Although many variations of the Hippocratic Oath hover around graduating medical students today, none of these versions specifically states that the individual patient is to be held in higher regard than public health policy. There’s a reason for this — public health policy didn’t exist 2,400 years ago in ancient Greece, at least not in the way we think of it today. Regardless, an oath of some sort (half of U.S. schools still use a version from Hippocrates) is administered in all of the existing medical schools in the United States, with the implication being that proper care of the individual patient is held above all else.

As straightforward as reverence for the individual patient might seem, there is a concerted effort to plunge a final dagger into the heart of the Hippocratic Oath. Why? The short answer: money. Technology has advanced so rapidly and become so costly that we can no longer think about what is “best” for our individual patients. Society comes first. This, of course, is the basic tenet of socialism, an economic platform with a philosophic foundation, be it right or wrong or somewhere in between.

Gregg Bloche, MD, JD, is a Professor of Law at Georgetown who previously served as a health care advisor to President Obama. His best-selling book raised collective eyebrows in the medical community, though not necessarily due to disagreement. His complete book title is: The Hippocratic Myth: Why Doctors Have to Ration Care, Practice Politics, and Compromise Their Promise to Heal. The author does not call for the death of the Hippocratic Oath; instead, he makes the point that the Oath is already dead, so now, let’s admit it. In a word, limited resources have already prompted a radical change in medicine, and many physicians are practicing for the good of the whole, rather than for individual patients, whether they admit it or not, whether they know it or not.

As it applies to this blog, I was surprised when reading the book to find that Dr. Bloche used screening for breast cancer with MRI as one example, this being a special area of interest and expertise for me. The facts in the book are presented correctly, acknowledging the better sensitivity of MRI in the detection of breast cancer, but pointing out the difficulty in justifying cost, not to mention the arbitrary cut-off for who qualifies and who doesn’t. I can find no fault with breast cancer screening as portrayed by Dr. Bloche in what has become a health care manifesto of sorts.

But here’s where paths diverge. Rather than throwing up my hands and bemoaning the fact “Oh, we can’t afford this or that,” I look for ways to make the superior MRI affordable for society, that is, “cost-effective” in today’s parlance. It’s not that hard if you think about it.

The first problem is the nearly universal belief that the only way to approach aggressive screening with MRI is through risk stratification, offering MRI only to women at the highest levels of risk. All international trials followed this reasoning. Yet, if one reviews cancer yields in the highest of all risks – women positive for mutations in the BRCA genes – only 3 women out of 100 will be found to have cancer on a single screening MRI, missed by mammography. Forgetting costs for a moment, this is actually considered a “high” yield, given that mammography identifies cancer in only 5 women out of 1000 (0.5%) in the general population. Even though 3% with MRI is six-fold the yield in general populations screening, it is not good enough to ensure cost-effectiveness. What now? Curse the insurance companies? The government? ObamaCare? Write books about the death of the Hippocratic Oath?

There are alternatives. First, lower the cost of breast MRI. This transition is in progress now, with the implementation of “fast” MRI for screening. With shorter study times (10 minutes instead of 30 minutes), the cost can be lowered significantly. Rather than several thousand dollars, some are offering the service at less than $500. Now, a Catch-22. Even though insurance covers high-risk screening with MRI, the coding system used universally in billing does not have a different code for screening MRI vs. diagnostic MRI. Therefore, the system shoots itself in the foot as radiologists are ready to lower costs, but can only bill at the higher rate due to the single code. Bottom line: those wanting to take advantage of “fast MRI” for screening must pay cash, and it doesn’t count toward the deductible.

Next, risk-based guidelines need an overhaul. The question should not be, “What is a woman’s breast cancer risk over the course of her lifetime?” Rather, we should be asking, “What is the risk that a woman’s mammogram is harboring an invisible cancer, on the very day of the normal screen?” This may or may not relate to long-term risk. It most certainly relates to the level of breast density on X-ray, a factor not even included in current MRI guidelines! To this end, my research collaborators are focused on computer analysis of subtle asymmetries on “normal” mammograms that currently escape expert radiologists as well as the so-called CAD, “computer-aided detection,” in common use today.

A different approach to the same problem of “current risk” vs. “lifetime risk” would be the development of a blood test to detect mammographically occult breast cancer. I have spent 20 years assisting basic scientists in the ongoing development of a screening blood test in which biomarkers would indicate the presence of cancer independent of mammographic findings. If either the “ultraCAD” approach above or the blood test prove successful, cancer yields on MRI could emerge as 10% or greater (with “missed cancers” very rare), vastly superior to anything remotely possible through risk-stratification, and easily cost-effective.

It speaks to the spirit of individualism that there’s a way to make this work. We already have the remarkable technology of MRI that can decrease the mortality of breast cancer well beyond what mammography can do by itself. So, rather than issuing guidelines that restrict care, it’s up to us to figure out how to make MRI (and other imaging approaches) cost-effective for potential “second tier” use in all women. After all, the majority of newly diagnosed breast cancer patients have no identifiable risks, a fatal flaw for those who trust entirely in risk stratification while proudly espousing “personalized medicine.”

One last point – while 100% of medical schools in the U.S. administer a professional oath of dedication to the individual patient, Hippocratic or not, as noted in the opening paragraph, it is interesting that only 50% of British medical students do the same.

The individual patient is teetering in a precarious balance weighed against societal resources, and there can be no doubt that some tottering is well underway.

 

Without criminal intent, several organizations have decided that screening women below age 50 does more harm than good. Most importantly, the U.S. Preventive Services Task Force led this crusade with their 2009 recommendations that flip-flopped from their 2002 recommendations. “New data” was the alleged reason, but if you read my book, Mammography and Early Breast Cancer Detection, you will learn what really happened.

