of the study, I tend to agree with Dr. Welch that it is unlikely that these confounders would be enough to account for the difference between the much higher reductions in breast cancer mortality observed in early randomized studies (the ones cited by the USPSTF) and Kalager et al found. Most likely, Kalager et al is correct, or at least not too far off. That leaves several questions.

First and foremost, is a 10% reduction in mortality from breast cancer adequate to justify mass screening programs? Whenever I am asked a question like this (for example, about Avastin), my tendency is to respond that this is not a scientific question. It is a moral question that asks us to make a value judgment as a society. Think of it this way. It is estimated that approximately 40,000 women will die of breast cancer in 2010. If Kalager et al is correct and its results are applicable to the U.S., that means that, without screening, approximately 44,000 women would die of breast cancer. What are 4,000 lives worth? I can’t answer that question. Dr. Welch frames it a bit differently, to make the benefit seem even more modest:

If we assume that mammography screening is associated with a 10% reduction in the rate of death from breast cancer (making the optimistic assumption that all the benefit comes from screening mammograms), the 10-year risk of breast-cancer death for a 50-year-old woman in the United States is now about 4 per 1000 women.6 If we assume that this risk already incorporates the benefit of screening mammography, the risk estimate without mammography would be about 4.4 per 1000 women.

Benefits that look very modest when looked at as a risk per 1000, however, can produce fairly large absolute numbers when applied to millions of women. I tend to view Kalager et al’s results as the lower bound of estimates for the benefits of screening mammography. It wouldn’t surprise me if the true benefits are higher. Remember those 4,000 women, who are all someone’s mothers, wives, and/or daughters. However, so are the women potentially harmed:

Because we are all subject to framing effects, it is important to consider the reverse frame. The number of women who will not die from breast cancer rises from 995.6 to 996 per 1000 women with the addition of screening mammography. Although readers may each respond differently to these frames, both reflect the same absolute benefit: 0.4 per 1000 women. In other words, 2500 women would need to be screened over a 10-year period for 1 to avoid death from breast cancer.

What happens to the other 2499 women who had to undergo screening to achieve this benefit is also relevant. Estimates of harm vary considerably. In the United States, more than 1000 women would be expected to have at least one false positive result,7 a number that would be considerably lower in Europe.8 Less frequent but more worrisome is the problem of overdiagnosis. Somewhere between 5 and 15 women would be expected to be needlessly treated for a condition that was never going to bother them, with all the accompanying harms.9,10

Another estimate that I discussed came from an article last year by Laura Esserman, who estimated that to avert one death from breast cancer with mammographic screening for women between the ages of 50-70, 838 women need to be screened over 6 years for a total of 5,866 screening visits, to detect 18 invasive cancers and 6 instances of DCIS. That’s roughly three times the benefit estimated by Kalager et al.

Whatever the true benefit of mammographic screening, how we balance the potential benefits of mammographic screening with the potential harms is more of a philosophical and moral question. Science-based medicine can inform us regarding the values of mammographic screening, but it can’t tell us what we value.

A MIDDLE GROUND?

Figuring out the benefits of screening for cancer, be it with mammography or by other means for other cancers, is by its very nature a difficult issue, full of scientific and ethical confounders. Unfortunately, this scientifically muddy issue, to be applied successfully to a mass population, is often sold uncritically and with far more confidence than the data support. Mammography is represented uncritically as pure good, and women are told that every woman should start having mammography religiously at age 40. That’s why, when the USPSTF recommendations were released last fall, which stated that screening should begin at age 50 and be offered every two years instead of every year (which, by the way, is what Norway does), the reaction against them was so vociferous, particularly given that the recommendations were released right in the midst of the debate about President Obama’s health insurance reform bill and its opponents were raising the specter of arbitrary government rationing of health care. It was science-based medicine reexamining an existing accepted belief about breast cancer and running right into the perfect storm of resistance from advocacy groups, politics, and physician practice patterns. It turns out that all too often both patients and physicians want certainty, not the ever-evolving recommendations based on new science.

Moreover, there are a lot of issues at play here, as Dr. J. Leonard Lichtenfeld of the American Cancer Society points out:

We have moved to a different age, but I have to admit that I have a bias that we run the risk of going back in part to that future. Today, with screening mammograms we find more cancers that are smaller than can be detected by physical examination and no amount of self-awareness or physician awareness is going to change that. Patients and physicians have not suddenly become more astute in their diagnostic skills. If anything, they have become less effective in that arena.

There is also downsides of our success:

  • We do find breast cancers today through mammography that years ago would never have been discovered and may never have caused a woman any difficulty.
  • We do treat more women than benefit from that treatment, but we don’t have tests that can tell us which breast cancers don’t require any treatment as compared to those which are lethal.
  • We have studies that show us formal, structured breast self examinations don’t appear to save lives.
  • We have ethnic groups in this country that have had significant reductions in breast cancer mortality and others that have not, in part because too many don’t have access to quality medical care.

In short, this is a complicated issue. I am not certain that all of the relevant facts and considerations applicable to the circumstances in the United States are necessarily reflected in this particular study. Yet I suspect the headlines will be that mammograms don’t work or that they make little difference.

