Daniel B. Kopans, MD

I very much appreciate Dr. Caruncho’s thoughtful and detailed response to my article in 

. It is ironic I wrote the article before the U.S. Preventive Services Task Force published its new guidelines.  Their scientifically unsupportable analysis merely reinforced the concerns I expressed in 

. The fact those of us who have an understanding of the data, and how the data have been manipulated, have been prevented from presenting the opposing information in such journals as the 

Journal of the American Medical Association

 over the past two months is testimony to the concerns that I have raised.

 There has been major management of the interpretation of the scientific evidence occurring even today (1). The writer’s review of what I have written in 

 is the first effort anyone has made to address the concerns I have raised over the years and I appreciate the effort. I am indeed angry because this “debate” has gone on for more than 30 years. I have seen data, repeatedly, misused and lives have been, unnecessarily, jeopardized as a result. It is easy to say, “Let’s agree to disagree,” but this is not a debate over the glass being half full or half empty. It is about the fundamental facts. The critique is thoughtful, but not scientifically accurate. Unfortunately, I am being limited in my response so that I cannot address all of the issues raised, but I will try to address the most important. 

 Countries that told their populations they were not screening before the age of 50 because the data did not show a benefit were, in fact, “lying.” The randomized, controlled trials (RCT) of screening, when analyzed as they were designed have always shown a statistically significant benefit for screening beginning at the age of 40 (2). The reason the age of 40 is a threshold today is that those of us who argue from the science recognize that the RCT only included women beginning at the age of 40 (Gothenberg did recruit women age 39). Consequently, since RCTs are the only scientifically acceptable way to prove a benefit, the age of 40 is, scientifically, supportable as a threshold.   The age of 50 was first chosen, as the writer correctly understands, as a surrogate for menopause. The statistician in the first RCT, the Health Insurance Plan of New York trial (HIP), decided to retrospectively evaluate his data, convinced that hormones must have some effect on the benefits of screening. They had not collected menopausal status so he chose 50 as a surrogate and divided the data and looked at women ages 40-49 and women ages 50-64.

 The trial lacked the statistical power to permit this, but this has been repeatedly ignored, and the trials that followed also had their data broken, and analyzed retrospectively. It was only through unplanned, retrospective subgroup analyses of trials that were not designed to permit age stratification, due to lack of statistical power, that the age of 50 was imbued with unsupportable importance (3).

 In 1993, the National Cancer Institute (NCI) misled the public (4) by dropping support for screening women ages 40-49 because they had set a requirement the RCT had to show a statistically significant mortality reduction within five years of the start of the trials (5). The data clearly showed a decrease in deaths for women in their 40s, but since the trials were not powered to permit this retrospective stratification, it was mathematically impossible for this to be “significant.”

 Dr. Caruncho clearly does not understand if unplanned, retrospective, subgroup analysis of data from trials that lacked the statistical power to permit such stratification is legitimate for making medical recommendations, then we should be able to examine smaller and smaller subgroups, and would ultimately only need two women in a trial. Clearly this is scientific nonsense, but our NCI and other governments have lied to their populations by using these scientifically unsupportable subgroup analyses to make medical recommendations. There are two alternatives. Either they were lying to their populations, or they simply did not understand appropriate trial data analysis and should not be advising anyone. 

 Opponents of screening also set a requirement that in the trials women ages 40-49 had to show a significant decrease in breast cancer deaths within five years of the start of the trial (5). Not only was this a mathematical impossibility (3), but, given length bias sampling (periodic screening detects moderate and slow growing cancers), why was an immediate benefit expected?  When the death rate from screening women ages 40-49 in the trials became statistically significant, with longer follow-up (6), it was completely ignored (7) or discounted, as suggested by Dr. Caruncho, because it was “delayed.” A “delayed benefit” is actually what would be expected in an RCT, yet it has been discounted.    De Koning even suggested that the benefit for younger women was due to women in the trials reaching age 50 and screening suddenly beginning to save lives (8). When he was presented with more complete data he recanted in public (and in an e-mail to me) (9) and agreed most of the benefit was from screening before the age of 50, but he has neglected to publish a written retraction, I would surmise, because his original paper was so often quoted (it was the basis for the Age Trial) that a written retraction would be too embarrassing. 