 

The so-called “new data” on the beneficial side of screening was the results from a single trial that, while supporting mammography for young women, did not alter the 2002 calculations one fraction. In 2002, the Task Force calculated a 15% relative reduction in mortality through screening women in their 40s. After the new data was added, then the 2009 Task Force calculated an identical 15% mortality reduction. No difference in benefit, so why the dramatic change in policy? Answer: the harms of screening.

 

The “harms” are things like “false-positives,” which are mostly the routine call-backs that come with screening. We call back roughly 10% of those screened, then after diagnostic views, only 5% are left with either short-interval follow-up or a biopsy that proves to be benign. However, the full 10% are “harmed,” according to the Task Force. Others weighed in with publications demonstrating permanent psychological damage from a benign biopsy (Why didn’t they measure the permanent psychological harm from a delayed diagnosis of breast cancer?) By inflating the harms, then magically balancing how many call-backs equal a saved life, the 2009 Task Force issued their reversal in policy – no routine screening under age 50.

 

The position of many of us who practice breast cancer screening is that the “15% relative mortality reduction” for women in their 40s is understated, perhaps greatly understated. Why? Too many reasons to list here (again, refer to my book), but let me offer the two most important. The first is that these calculations are based on obsolete technology used in the 1970s and 1980s primarily, with screening studies ending by the 1990s. With the later introduction of digital mammography, and more importantly, 3-D tomosynthesis mammography, our detection rates are much improved. One of the reasons it was hard to demonstrate breast cancer mortality reduction in younger women was that too many breast cancers were missed on mammography. But if we were missing half of detectable cancers in this group in the early days of screening (and we were!), yet still could demonstrate a mortality reduction, think what we could accomplish by finding the other half. Or even half of the other half!

 

The second reason is the “Intent to Treat” rule, or in this case, the “Intent to Screen” rule that haunts all prospective, randomized trials for screening, the gold standard in research. Outcomes are based on the group to which people are assigned in these “high quality” studies, not to what patient volunteers actually did. In the case of screening mammography trials, this is a huge issue. Many women assigned to mammography were not compliant, and many assigned to no mammography opted to have mammograms anyway. Toss them out of the study? No. That would be scientific malfeasance. No, instead, they are counted to the group to which they were originally assigned. That’s right. Women who did not get mammograms stay in the mammography group, and those who had mammograms were counted in the no-mammography group. One has to read the small print in these studies to learn the outcomes for those patients who were compliant, and guess what – the mortality reduction is always improved beyond the official study outcomes when measuring the benefit in the compliant patients only. But these are unofficial results. Meanwhile, the official “15% mortality reduction” is a deceptive tool used to mislead the masses as to the minimal benefit, and yet from the standpoint of scientific purity, it’s right on the mark.

 

Now, I’m finally to my point. I have always carried a burden of concern for women under age 40 diagnosed with breast cancer. To me, it has been callous disregard for a large number of women that our guidelines for screening begin at 40, when 5% of eventual victims of breast cancer are under age 40. My favorite word here (for decades now) has been disenfranchised. These young women are disenfranchised by a screening establishment that left them high and dry.

 

In 2007, this was partially corrected by the introduction of high-risk guidelines for screening breast MRI (added to mammography) where there is now a starting age of 30, and for some, age 25. Finally! But one problem – this only addresses the young women with risk factors, that is, very high risk. Unfortunately, this is only about one-fifth of the eventual patients who will be diagnosed with breast cancer prior to the age of 40 (or, 1% of the 5%).

 

I once made my “disenfranchised” statement at a national meeting where an ad hoc committee had been formed to discuss screening guidelines. It went over like a lead balloon. A participant turned to me and said, “These women are not disenfranchised, they have clinical exam and self-exam.” Really?! That may be a good way to diagnose Stage II and Stage III breast cancer, but it’s not the way to save lives. Even more remarkable here is the fact that there has never been a single study that remotely indicates that self-exam or clinical exam saves lives.

 

So, how big is this problem that has been shoved under the rug for years, based on the misconception that we’re only talking about a tiny minority? 5% of eventual victims sounds rather small, doesn’t it? Well, in 2015, the American Cancer Society estimated that 231,840 new cases of INVASIVE breast cancer (I’m not even going to count DCIS) were diagnosed in the U.S. That means that 11,592 of these women were under the age of 40. How does that compare to other cancer numbers?

 

Let’s take cervical cancer where one hears about Pap smears and vaccines and so forth all the time, as an entire industry surrounds the 11,955 diagnosed in 2013. Think of it. We offer NOTHING to the 11,592 women in their 20s and 30s who are bound for breast cancer (unless at very high risk), while an entire industry is focused on the same number of women who are headed toward cervical cancer, all ages included.

 

(As an aside, this is the reason that I have pursued blood testing and alternative imaging options for younger women in my research.)

 

But now we face a problem that absolutely dwarfs the 11,592 disenfranchised young women headed toward breast cancer. Now, we have the Task Force leading the way – without criminal intent, mind you – to disenfranchise an additional 20% of eventual breast cancer victims from the benefits of screening. Instead of ignoring a mere 12,000, we’re now going to let nature take its course into worse stages of breast cancer with 57,960 women every year. And I hate to tell you what’s next – “no screening beyond 70 or 75,” whereupon 116,000 women to be diagnosed with breast cancer every year will be relying on the unreliable self-exam.

 

How does this 57,960 eventual breast cancer patients under the age of 50 stack up to other cancers? According to American Cancer Society stats for estimated cases in 2016, here’s the list of some cancer types all ages included, most of which have no proven screening options: Uterine cancer (60,000), kidney cancer (62,000), all types of leukemia (60,140), pancreatic cancer (53,070), thyroid (64,300). The point is that we are going to deny a staggering number of eventual breast cancer victims (57,960) the benefit of early detection with screening, based on flawed and archaic data, all in the name of “evidence-based medicine” and scientific purity that is, in fact, covert cost containment.