We must find our way out of these dilemmas. Messaging to the public has become garbled and confusing. The sad fact is that if we make the wrong decisions about the value of screening mammography, it will be years before we find out if we were mistaken.

“Dr. Len” has a point. However, he, too, is a bit guilty of black and white thinking here. He seems to think that we either preach the benefits of mammography or not. There is, however, a third way, and this was described by Drs. Kerianne H. Quanstrum and Rodney A. Hayward, M.D. at the University of Michigan in an NEJM editorial published two weeks before Kalager et al entitled Lessons from the Mammography Wars.

After describing the violent reaction to the USPSTF guidelines, Quanstrum and Hayward pointed out two very simple things. First:

In reality, this independent panel, the Preventive Services Task Force, simply recommended that routine screening mammography begin at the age of 50 years, whereas women between the ages of 40 and 49 years should make individual decisions with their doctors as to whether their preferences and risk factors indicate screening at an earlier age. The panel also recommended that screening mammograms be performed every other year, which they suggested would reduce the harms of mammography by nearly half while maintaining most of the benefits provided by annual imaging.5 In short, the panel concluded that we had previously overestimated the value of mammography: that mammography is good, but not that good; that it is necessary for many women, but not all; and that it should be performed at some frequency, but perhaps not every year, for every woman.

And second:

Behind the panel’s conclusions regarding mammography lurks an unwelcome reality that our profession has often failed to acknowledge. Every medical intervention — no matter how beneficial for some patients — will provide continuously diminishing returns as the threshold for intervention is lowered. Mammography is just one case in point. For women between the ages of 40 and 49 years, the false positive rate is quite high, and the expected benefits are quite low: more than 1900 women would need to be invited for screening mammography in order to prevent just one death from breast cancer during 11 years of follow-up, at the direct cost of more than 20,000 visits for breast imaging and approximately 2000 false positive mammograms. Conversely, for women between the ages of 60 and 69 years, fewer than 400 women would need to be invited for screening in order to prevent one breast-cancer death during 13 years of follow-up, while accruing approximately 5000 visits and 400 false positive mammograms.6 In short, as the risk of breast cancer increases, the benefits of mammography increase, whereas the relative harms become progressively less significant.

Which strikes me as exactly correct. If there’s one rule of screening for any disease, it’s that the more you screen the more disease you will find, but much of it will be subclinical and much of it would likely never have killed the patient. Another rule is the law of diminishing returns. This leads to an observation, namely that for any screening test, there will be a population for whom the benefits clearly outweigh the risks, one for whom the risks clearly outweigh the benefits, and one for whom the answer is not so clear. What we have now is a model in which a threshold is set and there is in essence a binary system: Screen or don’t screen. What Quanstrum and Hayward argue is that there should be three options, which they represent thusly (click to enlarge):

model

And, it seems to me, that’s all that the USPSTF was suggesting: That for women without other risk factors for breast cancer between the ages of 50 and 70 the benefits of mammography clearly outweigh the risks. For women without other risk factors for breast cancer under age 40, the risks outweigh the benefits. For women between 40 and 50, the answer is unclear, and these women should discuss the issue with their doctors and come to a decision based on a frank discussion of the benefits and risks, acknowledging that screening may not be right for some women under 50, while for others it is. The problem is, binary decision-making is easier than more complicated models.

In the end, that’s probably what drives me the most batty about debates over screening for breast cancer. It’s not a black-and-white question, but advocates and physicians who become invested in the status quo sell it as such. Evidence and the science change, but policy recommendations become fossilized because certainty is perceived as being better than nuance. I will admit that three or four years ago I probably would have been one of the docs circling the wagons in the face of these new studies. No longer. I also detest the “other side,” who represent mammographic screening as useless because the benefits appear to be more modest than we originally believed. I believe that patients are far more capable than we give them credit for of understanding and acknowledging that there are gray areas in medicine. We should not be selling certainty when there is none.

Posted in: Cancer, Clinical Trials, Politics and Regulation

Leave a Comment (29) ↓

29 thoughts on “The mammography wars heat up again

  1. superdave says:

    We need to emphasize what it is that actually mammograms do. I think that a lot of people envision them as breast cancer detectors, when of course they are simply tissue density detectors (as are all x rays). I am sure the medical profession understands this perfectly well, but I don’t know about the public.

  2. superdave says:

    ok I had a pretty bad typo in there but I think my point was understandable.

  3. Will the improved treatment methods and increasing survival rates of women without risk factors beyond age, who don’t have screening mammography but go on to develop a small treatable lump, offset the liability risk to the doctors who recommended waiting a few years for screening?

    Just speaking anecdotally as an asthma patient, internists seem to have varying thresholds for testing vs. wait and see for similar (at least they seem similar to me) bronchial infections. I wonder how screening mammography recommendations vary by doctor.