 Dr. Caruncho states that age 50 is appropriate because breast cancers “behave differently before and after menopause.” The writer may understand the therapy data, but clearly does not understand the screening data. 

 Opponents of screening women in their 40s have repeatedly taken data that change gradually with increasing age, and grouped them dichotomously (40-49 compared to 50 and over) as if they were two uniform groups. This makes the changes that take place gradually falsely appear to change abruptly at the age of 50. Data grouping can be used to make any age appear as a “jumping” point. 

 There are no ungrouped data that show any of the parameters of screening (callback rates, biopsy recommended rates, cancer detection rates, etc.) change abruptly at the age of 50 or menopause (10). It is only by grouping data that the age of 50 has been imbued with unsupportable importance (10). 

 One often quoted paper grouped women ages 30-49 and compared them to all women ages 50 and older (11). No one was arguing in support of screening women in their 30s, but adding them to women in their 40s brought down the cancer detection rate for the younger group to make it appear there was a sudden jump at the age of 50 when their ungrouped data show, as would be expected, a steady change with age with no jump at any age. What would Dr. Caruncho call this–legitimate scientific analysis, or manipulation of data?

 It is fine for Dr. Caruncho to say that the age of 50 is “arbitrary,” but I would challenge the writer to identify, in the arguments against screening women ages 40-49, anywhere it is clearly stated this is an “arbitrary” threshold. If women had been told they were being denied access to screening, arbitrarily, until age 50, despite the fact that screening could decrease deaths while they were in their 40s, I suspect there would have been a “discussion.” Instead they were told the trials showed no benefit so the discussion was eliminated. The dichotomy between premenopausal screening and postmenopausal screening is in the mind of the reviewer, and not in the screening data.  The writer points to Berry’s article, which summarizes seven computer models that were asked to determine what percentage of the 30% decrease in breast cancer deaths in the United States that has occurred since 1990 was due to screening, and what was due to therapy. One has to ask, why would Berry choose computer models when there are direct data from the Netherlands (12) and Sweden (13, 14, 15) that show the vast majority of the benefit is due to screening, with only a small component due to improved therapies, and screening the general public decreases breast cancer deaths by more than 30% (including women in their 40s)? 

 Models are only as good as the assumptions programmed into the computer. Sophisticated financial computers said the economy was sound in 2008. Why would the writer have confidence in the models without knowing what assumptions were used? Clearly you can make one intervention appear superior to another by using assumptions that favor your bias. Direct population data reduce the chance that the results can be biased. Furthermore, I suspect that most medical oncologists would agree that therapy is only successful at saving lives, with rare exceptions, when breast cancers are found early.  I didn’t think I had to point this out, but the only way to detect cancer early, with proven mortality reduction, is with mammography screening. 

 With regard to the two trials that “specifically address mammography screening in women under their 50s,” the writer states the CNBSS1 has “withstood the criticisms.”  One has to ask those that have continued to support this trial–why? The CNBSS1 was a completely corrupted trial. In addition to being underpowered from the start (16), and using mammography that their own reference physicist admits was below the quality of even that being used in the communities, (17), the indisputable fact is the CNBSS1 violated the most fundamental requirements of a randomized trial–blinded randomization. 

 They examined everyone before allocation so they knew who had palpable masses and palpable axillary lymph nodes (advanced cancers) BEFORE allocation. Then they assigned women ON OPEN LISTS so that a line could be skipped to insure a woman with advanced cancer would be placed in the mammography group. That this occurred and biased the trial was clearly shown by Tarone (18). Enough is enough. The CNBSS1 violated the fundamental rules of an RCT yet, incredibly, it continues to be defended and used to pull down the benefit from screening for women ages 40-49. What is the point of having any requirements for scientific analysis if those rules can be violated with impunity?  I am surprised that Dr. Caruncho is clearly unaware of what took place in the Age Trial (19). The principal investigator of the Age Trial freely admits her trial was compromised. The “Age Trial” used single view mammography, which the investigators knew misses 20-25% of cancers (20). Furthermore, the investigators admitted they did not biopsy clustered calcifications, which are well known to be indicators of early breast cancer (21).