 

And notice one other tidbit: I’ve limited my discussion here to the number of women diagnosed with invasive breast cancer, to avoid the controversial aspects of ductal carcinoma in situ (DCIS). But if we include DCIS, as can be justified by its greater significance in younger women, then we’re talking about an additional 60,000 diagnoses each year (all ages), bringing our total number of breast cancers to nearly 300,000 per year. In this all-inclusive projection, the exclusion of screening women under 50 disenfranchises 75,000 eventual breast cancer victims every year. It only takes 13 years to deny early detection through screening to 1 million women headed for breast cancer. This is the recommendation of the U.S. Preventive Services Task Force, a rotating group of government-funded non-experts (this assures neutrality) who crank out recommendations for over 100 preventive health care measures.

 

To admit to a 15% mortality reduction (while the reality is probably closer to a 30% mortality reduction), with breast cancer screening under the age of 50, but then turn around and deny screening to these 57,960 headed toward invasive disease each year, well, let’s hope the Task Force appreciates the fact that there is no criminal prosecution in the establishment of guidelines.

How would you answer this: “What’s the best way to screen for breast cancer?”  Nearly everyone, including breast cancer specialists and radiologists, will routinely answer this question with “Mammography.”  But they’re wrong, at least by one definition of “best.”  The question is not as simple as it seems.  If one is using “best” to mean, “the most practical,” then YES, it’s screening mammography.  Mammography has the infrastructure and expertise in place so that we can screen all women in the U.S. who are interested in doing so — and, mammography is the only imaging modality which has revealed in prospective, randomized trials that fewer women die of breast cancer when screened.

But what if “best” means “best?”  That is, what if “best” means detecting cancers most reliably at the earliest stage?  (I think this is what most women hear when the word “best” is used, but those clinicians who are answering the question with “mammography” as the answer are using “best” to mean something else entirely.)  In fact, the best method for detecting breast cancer for the individual patient is MRI (magnetic resonance imaging).  Very close at the heels of MRI is MBI, or molecular breast imaging, a nuclear medicine study.  In fact, MBI can lay claim to having fewer false-positives and thus, preferred over MRI.  Both MRI and MBI require the injection of a contrast agent — gadolinium for MRI and a radionuclide for MBI.  Although MRI is widely accessible, with MBI playing “catch-up,” only time will tell about the safety of annual or biennial gadolinium vs. radionuclide, and this may be the deciding difference.

Then, for those women with dense breast tissue (another topic for later), ultrasound will actually find more cancers than mammography.  For those with extreme density (over 75% “white” on X-ray), the fact is that mammography comes in dead last of all available options.  For women with more modest levels of density, but still more than 50% of the area on mammography being “white,” it’s a toss-up as to whether mammography or ultrasound will find the most cancers.  And when it comes to the new 3-D mammography (a definite improvement in cancer detection), ultrasound still identifies additional cancers missed by this new technology.

Mammography is far from “best” when one is talking about early detection capability.  The bigger picture here is troubling — the so-called best recommendation for the general population is not always what is best for the individual.  Currently, MRI screening is used only in high-risk individuals, where published detection levels (sensitivity) are 90% compared to only 40% using mammography alone.  The same gap would be present in normal risk individuals as well, but screening the general population with MRI is so impractical that it has never seriously been considered…until now.  A new “fast MRI” may make screening larger numbers of women with MRI more practical.  Dr. Christiane Kuhl (Germany) has presented the first data on screening the general population with MRI, and it’s impressive — for women cleared by clinical exam and negative mammograms, and nearly all with screening ultrasound as well, Dr. Kuhl and her group identified 11 cancers per 1,000 patients at normal risk, roughly double the detection rate of mammography…after mammograms had already deemed these women as A-Okay.

The key is going to be identifying patients for ultrasound and MRI screening in a cost-effective manner.  And it is for this reason that I am involved in two major research efforts to properly select patients for additional imaging, based not on future risk, but the current probability that a cancer has been missed by mammography.  This blog will return to these research projects again and again.  And for detailed information as to how and why breast cancer screening needs to be overhauled, check out my book: Mammography and Early Breast Cancer Detection: How Screening Saves Lives.

The term “precision medicine” is so overused today that it suffers the same fate as any buzz phrase that is tossed about carelessly – loss of impact. Whether you call it “precision medicine” or “personalized medicine,” the intent is the same – to customize medical care for the individual. Effective treatments are applied only to those who benefit. Who can argue with that?

In its purest sense, it’s the ideal approach to medicine. Imagine a patient newly diagnosed with cancer whose tumor is analyzed at the molecular level, whereupon the exact combination of therapeutic agents designed for the tumor’s particular profile is utilized, and the cancer is eradicated. Great strides are being made in that direction.

Paradoxically, however, when it comes to breast cancer screening, the use of precision medicine to justify doing less benefits society at the expense of the individual. This is not the alleged intent of precision medicine; it’s the exact opposite.  Precision medicine is supposed to benefit the individual.  Let’s see how so-called precision works when it’s applied to the justification to do less screening for the early diagnosis of breast cancer. This is not hypothetical, by the way. The term “precision medicine” is often used in the defense of new breast cancer screening guidelines where only those women at increased risk are to consider mammography in their 40s.

The primary care physician, caught in the storm of controversy, is currently being pressured to say this: “Since you don’t have a family history for breast cancer, I’m going to recommend waiting until you’re age 50 to begin mammographic screening.” Or, this: “Since your mother had breast cancer, I’m going to recommend that you begin screening at age 40.” It sounds perfectly reasonable, but the logic is deeply flawed if one understands the numbers behind these recommendations.

For the decade of the 40s, the general incidence of breast cancer is only 1.5% over the course of these 10 years. That is, only 15 women out of 1,000 are going to develop breast cancer during their 40s (compared to 25/1,000 in their 50s, and 35/1,000 in their 60s). In order to improve cancer detection rates, the recommendation has been made to selectively screen only those women with risk factors.

However, the majority of women who develop breast cancer have no identifiable risk factors, so this logic is flawed from the git-go, even before we get to actual numbers.