  4. Scott says:

    women between the ages of 40 and 49 years should make individual decisions with their doctors as to whether their preferences and risk factors indicate screening at an earlier age

    There’s one point that bothers me about this bit of recommendation, and I wonder what you think about it. Specifically, given how strongly the benefits of mammography have been (and still are) promoted, how many women’s individual preferences will NOT strongly favor annual mammograms in that age range?

    It seems to me that, in the current environment and current general thinking about mammography, this recommendation may well in practice produce results little different from “women between the ages of 40 and 49 should get annual screening mammograms.”

  5. DonSelgin says:

    Were racial differences observed? I believe Norway (and Finland) is one of the most racially homogenous countries out there, so the study results may only be applied to the main racial group in Norway. Such a study done in a Central European country, or here in America, might have produced significantly different results. Or is mammography a science that is not affected by this?

  6. David Gorski says:

    All good questions. The short answer is: Yes, it’s possible that racial differences matter, as I discussed for the USPSTF guidelines:

    http://www.sciencebasedmedicine.org/?p=3082

    The reason I didn’t delve into those issues is because this post had already hit 5,000 words.

    Another issue is that Norway has a centralized, government-run health care system with close to 100% completeness in its tumor registry records. We here in the U.S. have nothing approaching that level of control or completeness. We also have a lot of regional variation in care, unfortunately. All of this would mean that it would be a lot harder to do such a study here.

  7. DonSelgin says:

    Thank you, Dr. Gorski.

  8. Albert Macfarlane says:

    Although I realize the current Norwegian study on mammography offers no data on overall mortality, could you comment on the difficulty of showing a decrease in overall mortality (as against disease specific mortality) in cancer screening ? To paraphrase Tom Chalmers, the proof of effectiveness of a national program against dread disease must be a reduction in the number of funerals. Screening for cancer has had difficulty in demonstrating this effect, either because it is very difficult to demonstrate, or the effect of screening is so small that it gets lost in the noise. Surprisingly the only screening technique known to me with a possible effect on overall mortality is a one time abdominal ultrasound for aortic aneurysm in men between the ages of 65-79 who have been smokers.

  9. squirrelelite says:

    Albert Macfarlane,

    I’ll offer you a few of my thoughts.

    Yes, overall mortality is an important measure of the success of any public health program. Most of us non-Klingons would like to live longer and stay healthier while we do so. And, this study was looking for improvement in mortality and trying to determine how much of that change was due to screening.

    But, when studying any intervention, it may take a long time to tell if that intervention, such as screening mammography, has a real long-term effect. And, that time will vary a lot depending on the type of cancer.

    For instance, for breast cancer, I went to the SEER database

    http://seer.cancer.gov/faststats/selections.php?series=age

    and looked up some numbers for 10 year survival for women of different age groups.

    There was a small age-related difference, but all groups showed a 10-year survival of about 80%.

    Since this study only tracked a longest followup time of 8.9 years, it would be impossible to even calculate a 10-year survival rate for comparison. And, secondary consequences like dying at 14 years from leukemia presumably caused by radiation from the screening test instead of dying at 15 years from the breast cancer itself would be even harder to detect.

  10. nybgrus says:

    @scott: I would say that would actually involve doing something that many physicians these days do not do (or at least not enough) – actually talk to your patients. The goal here is not to let them make such healthcare decisions on their own – that’s why we go to medical school. The goal is to inform them, as fully and completely as possible to all the knowledge, risks, ideas, pros, cons, etc etc and have a frank discussion. We should then give our informed opinion on what we would recommend the decision to be, but yes, ultimately leave the decision to the patient. The reality is that part of patient care is, well, taking care of the patient in all aspects. For those women that we feel do not warrant a screening mammogram but they feel adamantly that they do, then the answer is indeed to give it to them. For their psychological well being, stress levels, anxiety, etc it becomes medically reasonable to offer them access to the exam. The goal would be to adequately inform these women so that as many as possible can be comfortable with not getting the screen – not to with hold the screen from everyone regardless of their feelings.

  11. Ken Hamer says:

    Given the current scare campaign (and related book and product selling) about cellular/mobile phones*, it’s ironic that while people (including women) are becoming “terrified” by low power phones they will happily expose themselves to repeated high energy doses of radiation, be it from MRIs, X-rays, or whatever, receiving perhaps a million times the radiation from the phone over the course of a few minutes or even seconds.

    *one of a gazillion articles, websites, and loonies:
    http://www.vancouversun.com/technology/Researcher+wake+call+about+wireless/3463113/story.html

    “Kerry Crofton travels with a land line phone, purposely stays in hotels that don’t offer wireless Internet in rooms and when she gives her talk tonight on the topic of wireless radiation, it will be in a downtown Vancouver venue selected because it purportedly has no such radiation.

    The Victoria-based health researcher is speaking at the wireless network-free St. Andrew’s-Wesley Church, WHERE SHE’S PROMOTING HER NEW BOOK…”

  12. John says:

    Could you point me to where I could do some reading about prostate screening? I realize it’s not your specialty, but since you mentioned it I’m curious. My grandfather died of prostate cancer.