 I have not seen any publication that speaks to what percentage of women in the supposedly unscreened control group had mammograms outside the trial (contamination).  I am surprised this did not occur to Dr. Caruncho as an explanation for their “20% decrease in mortality.” If your trial misses a large number of early cancers in the screened group because you failed to biopsy them, and control women had their lives saved by screening outside the trail, why would you be surprised that the trial showed little benefit? 

 Radiation risk to the breast is inversely proportional to age at exposure. There is no direct evidence of any risk from mammography for women age 40 and older. Even the extrapolated risk for women age 40 and older is easily outweighed by even a 5% benefit (22). Certainly not proof, but hundreds of millions of mammograms have been performed in the U.S. since the 1980s. If mammography were causing cancer the incidence would be increasing. In fact, the incidence is decreasing. 

 Years ago Rosenquist and Lindfors showed that annual screening beginning at the age of 40 was cost effective (23). With regard to “absolute benefit,” I believe that breast cancer accounts for, approximately, 3% of all deaths each year. Reducing this by 30% will have little impact on the total number of deaths in the U.S. However, a 30% reduction amounts to 15,000-20,000 lives that are being saved, each year, primarily due to mammography screening. The writer feels this is trivial. I do not. 

 I appreciate the writer’s other critiques, but 

 will not permit me additional space. The writer only reinforces my premise. There is no lack of individuals who are willing to speak out on the screening issues, but there is a real lack of individuals who actually know and understand the data. 

 The scientific evidence clearly shows that mammography screening, significantly, reduces deaths among women beginning at the age of 40. 



 1. Kopans DB. Bias in the Medical Journals: A Commentary. Am. J. Roentgenol 2005; 185: 176 - 182.

 2. Shapiro S.  Screening: Assessment of Current Studies.  Cancer 1994;74:231-238.

 3. Kopans DB. Bias in the Medical Journals: A Commentary. Am. J. Roentgenol 2005; 185: 176 - 182.

 4. House Committee on Government Operations.  Misused Science:  The National Cancer Institutes Elimination of Mammography Guidelines for Women in Their Forties.  Union Calendar No. 480.  House Report 103-863.  October 20, 1994.

  5. Fletcher SW, Black W, Harris R, Rimer BK, Shapiro S.  Report of the International Workshop on Screening for Breast Cancer.  J Natl Cancer Inst 1993;85:1644-1656.

 6. Hendrick RE. Smith RA, Rutledge JH, Smart CR.  Benefit of Screening Mammography in Women Ages 40-49:  A New Meta-analysis of Randomized Controlled Trials.  Monogr Natl Cancer Inst 1997;22:87-92.

 7. Kolata G.  Stand on Mammograms Greeted by Outrage.  New York Times.  Tuesday January 28, 1997 

 8. de Koning HJ, Boer R, Warmerdam PG, Beemsterboer PMM, van der Maas PJ.  Quantitative Interpretation of Age-Specific Mortality Reductions From the Swedish Breast Cancer-Screening Trials.  J Natl Cancer Inst 1995;87:1217-1223.

 9. Kopans DB. Informed decision making: age of 50 is arbitrary and has no demonstrated influence on breast cancer screening in women. Am J Roentgenology 2005;185:177-82 

 10. U.S. Preventive Services Task Force.  Screening for Breast Cancer: U.S. Preventive Services Task Force Recommendation Statement Annals Int Med 2009;151:716-726 

 11. Kerlikowske K, Grady D, Barclay J, Sickles EA, Eaton A, Ernster V.  Positive Predictive Value of Screening Mammography by Age and Family History of Breast Cancer.  JAMA 1993;270:2444-2450.

 12. Otto SJ , Fracheboud J, Looman CWN,  Broeders MJM, Boer R, Hendriks JNHCL, Verbeek ALM,  de Koning HJ, and the National Evaluation Team for Breast Cancer Screening*  Initiation of population-based mammography screening in Dutch municipalities and effect on breast-cancer mortality: a systematic review Lancet 2003;361:411-417. 