This selective approach for breast cancer is to be sharply distinguished from lung cancer where “precision” screening using chest CT works quite well because of the tight correlation of smoking to the disease being addressed through screening. In lung cancer, 80% of patients have a smoking history. But more importantly, the level of lung cancer risk is 20-fold in smokers over the general population. Thus, smokers are advised to screen, while non-smokers are advised to do less, that is, nothing. Inevitably, there are those who believe we should adopt the same approach for all cancer types – screen only those at risk.

But breast cancer is not even in the same ballpark. Instead of 80% who have risk factors as in lung cancer, only 20-25% of newly diagnosed breast cancer patients have a positive family history. So, our target population is far weaker than what is seen in lung cancer. But it gets worse – the power of risk due to family history in breast cancer is often negligible. Rather than the 20-fold risk of smoking and lung cancer, the usual risk seen for breast cancer (with one first-degree relative with the disease) is more in the range of 2-fold, or one-tenth the power of smoking and lung cancer risk.

With the exception of patients who have multiple family members affected by breast cancer (with or without testing positive for a breast cancer predisposition gene), the usual “high risk” patient for breast cancer is not strikingly elevated above and beyond baseline risk. Again, unlike lung cancer where the baseline risk is low (in non-smokers), the baseline risk for breast cancer is high for all women.

 

Here’s how the numbers work in the decade of the 40s:

Risk of breast cancer over 10 years if there are no identifiable risk factors – 1%

Risk of breast cancer over 10 years in the general population of women – 1.5%

Risk of breast cancer over 10 years with one first-degree relative with breast cancer – 2%

 

Do we really limit screening to the group with 2% 10-year risk and ignore the women at 1%, understanding that this maneuver will exclude the majority of women with breast cancer? Certainly, the yield improves when you limit screening to higher risk patients, but “cancer yields” don’t tell you how many women were excluded to get the boost from 1% to 2%. Cancer Detection Rates (CDRs), or cancer yields, can be very misleading.

The cost savings with “precision medicine” in this instance is staggering. If we take 100,000 women in the general population at baseline risk, we will need to perform one million mammograms over the course of 10 years to identify 1,500 cancers. But if we limit screening to only those women with a positive family history, we will need to perform only 200,000 mammograms over 10 years rather than 1,000,000. And, our cancer yields go up! 2% rather than 1.5%. Great. But we will only find 400 cancers (2% of 200,000), while missing the majority of breast cancers with this “precision” approach. Had we simply screened everyone, “without” precision, we would have encountered 1,500 cancers, instead of only 400.

Actual breast cancer deaths are calculated differently, and require taking into account cancers missed by mammography, but a reasonable estimate is that there will be an additional 1,000 breast cancer deaths every year in the U.S. if we restrict screening to a starting age of 50.

In a roundtable committee on screening, I once stated that women in their 30s were already disenfranchised from early diagnosis of breast cancer (5% of eventual breast cancer patients), but to start screening at 50, we would disenfranchise a much larger group of women in their 40s (an additional 20% of eventual breast cancer patients). I was challenged by a colleague who said, “These women are not disenfranchised, they have physical exam.” Wow. Clinical exam usually detects Stage II disease (or worse) in this population, and there’s not a shred of evidence that lives are saved. Yet, the evidence is strong that mammographic screening lowers mortality in the 40s, even if the benefit is not as great as later in life (even the Task Force admits to a 15% relative reduction in mortality for women screening in their 40s).

When it comes to breast cancer screening for women in their 40s, the admonition to do less in the name of precision medicine benefits society by lowering health care costs, but does little for the individual and could cause substantial harm, the exact opposite of what “precision medicine” claims to be.

For a detailed look at the fallacy of risk-based screening as used to justify doing less, refer to my book — Mammography and Early Breast Cancer Detection, Chapter 20 — Risk-based Screening — It Feels So Right, But Wait…

 

 

In a recent article in the New England Journal of Medicine[1], H. Gilbert Welch and associates draw from the Surveillance, Epidemiology, and End Results (SEER) program, spanning the years from 1975 to 2012, to estimate the extent of overdiagnosis in mammographic screening. Using yet another variation of indirect deduction, this time focusing on tumor size, it was determined that “only 30 of the 162 additional small tumors per 100,000 women that were diagnosed were expected to progress to become large,” implying that 81.5% of women were overdiagnosed by screening. This conclusion sets a record high for the calculated extent of overdiagnosis. Given that there are no patient-specific data about mammography use and compliance in these massive SEER reviews, one has to wonder how far these indirect methodologies can take us. Is the next stop 100% overdiagnosis?

While criticisms of the indirect methodology will be levied, then defended ad nauseum, one question always looms in this debate when discussing the overdiagnosis of invasive breast cancer (as distinct from DCIS) – why don’t we see evidence of these overdiagnosed tumors clinically? Of course, the epidemiologists have beaten that argument down to their own satisfaction by reminding us that these overdiagnosed tumors are all removed, making it impossible to directly measure overdiagnosis.

Still, what is happening at the level of the individual patient? At the level of histology and tumor biology? For such an allegedly pervasive phenomenon, there must be a clinical correlate. In fact, the only true overdiagnosis that can be directly documented would be more accurately labeled as misdiagnosis, e.g., when a complex sclerosing lesion is confused with invasive carcinoma, something that can trip up even the experts[2]. But this scenario doesn’t even begin to explain the staggering numbers for overdiagnosis being generated indirectly and likewise spilling into proposed informed consents for screening.

Using the strict definition of overdiagnosis – tumors that never progress – there are only two scenarios that could be happening at the histologic level, that is, tumor regression or, alternatively, tumor quiescence where the cancer simply reaches a certain size and stops. Either way, the tumor does not become clinically evident during the life of the patient.

Of these two possible explanations, the focus recently has been more on complete tumor regression, a shifty target since the evidence has already disappeared. Dr. Welch and associates will sometimes reference themselves in claiming that evidence supports regression[3], yet these are not studies where direct observation confirms that cancers melt away. Instead, the authors simply layer more indirect evidence on top of the indirect premise, creating a circle of self-validation.