  13. rork says:

    I think I am with Albert Macfarlane. I worrying that we have not done a good job in determining how many women we kill thanks to screening mammography and it’s consequences, not to mention the hassles and worries of getting it and getting treated when there was no need. One would think that all-cause mortality would have to be shown to be improved to consider a public health measure actionable, but think that infact the influence on mortality of screening young low-risk women is so small that we may not be able to detect it, even in cohorts of 100000 women. I’m not sure I buy that there is no equipoise, at least for younger women with no particular risk factors. I am ready to be convinced otherwise.
    In case it’s not clear, it will only take a few deaths from cancers caused by the screening, unnecessary treatments, or even just traffic accidents on the way to the screen, to counteract the small benefit for younger low-risk women. Perhaps each such effect can be dismissed as negligible, but the sum of them is what matters, and the benefit they are competing against is not very great.
    I think I need a lesson on when it’s OK to do your new thing in the absence of demonstrations that all-cause mortality is improved.

  14. Scott says:

    @ nybgrus:

    That’s more or less what I was getting at. Given how entrenched the current perceptions are, it seems to me that, if the evidence indicates that those perceptions are inaccurate, a more concerted educational effort would be in order.

  15. JMB says:

    I am a mammogram advocate, so you may not want to read this.

    First, in regards to economic incentive, any clinic doing only screening mammography will likely go bankrupt, unless it receives grants or donations. The only part of the screening process that can be considered lucrative are the breast biopsies (hence most dedicated breast centers will also offer breast biopsies if they wish to stay financially viable). Turf wars, where doctors of different specialty certification offer the same lucrative procedure, is seen for breast biopsies, but not screening mammography. I will be happy when studies show that breast cancer treatment is so good that we no longer have to catch it early by screening. If you dismiss my arguments because of my financial incentives, then you are wrong. That is black and white.

    In case it’s not clear, it will only take a few deaths from cancers caused by the screening, unnecessary treatments, or even just traffic accidents on the way to the screen, to counteract the small benefit for younger low-risk women.

    The radiation risk of screening mammography has been extensively studied. This is a good site providing an overview of radiation risk from screening mammography:

    http://envirocancer.cornell.edu/factsheet/physical/fs52.radiation.cfm

    This site provides an estimate of radiation induced breast cancer deaths from yearly screening mammography in the age group 40-50 of 8 breast cancer deaths per 100000 women. Based on the USPSTF estimate of one cancer death averted by screening mammography per 1904 women screened for ten years, the risk benefit ratio is 52 lives saved versus 8 lives lost.

    http://www.ncbi.nlm.nih.gov/pubmed/9709287

    The USPSTF notes concern about the increased radiation risk associated with BRCA1/2 mutations. This reference estimates that the benefits of early detection outweigh the risks of radiation exposure in patients with BRCA1/2 mutations beginning at age 35.

    http://jnci.oxfordjournals.org/content/101/3/205.short

    The risk of a diagnostic mammogram (which frequently involves more views of the breast) is usually no greater than one more additional exam.

    The risk of radiation in those patients receiving radiation therapy is a concern for those with biopsy proven breast cancer. An important issue is the number of extra women that will be treated for breast cancer who would not have had it discovered without undergoing screening. It is important to remember that most of the breast cancers detected by screening mammography, would eventually be detected by physical exam (usually because of interval growth). Estimates of excess breast cancers detected by screening mammography are usually in the range of 5% – 10%. In the Age RCT, the observed excess was 8%:

    http://breast-cancer-research.com/content/6/S1/P29
    http://www.icr.ac.uk/research/research_sections/epidemiology/epidemiology_teams/cancer_screening_evaluation_unit/age_trial/index.shtml

    This means that a woman with a breast cancer discovered by mammography (at least in the age group 40-50) who ignores the result, will find the lump by self exam or during a physical 92% of the time, a few years later and larger. The risks of breast cancer treatment should be considered in the group with biopsy proven breast cancer. It is a dubious argument against screening, to use the risks associated with treatment of biopsy proven breast cancer to argue against screening (are we forgetting Bayes approach?). The risks often attributed to overdiagnosis and treatment are not unique to mammography detected cancers, they are also a risk of breast cancers detected by palpation.

    There are other issues.

    To paraphrase Tom Chalmers, the proof of effectiveness of a national program against dread disease must be a reduction in the number of funerals.

    This is the paragraph from the article reporting on one of the large scale RCTs:

    One objection to the claims for the benefits of breast cancer screening is that no effect has been demonstrated on total mortality.4′ 9 This point merits some discussion. In the age group 40-74 years, breast cancer in Swedish women causes about 7% of deaths. A 30% reduction in breast cancer mortality would therefore lead to a 2% reduction on overall mortality, well within the confidence interval seen for the relative risk in table 10 after adjustment for age and county. Furthermore, after an average of 7-9 years follow up, the death rate from breast cancer diagnosed after the start of the trial (ie, the breast cancer deaths on which the 30% reduction is based) is still only about half the breast cancer mortality rate in the general population. The expected effect on total mortality seen so far is therefore only 1%, exactly as seen in table 10. This point underlines the naivety of those who ask for an observable and significant reduction in total deaths.