13 Tabar L, Vitak B, Tony HH, Yen MF, Duffy SW, Smith RA.  Beyond randomized controlled trials: organized mammographic screening substantially reduces breast carcinoma mortality.  Cancer 2001;91:1724-31 

 14. Duffy SW, Tabar L, Chen H, Holmqvist M, Yen M, Abdsalah S, Epstein B, Frodis Ewa, Ljungberg E, Hedborg-Melander C, Sundbom A, Tholin M, Wiege M, Akerlund A, Wu H, Tung T, Chiu Y, Chiu Chen, Huang C, Smith RA, Rosen M, Stenbeck M, Holmberg L.  The Impact of Organized Mammography Service Screening on Breast Carcinoma Mortality in Seven Swedish Counties.  Cancer 2002;95:458-469

  15. Swedish Organised Service Screening Evaluation Group. Reduction in breast cancer mortality from organized service screening with mammography: 1. Further confirmation with extended data. Cancer Epidemiol Biomarkers Prev. 2006;15:45-51. 

 16. Miller AB, Howe GR, Wall C.  The National Study of Breast Cancer Screening.  Clinical and Investigative Medicine 1981;4:227-258. 

  17. Yaffe MJ.  Correction: Canada Study.  Letter to the Editor JNCI 1993;85:94  

18. Tarone RE.  The Excess of Patients with Advanced Breast Cancers in Young Women Screened with Mammography in the Canadian National Breast Screening Study.  Cancer 1995;75:997-1003. 

 19. Moss SM, Cuckle H, Evans A, Johns L, Waller M, Bobrow L Effect of mammographic screening from age 40 years on breast cancer mortality at 10 years' follow-up: a randomised controlled trial. Lancet. 2006;368:2053-60. 

  20.Wald NJ, Murphy P, Major P, Parkes C, Townsend J, Frost C. UKCCCR multicentre randomized controlled trial of one and two view mammography in breast cancer screening. BMJ 1995; 311:1189-1193 

 21. Evans AJ, Kutt E, Record C, Waller M, Moss S. Radiological findings of screen-detected cancers in a multi-centre randomized, controlled trial of mammographic screening in women from age 40 to 48 years. Clin Radiol. 2006;61:784-8.

 22. Mettler FA, Upton AC, Kelsey CA, Rosenberg RD, Linver MN.  Benefits versus Risks from Mammography:  A Critical Assessment.  Cancer 1996;77:903-909.

 23. Rosenquist CJ, Lindfors KK.  Screening Mammography in Women Aged 40-49 Years: Analysis of Cost-Effectiveness.  Radiology 1994;191:647-650.

Articles

I very much appreciate Dr. Caruncho’s thoughtful and detailed response to my article in Diagnostic Imaging. It is ironic I wrote the article before the U.S. Preventive Services Task Force published its new guidelines.  Their scientifically unsupportable analysis merely reinforced the concerns I expressed in Diagnostic Imaging.

Kopans offers point by point rebuttal to Caruncho

Mammography screening is one of the major medical successes of the past several decades, yet this fact seems unable to break free of the doubts promulgated by such articles as Dr. Leonard Berlin's, published in an issue of 

 earlier this year (“Disagreement continues to dog screening mammography,” April, page 31). I suspect that few people are aware of the fact that the death rate from breast cancer, the second leading cause of cancer deaths among women, has decreased by almost 30% since 1990. This is a remarkable achievement, especially in light of the fact that the death rate had remained unchanged for the preceding 50 years.

The statistically significant mortality reduction in the randomized, controlled Two County trial of mammography screening in Sweden

 led to the onset of widespread screening in the U.S. This initiation of nationwide screening led to a sudden increase in annual breast cancer incidence in 1984-85. The sudden decrease in cancer deaths that began in 1990 is clearly related to the preceding, equally sudden, increase in earlier cancer detection.

 Although oncologists, citing computer modeling, would like to claim that improvements in therapy are responsible for the decline in deaths,

 using direct population data, have shown that at least two thirds of the decrease in deaths is due to mammography screening (this result is also shown in Berry's computer model, but it has been ignored by opponents of screening).

I am unaware of any test that has been as completely studied or challenged and has so successfully met the challenges as mammography screening. Three steps are required to prove that a screening test for breast cancer is efficacious. The first is that it must be able to detect breast cancers at a smaller size and earlier stage than is possible without the test. The Breast Cancer Detection Demonstration Project (BCDDP) in the 1970s proved this.