And this is where a different perspective emerges through direct patient care. While there is some evidence histologically for “burned out” DCIS, the microscopic evidence from which to theorize the same for invasive regression is scant, at best. In contrast to the claim that we can only use indirect methods to study overdiagnosis, we clinicians have the occasional opportunity to witness tumor regression in the clinic by virtue of those women who refuse biopsy of screen-detected abnormalities. Or, after biopsy, patients refuse further treatment. Curiously, some will return for follow-up, often still declining further intervention. For us, this sequence happens once or twice a year, mounting to a fair number of instances over time. The collective experience of thousands of radiologists over decades seems to be similar to our facility where we have never seen a single case of tumor regression.

The more plausible explanation would be the option of tumor quiescence – that is, indolent tumors that reach a certain size and stop growing, remaining silent throughout the life of the patient. The easily accessible repository in which to document this phenomenon – directly – would be autopsy studies, in which these cancers should be evident in numbers out of proportion to expected disease prevalence. Oddly, there is so much momentum by the overdiagnosis bandwagon that it is not uncommon to hear it stated that autopsy studies of occult breast cancer show “pretty much the same” as what one sees in prostate cancer where overdiagnosis is readily evident. But this is not the case.

In the 1990s, there was enormous enthusiasm for the detection and treatment of DCIS, as it was felt that we could nip invasion in the bud every time. To counter this trend, an epidemiologist set about to show how common DCIS could be found in autopsy studies. Indeed, the review[4] indicated modest potential for overdiagnosis in DCIS (range – 0 to 14.7% in seven autopsy studies, drawn largely from the pre-mammographic era). As one would expect, the higher rates were seen when more slides were examined, the mean number of slides per breast in the studies ranging from 9 to 275.

Seemingly forgotten today, this comprehensive autopsy review secondarily included coverage of invasive disease as well. Given that disease prevalence in the U.S. for invasive breast cancer among the living is around 1% in an unscreened population, one would expect the autopsy data to generate a number well in excess of 1% if widespread tumor quiescence were at work. In fact, the discovery of occult invasive breast cancer in these seven autopsy studies ranged from 0 to 1.8%, with a median of 1.3%, a strong indictment against the alleged phenomenon of tumor quiescence. Of special interest, the lead author of this 1997 autopsy review was H. Gilbert Welch, cutting his teeth on DCIS, who many years later would move on to invasive disease. In 2012, Bleyer and Welch would claim that, over the past 30 years, 1.3 million women in the U.S. have been overtreated for pseudocancers of the breast, and that we continue at the rate of 70,000 per year[5].

If neither tumor regression nor tumor quiescence is at work, then most likely, the magnified illusion of overdiagnosis is occurring due to old-fashioned length bias with very long natural histories for many breast cancers. By using indirect methodology, these tumors appear as “excess cancers” when adjustments are not made accordingly.

Overdiagnosis is intertwined with length bias – the former being tumors that never progress, the latter relating to tumors that slowly progress. Yet, the two cousin concepts can be indistinguishable in large-scale population studies, depending on how the data is handled. And given the choice of picking overdiagnosis as one’s operative word versus length bias, which is the more powerful iconoclastic bombshell? “Overdiagnosis” sends shivers up the public spine, whereas “Length Bias” only draws a collective yawn.

 

 

[1] Welch HG, Prorok PC, O’Malley AJ, Kramer BS. Breast-cancer tumor size, overdiagnosis,, and mammography screening effectiveness. N Engl J Med 2016; 375:1438-1447.

 

[2] Elmore JG, Longton GM, Carney PA, et al. Diagnostic concordance among pathologists interpreting breast biopsy specimens. JAMA 2015; 313:1122-1132.

 

[3] Zahl PH, Maehlen J, Welch HG. The natural history of invasive breast cancers detected by screening mammography. Arch Intern Med 2008; 168:2311-2316.

 

[4] Welch HG, Black WC. Using autopsy series to estimate the disease “reservoir” for ductal carcinoma in situ of the breast: how much more breast cancer can we find? Ann Intern Med 1997; 127:1023-1028.

 

[5] Bleyer A, Welch HG. Effect of three decades of screening mammography on breast-cancer incidence. N Engl J Med 2012; 367:1998-2005

First, it was lumpectomy margins for invasive disease, and then in late August 2016, margins for DCIS. In the former case, it was “no ink on tumor,” and in the latter, “2mm is adequate as long as radiation is planned.” After a quarter-century of breast conservation, with absolute chaos reigning the entire time as to what constitutes an adequate margin, the majority are shouting, “Amen!”

Now, go back and read my July 2016 blog “Guidelines Morphing Into Canon.” Guidelines are great, as long as they are used as guidelines. Instead, guidelines have a way of becoming “standard of care,” and from there, it’s a small leap to canon, with any departure being a grave violation of patient care, and certainly not worthy of reimbursement by the insurer who only has the patient’s best interest at heart.

Lumpectomy margins are probably the most random, irreproducible, inaccurate measure we have in breast cancer management today. I sometimes joke that “pathologic margins are only a surrogate for, well, true margins.” But somehow, if you collect enough experts together in the same room, representing three major cancer organizations (SSO, ASTRO and ASCO), then wave a statistical wand over a plethora of clinical studies, you can turn lead into gold!

Having spent a year in the pathology lab, and being intimately familiar with tissue processing, I have a different view. From the time the lumpectomy specimen is being removed from the patient, aberrations begin to occur that give phony confidence when the margin is assessed. From the specimen radiograph that can knock off the outer rim of fat, to the handling of the gross specimen, to the ink that slides down into the crevices, to the ink that can be dragged into the specimen with the scalpel, and on and on, I can tell you why false-positive margins emerge. And then, on the false-negative side, there are even more reasons. The point is that margins are highly unscientific. So, how do p-values correct this? They don’t, but they give the illusion of certainty and the delusion of evidence-based medicine.