    “The Swedish two county trial of mammographic screening for breast cancer: recent results and calculation of benefit.
    L Tabar, G Fagerberg, S W Duffy, and N E Day, J Epidemiol Community Health. 1989 June; 43(2): 107–114. ”

    http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1052811/pdf/jepicomh00223-0005.pdf

    So the Swedish two county trial did demonstrate the expected reduction in overall mortality, but because the expected overall reduction of mortality was only 1%, it was not statistically significant. The number of women that would have to be included in the trial to achieve sufficient power to identify a significant one percent reduction in mortality could be calculated by those that are biostatisticians. It will be a large number.

    Moreover, statistically, there is enough uncertainty in this estimate that it could be as little as 2%

    What is the upper bounds of the estimate based on measures of uncertainty? One correction that can be applied to the estimate of 10% reduction in mortality is the difference expected from a biennial screening strategy versus an annual screening strategy. According to the USPSTF, the expected number of breast cancer deaths averted by the annual screening strategy between age 50-69 is 7.3/1000, compared to the biennial screening strategy, 5.4/1000. So the 10% should be multiplied by 7.3/5.4, or 13.5%. Most trials did not have 100% compliance with screening recomendations, and geographically based trials usually had some women in the area not offered mammographic screening, receiving mammographic screening (they travel the distance). Those confounding factors may also increase the percent of mortality reduction that can be attributed to mammography. There are other studies that have tried to determine the fraction of breast cancer mortality reduction that can be attributed to improvements in cancer treatment versus early detection. The estimates vary.

    In reality, this independent panel, the Preventive Services Task Force, simply recommended that routine screening mammography begin at the age of 50 years, whereas women between the ages of 40 and 49 years should make individual decisions with their doctors as to whether their preferences and risk factors indicate screening at an earlier age.

    Between the recomendations on screening mammography issued in 2002 and 2009, the USPSTF changed its strategy in arriving at a recommendation. The following is a quote from the USPSTF website (note the name has now changed as part of the health reform bill):

    In examining benefits in terms of life-years gained
    (Appendix Table 4, available at http://www.annals.org), 6 of the
    8 consistently nondominated strategies have a biennial interval.
    In contrast to results for mortality reduction, half of
    the nondominated strategies include screening initiation at
    age 40 years. Annual screening strategies that include
    screening until age 79 or 84 years are on the efficiency
    frontier (Appendix Figure, available at http://www.annals.org),
    but are less resource-efficient than biennial approaches for
    increasing life-years gained.

    The USPSTF picked the resource efficient strategy of biennial screening over the most scientifically effective strategy of annual screening from age 40 to 84.

    http://www.uspreventiveservicestaskforce.org/uspstf09/breastcancer/brcanart.pdf

    Traditionally, the USPSTF would recommend the most effective strategy based on the most lives saved.

    These arguments are not new, they have been rehashed for some time. We should give women the best estimate of risk versus benefit, note the harms that are hard to quantify, and let the woman decide. That strategy is the fossilized approach. What has changed is implying that the risks of overdiagnosis and overtreatment are a consequence only of screening for early detection (it increases by 5 to 10% with screening mammography, compared to the detection by feeling the lump), and by using the efficient use of resources to select the strategy (the old method was to calculate the cost per year of life saved – which was included in the appendix of the supporting articles of the USPSTF, and deemed acceptable for the strategy of annual screening from 40 to 84 -$50000 per year of life saved).

    Currently only 12.5% women will develop breast cancer in their lifetime. Only about 3% of women currently die of breast cancer in their lifetime. Those low percentages are why we have to screen so many women to have a small effect. That may be sufficient reason to avoid screening mammography. It is a personal choice based on personal values.

    I look forward to the day that treatment becomes so effective that we do not need to strive for early detection. Even if the 10% estimate was true, that day has not arrived. There is still reason to offer women the choice.

  16. rork says:

    The long JMB comment was interesting. But I had some issues. I’ll only point at two and they are nearly the same point.

    1) “What has changed is implying that the risks of overdiagnosis and overtreatment are a consequence only of screening for early detection”. Around there it seems like you are nearly trying to imply mammography creates no overtreatment, just because it is not the sole cause of overtreatment. I don’t follow this logic.
    2) “It is a dubious argument against screening, to use the risks associated with treatment of biopsy proven breast cancer to argue against screening (are we forgetting Bayes approach?). The risks often attributed to overdiagnosis and treatment are not unique to mammography detected cancers, they are also a risk of breast cancers detected by palpation.”
    Same logic problems for second sentence, but this time the first sentence is saying something more that I don’t get. I think it is saying you don’t think there even is any such thing as overtreatment that can be credited to the mammography, since the biopsy proves it’s “real”. Isn’t that one of the famous ways to fool your own socks off? Not all biopsy proven breast cancers detect by mammography are overscreening, true. But some of them are, right?

  17. rork says:

    Last “overscreening” should be “overtreated”. Durn.