 The second is that randomized, controlled trials must show the test brings about a statistically significant reduction in mortality. Such a decrease in deaths has been clearly demonstrated by the seven randomized, controlled trials of mammography screening.

 The third is that when the screening test is introduced into the general population, the death rate declines. Mammography has fulfilled all three requirements.

It has been argued that women have been misled into believing that screening will save all of them from breast cancer, and even that women are being coerced into being screened. This is a gross exaggeration and a distraction. There is no question that some organizations have engaged in some hyperbole, but radiologists involved in these debates have always made it clear that mammography screening is far from perfect and does not save all lives. There are no perfect tests and mammography is no exception. However, this does not mean that it does not provide very important, life-saving benefit for many women. Tens of thousands of lives have been saved since 1990.

Despite overwhelming proof of a benefit, there continue to be those who question the efficacy of mammography screening and suggest that there is real ambiguity in the benefit. In fact, any ambiguity is due to unscientific data analyses that have taken place over the past 40 years. The use of retrospective subgroup analysis of data from the randomized controlled trials that lacked the statistical power to permit stratification by age, and making medical recommendations against screening women in their 40s based on these analyses, is a major misuse of science.

 The use of data grouping to make it appear that results change suddenly at an arbitrary age when there is no evidence to support this, and the decision by some analysts to exclude data that they do not like, are violations of appropriate scientific analysis. That all have happened is not a secret. Those who continue to rely on these fallacious arguments are either ignorant of scientific analysis or are maliciously misleading women and their physicians.

As is discussed below, many of the arguments against screening are based on scientifically unsupportable analyses and misuse of data. Unfortunately, these efforts have been propped up by journals that publish articles whose peer reviewers clearly do not understand scientifically supportable data analysis. Rather than explaining how opponents of screening have misused and manipulated data, it is argued that the two sides in the debate have equally valid assessments but view the facts differently. We often hear that “individuals of good faith can look at the same data and come to opposite conclusions.” I have no doubt that there are times when this approach is supported by facts, as when a glass can be viewed as half full or half empty. However, this approach is an interpretation of the facts. It does not speak to the facts themselves. And there are actual facts in this debate.

What has been repeatedly overlooked is that truths exist. The Earth is not flat. It is our responsibility as physicians and scientists to seek the truth and not merely throw our hands up and “agree to disagree,” especially when lives are at stake. The problem lies in the fact that very few physicians, and certainly few radiologists, have taken the time to understand the data that support mammography screening. Because few understand the studies and the data they have generated, most are unable to recognize when data are being scientifically analyzed and when they are being manipulated. The controversies over mammography screening are due not to the inherent ambiguity of the data, but to the scientifically unsupportable ways that those data have been manipulated to generate doubt.

Numerous controversies over mammography screening have arisen over more than 40 years. As a result of these controversies, mammography has been disparaged rather than acknowledged as a major medical achievement. As someone who has been directly involved in the debates since the 1970s, I see the problem not as a disagreement over the meaning of the facts, but as a manipulation of the facts designed to produce the disagreement.

Few of us have sufficient interest or time to review all of the data under discussion and to determine what are the actual facts. We rely on others to distill the findings, and our own critical review is often lacking. Unfortunately, this includes peer reviewers for medical journals who support the publication of “studies” that provide misleading information due to major scientific flaws that escape the reviewers. A recent article by Jørgensen and Gøtzsche

 suggested that mammography finds cancers that would have “melted away” if the women had not been screened because the “incidence” of breast cancer did not return to baseline once screening had been established in several countries. But the authors had not taken into account the new prevalence of cancers that would contribute to new annual incidence figures as each year new women reached the age at which screening begins. The annual diagnosis of breast cancer would not be expected to return to baseline because what they termed “incidence” was actually a combination of incidence and prevalence. This is a fundamental error that completely escaped peer review.