There are so many variables that should enter into the decision for re-excision that I can’t begin to list them here. But the first problem with this new standard is that “DCIS” is addressed as though it were a single entity. But a 5.0cm DCIS where the extent is not seen well on imaging, and with margins of only 2mm at multiple sites around the specimen…well, it’s not even in the same category as the 0.5cm DCIS that fits on one slide were you see the entire lesion.

As DCIS grows, the margins become less and less reliable, and imaging of all types can be unreliable as a roadmap as well. How many prospective, randomized clinical trials have been performed to test the value of radiation in women with Grade 1 or 2 DCIS that measures under 1.0cm? Answer: None. Yet, these women are told to undergo radiation because prospective RCTs have shown benefit to radiation, even in “good DCIS,” failing to mention that so-called “good DCIS” in those trials, when Grade 1 or 2, can be up to 2.5cm in the study protocol, with 3mm margins. That’s a different animal than the 0.5cm DCIS that was also 0.5cm on imaging that I described above, especially if you can accomplish 1.0cm margins. In this latter situation, recurrence rates with wide excision alone are close to zero, making it very difficult for radiation to add anything other than trouble.

Take note, by the way, that if one thinks this through (called rational thought, often a passé approach in today’s climate), and you get only 2mm margins on your first excision of a 0.5cm Grade 1 DCIS, the Triumvirate would spare you the re-excision (and this is where they are being praised), but insist upon radiation. In contrast, you could perform re-excision and spare the patient radiation therapy. Which can cause more trouble – a re-excision or unnecessary radiation? I hope the answer here is self-evident.

The congratulatory comments have been pouring in for the New Triumvirate of Margins – SSO, ASTRO and ASCO – with other societies chiming in their support. The take-away message is that this 2mm directive is a wonderful advance in that it will cut down on the need for re-excisions. In fact, the leader of this entire “margin guideline” movement is a breast surgeon who, only a few years before this crusade, published one of the highest re-excision rates ever reported – 60%. The reason for this reinvention of one’s self is unknown, but it’s remarkable that one can go from assuring the world that a 60% re-excision rate is okay, to the extraordinary steps taken these past few years to minimize re-excisions.

Regardless, this movement to cut down on re-excisions is no doubt admirable. We are trying to minimize overtreatment these days. Critics point out that DCIS should not be called cancer at all, but there’s a more elemental question than that – Many of the small, low grade DCIS lesions I see in consultation are not DCIS but ADH (atypical ductal hyperplasia), best termed a “borderline lesion.”

Many clinicians would be shocked to understand the subjectivity that comes with DCIS, esp. small, low grade lesions. The articles have been published (most recently by Elmore et al, JAMA 2015), but the implications are so overpowering that surgeons and radiation oncologists just tuck the information away in their individual safe places. But the fact remains, we have known since the days of the BCDDP study in the 1970s that there are lesions for which there is no agreement on the diagnosis. My solution to this problem is staggeringly simple – admit these lesions are “borderline” and treat them all with wide excision, NO RADIATION. This alone would spare more overtreatment than this entire Margin Triumvirate trend, which has been focused on a lesser endpoint. My solution is not original. A small minority of pathologists have been trying to draw attention to the problem for over 50 years, but clinicians will have none of it. They want black-and-white from a medical discipline (pathology) that happens to have shades of gray as part of its core.

So, here’s how I rank the most urgent problems today with regard to DCIS:

1. Unnecessary radiation therapy for a non-life-threatening condition and for which there is no survival difference after treatment (the current Margin Triumvirate was not able to reach a conclusion or recommendation on this most important issue).
2. The correct diagnosis, which ought to be “borderline lesion” in some cases, the working definition being whenever two experts disagree (this phenomenon is so well known in the hidden world of pathology that practicing pathologists will even tell you, correctly, that “Dr. X would call this lesion atypical ductal hyperplasia, while Dr. Y would call this DCIS. So which diagnosis do you want?”
3. How do we handle the “STOP Pre-op MRI” movement when, for the DCIS patient, 2% (our publication) will have a life-threatening invasive cancer on the opposite side of their known DCIS. In other words, without MRI, one in every 50 patients undergoing some minimal treatment of their DCIS is going to have an untreated invasive cancer on the opposite side. Imagine anywhere else in the body where “wrong side surgery” is performed as a matter of routine once every 50 times! Yet, pre-op breast MRI is maligned from every angle possible, and especially so by the leadership of the Margin Triumvirate. Remarkably, because pre-op MRI in DCIS does not help much with the index lesion, it is maligned even more than when used for invasive disease. Yet, for our tiny 2% (nothingness to a statistician), it’s a matter of life and death, bringing up the possibility that MRI is even MORE important for DCIS than invasive disease. After all, we don’t alter survival with pre-op MRI in invasive cancer, but what about our 2% in of women with DCIS? We’re talking about 1,200 women each year diagnosed in the U.S. with DCIS who actually have mammographically invisible invasion on the opposite side.
4. How do we accept the notion that nothing is important beyond 2mm when a vast body of data exists that show a direct relationship between margin size and local recurrence rates? Do we ignore the entire body of work by Silverstein and Lagios (USC/Van Nuys Prognostic Index), replicated by others? Do we reduce the seemingly infinite clinical presentations of DCIS and call it a single entity and offer simplistic solutions in the name of “generalizability.” DCIS is a complex array of entities, and there are many breast surgeons who put an extraordinary amount of thought into re-excising as needed, not when guidelines dictate a one-size-fits-all approach.

 

Re-excisions are not the most pressing problem with regard to lumpectomy, but of all the outstanding issues, why did this group try to tackle the least scientific? Why did they focus on turning lead into gold?

I have said it many times before – when it comes to prospective, randomized trials that involve surgery or radiology, there is no such thing as pure science, and that means evidence-based medicine cannot thrive here like elsewhere. Why? Inadequate blinding and huge differences in quality.   Excellence is put on the back burner, and the focus is on “generalizability” – or, stated alternatively, the acceptance of substandard care into the trials.