  18. JMB says:

    I was really trying to address two issues in those interconnected statements. The first issue was how it appeared to me that in so many public discussions, the term overdiagnosis was being used with different definitions, and people were being led to believe that overdiagnosis is a problem that occurs only in women with a cancer detected by mammography, and not a problem if the cancer was detected by palpation. If overdiagnosis is defined as diagnosis of a cancer that would not cause any health problems before death of the patient due to other problems, then that is an issue for patients with cancers whether they are identified by palpation or mammography. Most patients who present with a palpable lump do not yet have health problems (other than the anxiety from the lump). By definition, it does not apply to patients who have health problems that lead to the discovery of underlying cancer (such as pain due to cancer metastasis to bone). When an estimate of overdiagnosis is cited that is in the range of 30%, the discussion is refering to this definition. The 30% can be derived from statistics recorded for survival rates and tumor staging data (and how the staging may change in an individual patient over time).

    When the definition of overdiagnosis is the excess number of breast cancer cases that are discovered by mammography as opposed to palpation, then that is solely a problem for those undergoing screening mammography. That estimate is based on comparing the number of excess cases of breast cancer discovered in the screening arm versus the no screen arm of an RCT. In the USPSTF documentation, “”Systematic evidence Review Update, Heidi D. Nelson, MD, MPH; Kari Tyne, MD; Arpana Naik, MD; Christina Bougatsos, BS; Benjamin K. Chan, MS; and Linda Humphrey, MD, MPH, Oregon Evidence-based Practice Center, Oregon Health & Science University ”

    http://www.uspreventiveservicestaskforce.org/uspstf09/breastcancer/brcanup.pdf

    If you download this pdf and find “excess”, you will see the summary of review of the literature for estimates of excess cases. Those estimates, particularly of excess invasive cancers, are greater than that observed in the AGE trial primarily because of the limited follow up time of 10 years. Excess cases will decrease between 10 and 15 years, and to a lesser extent, between 15 and 20 years. A reasonable estimate of excess cases observed after 15 years of follow up would be 5% (down from 8%). A small percentage of tumors are very slow growing, or may exhibit delayed metastasis.

    That is the attempted focus of the first point, that estimates of overdiagnosis that should be considered in the decision to have screening mammography is that percent of excess number of cases discovered by mammography compared to palpation. That figure is in a range of 5 to 10%. The 30% estimate of overdiagnosis refers to an issue that affects both screen detected cancers, and cancers detected by palpation.

    The second point was to discuss how best to use the information to make a decision about screening mammography and treatment of breast cancer. The Bayes strategy is to use the best information available at each step to make the decision for the step. If RCTs carried out to 15 years gives us information that breast cancer mortality can be reduced by detecting the cancer earlier, then screening should be performed. If the benefit of treatment in screen detected breast cancer is diluted by 5% of excess cases, then that information should be used to optimize decisions about the strategy of treatment of breast cancer. In the alternative approach, we must determine the mortality of breast cancer treatment in a patient with a non-lethal cancer – a difficult task. Determining mortality from breast cancer treatment requires a somewhat subjective distinction between dying from treatment, or dying from the cancer. In some cases it may be straightforward, in many it may be impossible. That is a factor in the use of survival curves in assessing the effectiveness of breast cancer treatment. In the case of RCTs, a patient dying during breast cancer treatment is usually classified as a breast cancer death without trying to differentiate whether the death is due to treatment or the underlying cancer.

    So that is a description of the related two points. One is an attempt to reduce possible confusion about the definition of overdiagnosis (the USPSTF appears to use both definitions in its discussions). The main idea is that what most people are defining as overdiagnosis will be observed in patients with breast cancer identified by palpation. The second is a point about the strategy to reach the optimum decision(s) in the approach to breast cancer to minimize mortality. Bayes strategies are generally accepted as producing the optimum decision to maximize a desired result when accurate measures of probabilities are available (or so the electrical engineering PhD I worked with used to tell me).

    Overtreatment is another issue with different defintions. It may be used to refer to the strategy of treating all patients with similar tumor characteristics the same way, because we cannot yet identify which tumors will progress to cause problems, and which will stay quiescent. It can also refer to choices by patients or recommendations by doctors for treatments more aggressive than suggested by guidelines, attempting to achieve an additional margin of safety, but incurring a greater risk of morbidity or mortality.

    One added note, there is always an assumption that there is a difference in screening detected tumors and tumors identified by palpation. Screen detected tumors tend to be smaller. Screening detects proportionally fewer lobular carcinomas because they are often indistinguishable from normal breast tissue. But I believe that whether the tumor was screen detected or palpated has never been shown to be as significant a prognostic factor as tumor size, cytologic measures of aggressiveness, cell type, or tumor staging.

  19. JMB says:

    I’m sorry, a correction is needed.

    The estimate of excess cases in the Age trial is greater than discussed in the review of literature in the USPSTF (the part authored by the Oregon group), probably because of the 10 follow up limitation of the reported estimate in the Age trial.

  20. JMB says:

    Follow up years… I need an editor.

    I did look up the death rate per miles driven. From the discussion on

    http://www.nsc.org/news_resources/Resources/res_stats_services/Pages/FrequentlyAskedQuestions.aspx#question11

    the automobile death rate in 2010 in the USA was .61 per 100 million miles.