An important example of a similar oversight by peer reviewers occurred when an oft-quoted paper by Kerlikowske et al was published in the Journal of the American Medical Association

 during the debate over whether to screen women aged 40 to 49. The authors stated that since the breast cancer detection rate was two in 1000 for women aged 30 to 49 and 10 in 1000 for women aged 50 to 74, we should concentrate on screening women aged 50 and over. What the authors failed to point out is that the ungrouped data provided in the paper show a steady increase in breast cancers detected with increasing age (as would be expected) with no abrupt change at the age of 50. It was only by grouping the data and analyzing those above 49 as if they were a uniform group and comparing them with those 49 and younger as if they were uniform group that the authors made it appear that there was a sudden change at the age of 50.

In addition, women in their 30s were not even being considered for screening, so why did the authors include them in the analysis? Could it be that by grouping women in their 30s with women aged 40 to 49, the lower incidence of breast cancer among the younger women was used to bring down the detection rate for women under the age of 50? Not only did this pass peer review, but though I alerted the lead author to the fact that her analysis was misleading prior to the publication of the paper, nothing was changed, and readers of the study were led to believe that something really changed suddenly at age 50.

 This clear artifact of data grouping passed peer review and is now a major support for the myth-which persists today-that age 50 has biological significance for the incidence of breast cancer.

I do not mean to suggest that I possess the “truth,” but there are facts, and these facts have been ignored by many opponents of screening, or distorted to support their position. I apologize for my tone, but this has gone on far too long. The controversies persist because few are willing to take the time to understand the issues and seek the truth, or to challenge much of the nonscience that gets published. With true humility I say that no one yet has refuted any of the arguments summarized in this article.

A prime example of how opponents of screening have provided misinformation and avoided addressing the facts could be seen when the American College of Physicians put forward guidelines in 2007, which recommended that women aged 40 to 49 should consider screening based on their risk of developing breast cancer.

 What these supposed experts failed to understand, and what I pointed out in a letter to the editor

 (limited to a few hundred words), was that:

• The guidelines implied that the age of 50 was a legitimate threshold. But there are no data to support using the age of 50 as anything but an arbitrary threshold.

• No data from the randomized, controlled trials support screening based on risk since none of the trials stratified the participants by risk. No data show that this will save any lives.

• Since 75% to 80% of breast cancers occur in women who are not at elevated risk, screening based on risk would miss most of them.

Rather than explaining why my concerns were incorrect, the authors' reply was, essentially, “We disagree with Dr. Kopans.” This is indicative of why the controversies continue. Supporters of screening have argued the scientific evidence and responded to all attacks on the benefits of screening with science and logic. Opponents of screening have developed pseudo-arguments that are not supported by facts and they have been allowed to persist in using arguments that ignore science. When those of us who have defended screening based on the data have challenged interpretations of the data disseminated by opponents, rather than defend their position with facts, they merely “disagree.” What many fail to understand is that it is impossible to resolve a disagreement when one side refuses to acknowledge facts and ignores the scientific evidence, saying “we disagree.” Those who advise the public should not be allowed to simply “disagree.” In science and medicine one must be able to provide scientifically derived data and facts.

Gøtzsche and Olsen were provided with two chances, once in 2000 and again in 2001 (most of us get only one chance at publication), to publish an attack on screening mammography for all women

 by deciding that they did not like the way five of the randomized, controlled trials were performed and dropping them from their analysis (this is scientifically inappropriate). These included four of the Swedish trials that showed a clear benefit. They claimed the Canadian National Breast Screening Study (CNBSS) was well done, despite the indisputable fact that the CNBSS is an example of how not to perform a randomized, controlled trial.

Discounting that the CNBSS was underpowered, and that the quality of the mammography was indefensibly poor for a trial of mammography screening,

these analysts also ignored the fact that the CNBSS violated fundamental rules for randomized, controlled trials. The randomization was unblinded and all women had a clinical breast examination before they were allocated to the screened or unscreened control groups. Women with lumps and palpable axillary lymph nodes were allowed to participate in this trial of mammography screening. The allocation was on open lists so lines could be skipped to place women with advanced cancers in the screening group. Indeed, they placed significantly more women with advanced cancers in the screening group,

 thereby rendering completely suspect the trial results. There can be no argument that these are major violations of the rules for randomized, controlled trials, yet Gøtzsche and Olsen were permitted to argue that the CNBSS was a well-executed trial, and since it showed no benefit from screening, there was no benefit.

 results but failed to acknowledge that Malmo actually showed a benefit. Their nonscientific approach would have been ignored by the scientific community, but it was published on the front page of 

 leading to doubts being raised, inappropriately, around the world and suspicion about screening that persists even though all of the authors' concerns were shown to be unsupportable.