In contrast to this poorly controlled situation, a miracle drug can be tested with triple-blinding (even the study sponsors don’t know who is taking what), and the pill being studied is standardized with a high degree of quality control. Imagine the absurdity of a clinical trial for a new drug, with each participating hospital responsible for manufacturing its own drug, free of quality controls, with these directions: “Whatever works best for you. We want the results to be generalizable.” That’s exactly what happens in surgery and radiology trials. If there is a more unscientific parameter than MARGINS that has been subjected to evidence-based medicine, I’d like to know what it is.

Oh, that’s right. The American Cancer Society subjected the clinical breast examination to the rigors of evidence-based medicine, and decided it should be stopped! I guess there really is no limit to the absurdity to which statisticians and their death-to-rationalism clinicians will follow.

Fast forward to a time when the predicted water shortage extends to the entire country. And rather than admit the shortage and the need to ration water, the government begins a campaign to convince the public that daily bathing is potentially harmful, and offers little in the way of health benefits. In fact, bathing is painted as an unnecessary luxury, and no one bathes like Americans anyway. We should slow down to every other day, or every week, or not at all. The population responds with the usual division – pro-bathers vs. anti-bathers, and those who cling to the middle. Journalists jump into the fray, pointing out the dangers of soapy water going down the drains, the unnatural alteration of our skin flora, and the harmful chemicals that are absorbed from perfumed soap. Finally, the government steps in and enforces weekly showering by mandating timed controls on our shower heads. “Once a week” becomes the new mantra taught to all in order to control the minds of the population.

Well, we are experiencing this very phenomenon when it comes to mammographic screening for the early detection of breast cancer. Rather than admit that it has become too costly (depending on how costs are calculated) to screen annually starting at 40, we are in the midst of a propaganda campaign designed to limit or eliminate mammographic screening. Out of the thousands of breast cancer books on the market, you might be surprised to learn that, other than textbooks and monograph/pamphlets, there are no books with the lay public in mind, having the single goal of justifying “start at 40, annually” screening guidelines. It’s a “dog bites man” issue, in that the justification for early diagnosis is self-evident. Or so we thought in years prior. Today, a concerted effort is being made to cut back or eliminate breast cancer screening, and these anti-screening forces are gaining ground even among some breast cancer lay activists. The new mantra is: harms outweigh benefits. You can find plenty of books to support this view as the American public is being re-programmed to bail out of their love affair with screening. So, if the title of my upcoming book seems self-evident, it is not. If the topic seems self-evident, it is not. Who would have thought that we would ever need a book to justify early diagnosis? The best I can tell, this book will be the first to tackle the anti-screeners head-on, and to justify a bottom line that has been misplaced – that is, less screening means more breast cancer deaths. Period.

Mammography and Early Breast Cancer Detection: How Screening Saves Lives is a polemic that justifies the pro-screening school of thought. Available later this fall, I’ll offer the Table of Contents below as a teaser. One can readily see that this will not be a dry recitation of medical facts, but instead, a tour through the smoke-filled rooms inhabited by public health experts who are, remarkably, peddling death, while claiming “Trust us, we’re doing what’s best for the population as a whole.”

http://www.mcfarlandbooks.com/book-2.php?id=978-1-4766-6610-5

Table of Contents

Acknowledgments vii
Preface 1
1. Last Word vs. Final Word 5
2. Early Diagnosis May Be the Key, but It’s Not a Lock 10
3. Biology Can Trump, but Size Matters 16
4. Prostate Is Not Breast, So Give It a Rest 22
5. The Four Horsemen That Inflate the Power of Mammography 31
6. The Four Horsemen Are Throttled by Clinical Trials, but O Canada! 41
7. The Mammography Civil War (1993-1997) 49
8. The Number Games 61
9. The (Over)Selling of Mammography 67
10. The Evidence for ¬Evidence-Based Medicine (or, How to Raise the
Bar of Bias: An Editorial) 74
11. Blame It on Canada (and Something’s Rotten in Denmark, Too) 82
12. Overdiagnosis: Embracing Your Inner Malignancy 88
13. Overdiagnosis Part 2: A Way Out of the Wet Paper Bag 95
14. The Task Force Opens Fire 105
15. The Zombies Among Us 121
16. Circumstantial ¬Evidence-Based Medicine 128
17. The Social Tsunami of ¬Anti-Screening 137
18. The 2015 ACS Peace Accord–Science or Societal Pressure? 144
19. A Journey to the Pathology Lab to View the ¬By-Products of Screening 152
20. Risk-Based Screening–It Feels So Right, but Wait… 168
21. The Greatest Story Never Told 178
22. The Myth of Mammography 184
23. Do These Genes Make Me Look Dense? 192
24. The Emperor of All Modalities 201
25. The Bright Side of the Dark Side of the Force 210
26. The Crystal Ball Is Fair to Partly Cloudy 222
Chapter Notes 229
Bibliography 241
Index 247

Guideline medicine is relatively new, that is, the practice of following published guidelines based on evidence-based medicine. These guidelines are derived from consensus panels of clinicians, with whom insurers may or may not agree; however, these third party payors feel the pressure to cover diagnosis and treatment as outlined by physicians. Thus, the strength in collective expertise allows one to practice good medicine with greater ease…usually.

But there are problems, one of which is the fact that experts don’t always agree. Two sets of eyes can look at the same data and come away with different interpretations. And, when it comes to surgical and radiologic guidelines, things can really get murky because prospective, randomized, controlled trials cannot be purely blinded. Partial blinding can be done, but these trials are never as pristine as drug trials where the dummy-pill control looks just like the real thing, and neither patient nor doctor knows who is taking what. So, when it comes to surgical technique and radiologic interpretive skills, there is an unsettling tendency toward the “tall poppy syndrome,” that is, chopping the head off excellence in the name of uniformity.