    For the death rate from a car accident occurring while driving to and from a test, to cancel the benefit of one life saved in 1904 women aged 40 to 50 screened for breast cancer for ten years, the average distance driven to the testing facility would be at least 4,305 miles (one way distance).

    Yup, I’m a nerd.

    I may have been the one to talk about traffic accidents originally because of an example brought up by Lazlo Tabar at a breast cancer conference. In his gripes about the Canadian trial, he brought up the issue of counting a traffic death occurring in a screen detected cancer subject in the screening arm deaths. He also stated that he offered to go out and train the facilities how to do mammography correctly, but his offer was declined. Too bad we can’t get him in these comments, it would be very entertaining.

  21. Albert Macfarlane says:

    A reply to JMB’s eloquent posts would require more knowledge than I possess.

    However I would note that his use of the Swedish two-county trial (Tabar L. et al Cancer 1995:75; 2507) to oppose use of overall mortality as an endpoint in cancer screening is diminished by the assessment that this trial was “of poor quality.”(Lancet (2000) 9198: 129-134 doi: 10.1016/S0140-6736(99)06065-1).

    For those who are interested, a more general discussion of the bias induced by using disease specific mortality in cancer screening trials was summarised by Juffs and Tannock in their paper titled “Screening trials are even more difficult than we thought they were.”
    JNCI J Natl Cancer Inst (2002) 94(3): 156-157
    doi: 10.1093/jnci/94.3.156
    See also
    JNCI J Natl Cancer Inst (2002) 94 (3): 167-173.
    doi: 10.1093/jnci/94.3.167

    For those who don’t have time to follow this argument in the literature, consider old men with prostate cancer. Many will die with cancer present in their prostate, and even elsewhere, but the death certificate will list “pneumonia” or “fractured hip”. No one can say with 100% certainty (even with an exhaustive autopsy) whether their death is due to or even partially due to prostate cancer. This is a clear source of bias in screening trials.

    The same problem exists when following a cohort of women in a screening trial for breast cancer: when is a death due to breast cancer (disease specific death) or to another cause unrelated to breast cancer. The only undeniable event is the death itself (overall mortality).

  22. JMB says:

    The criticism of RCTs because of the subjectivity of the classification of cause of death is not an argument that can be settled by logic or calculation. The raw data must be available for someone to assess presence or absence of bias. Since the raw data is not available to you and I, we must rely on others for the assessment. Even if we had the raw data, we would just be substituting our subjective opinion for that of others.

    Ultimately, it comes down to a subjective opinion whether breast cancer was a factor in a death, or not. That subjective opinion becomes the endpoint for analysis. That is an uncomfortable position for any scientist to be in. I would rely more on the panel with a clinical oncologist determining cause of death, rather than a dedicated research physician who has never practiced medicine. A clinical oncologist is often faced with the decision whether an illness experienced by a patient is due to a coincidental disease, or is a disease process related to the neoplastic process. They have the feedback of the clinical outcomes of their assessment. That experience hones the assessment of the clinical oncologist for that issue.

    Given that the RCTs are not perfect, what to do now? That is the key question. Do we stop all mammographic screening for 15 years, and invest a large sum of money in the largest RCT ever attempted, to detect a statistically significant difference of 2% in overall mortality. The risk of that strategy is that if the value of early detection is proved, then we have lost worldwide 100,000 ? 200,000 ? (a conservative estimate) lives while waiting for proof. Those that argue that overall mortality may decrease when screening is stopped, have much shakier ground to stand on. We can calculate the risk of excess cancer deaths due to cessation of screening from the data of the RCTs. Can someone calculate the risk of excess deaths if we continue screening mammography? So far, I have only seen expressions of concern, not reproducible data that allow a risk calculation. We are pitting numbers against concerns (those concerns are valid for presentation in informed consent for value judgment, but don’t give us numbers to calculate).

    I think the better strategy is to gamble that the primary researchers involved in the original studies were in a better position to assess cause of death than the the arm chair quarterback doing a meta-analysis looking only at recorded data. If we continue screening, but continue studying the population based data to confirm that we are achieving the results we predicted from flawed trials (I don’t think there will ever be a large scale trial completely without flaws), then we will risk fewer lives than the strategy of stopping screening. Wrong one way, we lose a lot of lives, wrong the other way, we lose a lot a money, and possibly a few lives. If we are right about screening and continue screening, we have saved a lot of lives (albeit at a cost of $50000 per year of life saved). If we are right about excess cancer deaths from screening, and stop screening, then we will save fewer lives, but a lot of money. Draw the line for your decision.

    RCTs are not perfect, but they are not so easily dismissed. When the majority of RCTs support screening mammography, then it is very risky to reject their conclusions based on a controversial meta-analysis, even if the controversy is based on an identifiable source of subjective bias. There are other meta-analysis which reach different conclusions (like the one in the USPSTF).