 The CNBSS clearly violated the fundamental rules of randomized, controlled trials. How did 

 allow them to use its results to tell women there was no benefit, while ignoring the well-done studies that show a benefit? How can it be suggested that there are two equivalent sides to these debates?

Since the 1970s, opponents of mammography screening have repeatedly thrown impediments in front of mammography screening with, unjustified claims. In 1976, Bailar

raised concerns over radiation risk that actually resulted in stopping the screening of women aged 40 to 49 in the Breast Cancer Detection Demonstration Project (BCDDP). Yet his fears were subsequently shown to be based on gross overestimates of risk. In fact, radiation risk to the breast is predominantly to women in their teens and early 20s

 and even the smallest benefit far outweighs any theoretical risk among women aged 40 and over.

 If mammography was causing cancers, why, after imaging hundreds of millions of women over the past 20 years, is the incidence of breast cancer decreasing rather than increasing? Yet radiation risk continues to be used to frighten women.

In the 1970s and 1980s it was argued that screening led to too many biopsies with benign results until we demonstrated that clinical examination produced a lower yield of cancers and the ones it found were at a larger size and later stage than those found by mammography. It was even argued that screening led to biopsies that permanently scarred the breast so that when a woman subsequently develops a lump, mammography will be useless in its evaluation. The “expert” who stated this on national television was ignorant of the fact that biopsies rarely permanently scar the breast, and by waiting for a cancer to become palpable, the benefits of mammography would be missed.

These arguments have all been met and refuted. Yet undeterred, and as more and more data have accumulated, the opponents' arguments have mutated. In the debate over screening women aged 40 to 49, they originally claimed there were no data to support recommending screening for women before the age of 50. In 1993, the National Cancer Institute actually dropped support for screening women aged 40 to 49 based on fallacious arguments, even though there were always data that supported screening these women when the trials were analyzed the way they were designed to be analyzed. As the data became increasingly robust, those who opposed screening grudgingly admitted that there was a benefit, but instead of acknowledging that they had been wrong, they argued that it was too small to justify screening. Because the fallacious analyses of the past were allowed to be circulated unopposed, a mythology has developed that younger women do not benefit from screening. We should insist that anyone who disparages the benefit of screening be required to address the issues described in this article and refute the conclusions. This could greatly reduce the nonsense that continues to be foisted on the public.

As I documented in 2005, several medical journals have an unacknowledged bias in what papers they select for publication.

 Clearly, recent arguments against screening have had an effect by suggesting that both sides of the debates have equal weight when this is not true. Several medical journals have knowingly refused to provide women with accurate information.

 It is due to either the willful misrepresentation of data or the sheer ignorance of opponents of screening that there is still controversy about screening women aged 40 to 49. Many European countries as well as Canada do not support, or at any rate do not encourage, screening before the age of 50 and have lied to their populations by suggesting that the data did not show a benefit. I use harsh language because there are no data to support age 50 as any kind of threshold, yet women continue to be told there are.

There are legitimate issues that pertain to screening: cost, false alarms, and possibly overtreatment, but these are clouded by the numerous fallacious arguments that have become legitimized by their repetition. The continuing disagreements over screening come from the fact that radiologists and scientifically driven epidemiologists have argued the science and the facts, while opponents of screening have repeatedly violated the basic rules of scientific analysis to plant doubts that have persisted for more than 40 years. Unfortunately, most physicians have insufficient knowledge to know when they are being misled. Enough is enough. Instead of reinforcing the misuse of science, Dr. Berlin and others should be urging us all to learn and understand the data and to argue in support of science and scientifically supportable data analysis.

Mammography screening is one of the major medical successes of the past several decades, yet this fact seems unable to break free of the doubts promulgated by such articles as Dr. Leonard Berlin's.

Daniel B. Kopans, MD

Articles

Kopans offers point by point rebuttal to Caruncho

Why the critics of screeningmammography are wrong