    I do not argue that the issue is settled, I argue that there is enough data to support continuing screening mammography until further information… RCTs, population data, or advances in treatment of breast cancer advances to the point that early detection is no longer necessary… provide us with reason to stop screening.

  23. Who is saying to stop screening?

    My understanding of the recommendations is biannual screening after 50 years, and screening for anyone else who really wants it or whose doctor wants it for them.

    I’m confused.

  24. JMB says:

    Sorry I grouped people originally raising objections to the major RCTs, with others who take it to the extreme. Most who make the argument that the benefits of mammography have been overestimated based on the argument of the subjectivity of the assessment of cause of death, support the European strategy of biennial screening from age 50 to 79 (the ending age varies). The Europeans were fossilizing the European approach. There are a few who argue against any screening mammography.

    ——————————–

    I think my answer about harms of overdiagnosis and overtreatment was not straightforward. I answered it with calculations and data rather than a simple answer. So my simplest answer without resorting to calculations is yes, overdiagnosis and overtreatment is a problem for screening mammography. But the tradeoff is saving somebody from dying from breast cancer. It is the woman’s choice to balance the small chance of being saved from breast cancer because of early detection, versus the approximately equally small chance of enduring unnecessary treatment.

    If you are wondering how I arrived at that statement of the risk of overdiagnosis and overtreatment, these are the numbers and calculations. The supporting articles in the USPSTF estimated the excess number of cases at 3% or less. Those percentage figures represent the excess cases of breast cancer divided by the number of breast cancers identified without screening mammography. If you multiply those percentages by the expected incidence of breast cancer ( 10 year incidence at age group 40 is 1/69, 1/42 at age 50, 1/29 at age 60) you arrive at the risk for overdiagnosis and overtreatment by age. Those numbers are in the same magnitude as the calculated number of lives saved (1/69 * 1/33 = 1/2277 at age 40 (based on USPSTF numbers). So in the age group 40-50 one woman will have their life saved for every women who is overdiagnosed and overtreated. Since mortality from treatment is a fraction of those undergoing treatment, more lives will be saved than lost. The quantitative calculation supports that annual screening beginning at age 40 is the most effective strategy (that which saves the most lives). The USPSTF recommended the resource efficient strategy of biennial screening beginning at age 50 (80% of the expected reduction of breast cancer mortality using the annual-40 strategy, but with half the number of screening mammograms required by the annual-40 strategy).

  25. JMB says:

    Just another perspective on overdiagnosis and overtreatment (remember, the risk affects those with biopsy proven cancer). If a woman is given the choice, would you undergo treatment and suffer the harms of surgery/radiation therapy/chemotherapy if 50% of the time, it will save your life? I think many women choose to accept the harms of treatment when there is a 10% chance their life will be saved. Pose a similar question to a woman without biopsy proven cancer, would you risk the harms of treatment if there is only a 1 in 1904 chance of it saving your life, then many would reasonably decline. What is the most honest way to present the information to women?

    Overdiagnosis and overtreament is not something newly discovered. It is a new perspective on data that has been available for years. How old were the RCTs that Peter Gotzsche accepted as valid, and used as basis to arrive at his estimate for overdiagnosis and overtreatment? Since when did coming up with new phrases cause a change in the interpretation of data. What data does overdiagnosis and overtreatment refer to? We have always known that some patients with breast cancer will not die from it, even if they aren’t treated. We have always known that smaller cancers will less likely kill the patient, even if they aren’t treated. We have always known that screening mammography will detect smaller cancers than detection by palpation. We have always known that screening mammography will detect more cancers than palpation only in RCTS. Those numbers have been tracked in every large scale RCT. Nothing new there, except the spin. Calling those things a different name does not change the risk vs benefit analysis (based only on data, not labels). Sometimes it is annoying to us old dogs when somebody suggests that we never considered those problems before.

  26. JMB says:

    Correction (if anybodies still reading this thread),

    “We have always known that screening mammography will detect more cancers than palpation.”

  27. bexley says:

    Ken Hameron 27 Sep 2010 at 10:36 pm:

    Given the current scare campaign (and related book and product selling) about cellular/mobile phones*, it’s ironic that while people (including women) are becoming “terrified” by low power phones they will happily expose themselves to repeated high energy doses of radiation, be it from MRIs, X-rays, or whatever, receiving perhaps a million times the radiation from the phone over the course of a few minutes or even seconds.

    The other important point is that just like mobile phones MRIs don’t use ionising radiation (big magnets and radio waves).

  28. davidp says:

    Missing from Dr Gorski’s discussion is the impact on patients of earlier diagnosis. Is the treatment for stage 2 breast cancer less invasive and traumatic than for stage 3 or stage 4 ?

    There is a real benefit for patient quality of life to not need lots of lymph nodes removed (arm swells up, becomes very vulnerable to damage or infection) ; There is a benefit to lumpectomy rather than mastectomy ; there is a benefit to needing less aggressive chemotherapy.

    The discussions routinely cover the harm of unnecessary treatment, but what about the quality of life benefits of earlier diagnosis and treatment? Can Dr Gorski comment on these?

    N.B. I’m approaching 50, friends are getting breast cancer.

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