Some clinical trials make no effort whatsoever to ensure quality care. The reasoning is this: your results must be “generalizable” to the community standard because you can’t expect everyone to become an expert. Centers of Excellence have thus lost considerable ground. When pre-operative MRI, for instance, was subjected to a so-called “high quality” prospective, randomized controlled trial (COMICE), the epidemiology might have been statistically sound, but the technology was substandard, the interpretations were substandard, cooperation and communication with surgeons was poor, and the outcomes widely misunderstood. To many, the p-values were the only important feature, and pre-op MRI was widely condemned. After all, it was a “prospective, randomized controlled trial” and the mere utterance of those words render magical truth.

Yet, for those who have worked hard to achieve excellence in the use of breast MRI, our outcome data is completely different than the COMICE trial results, and we can make a very strong case that MRI should be done routinely…IF IT IS DONE WELL. But critics say if you only study MRI at centers of excellence, your outcomes will have no external validity. Okay. So should we all aspire to mediocrity? “Bad MRI is worse than no MRI at all,” is an adage we have been using ever since the introduction of breast MRI into clinical practice. Yet, the pro-MRI data is routinely ignored, while policy-makers cling to substandard MRI results. A meta-analysis was even performed where mediocrity was studied in the collective sense, somehow rising above the “garbage in, garbage out” designation.

Most clinicians are familiar with the epidemiologic biases – selection, lead time, length time and overdiagnosis. But there are minor biases as well. One of them is called “file cabinet” bias or “shelf bias,” slang for the fact that enormous amounts of data go unpublished. What is the relationship between the 1% of data that gets published versus the 99% real life data that sits on shelves or in file cabinets? For instance, I have detailed data for perhaps the largest series of consecutive, routine pre-op MRI in existence. Most centers use pre-op MRI selectively or rarely, and their data is highly skewed – that is, there’s a reason why some women get MRI and some don’t, so any attempt to compare the two groups is highly biased, with the MRI group composed of younger patients, denser breasts, lobular histology, and extensive in situ components. When “no difference” in outcomes is reported with or without MRI, it may well be that the MRI group would have had much worse results without the MRI. Maybe not. However, the mere fact that a cavalier dismissal of MRI is the conclusion of these studies, in the face of glaring selection differential, is a stunning disregard of the power of bias.

But our data at Mercy Breast Center-OKC is unique. We can compare cancer yields in sub-groups to a degree greater than anyone (to my knowledge), by virtue of the complete absence of selection bias. The downside is that we have no real-time control group, so we cannot make claims about MRI vs. no MRI. With only historical controls for reference, we cannot provide high quality data as to what would have happened without MRI. But what we surrendered on that front actually strengthened our data on another front – sub-group comparisons.

When it comes to sub-group comparisons among those women who have undergone pre-op MRI, our data is unique and invaluable. This is one reason we have persisted with routine pre-op MRI as long as we have, given the apparent absence of a comparable data bank anywhere. I’ve personally kept the extensive database for 13 years, logging in over 2,000 studies, with close comparison of final path to what the MRI predicted. Yet, the data beyond our first 603 patients remains unpublished (at this point), so it doesn’t even count. And when we published our results after 603 patients in the American Journal of Surgery (Vol 196: 389-397), we had no idea that MRI was going to have its feet held to the flames in a way that was never done for pre-op mammography (for which there is not a shred of evidence, btw, that pre-op mammograms for palpable tumors alter the outcomes demanded of MRI). As a result, we didn’t spend a lot of time in that publication addressing the sub-groups, namely age, breast density, and histology.

So, when I see guidelines that say, “Pre-op breast MRI is an option for women with dense breasts and/or lobular histology,” I have to respond: “Based on what evidence?” Even though I agree with using MRI in these instances (at a minimum), the belief that MRI cancer yields are higher in dense breasts and lobular histology is not as clear-cut as most believe. If you look at our (unpublished) data, you are drawn to this conclusion – either do MRI routinely or not at all. The sub-groups targeted by the vast majority have nearly the same cancer yields as those where MRI is thought to be unnecessary. Yes, there are differences, especially with lobular histology, but not a clear cut-off point. What irony! “Selective use of pre-op MRI” is based almost entirely on a “gut feel” without empiric back-up, and our decision to keep performing pre-op MRI routinely is based on actual data, the gold standard of evidence-based medicine. Yet, we are the ones under fire.

In the community setting, we have no resources or residents to help with the publication process, so what we’ve managed so far is done at considerable burden in the private sector. But even when we do publish, our results have been largely ignored, perhaps because they run counter to the party line. Witness what should have been a highly provocative article that we published in the use of pre-op MRI in patients newly diagnosed with DCIS. At the time, it was the largest series of DCIS and pre-op MRI ever reported (The Breast Journal 2012; 18:420-427). Furthermore, our implications involved survival differences in DCIS patients, unlike invasive disease where survival should not even be an endpoint with regard to the use of pre-op MRI.

Many believe that pre-op MRI is of limited value in invasive disease when it comes to better local management of the index lesion, and then absolutely worthless in DCIS. And, because these critics are focused entirely on the index lesion, as are nearly all publications, I cannot disagree when it comes to the known area of DCIS. DCIS is so hard to define during surgical excision that a good road map doesn’t help much, if at all. But we asked a different question entirely, based on data from MD Anderson (Dawood et al. Ann Surg Oncol 2008: 15:244-249) where they reported a large observational series of 799 DCIS patients, treated unilaterally between 1976 and 2005 (no MRI is assumed for the vast majority, if not all), with the finding that the most likely event after treatment was invasive cancer (at a rate of 3.9% after only 2.9 years), usually in the opposite breast. Even more concerning was the associated increase in disease-specific mortality following the second event. Commentators (Drs. Lagios and Silverstein) pointed out that with such short follow-up, the contralateral invasion was probably present at the time of DCIS diagnosis, but remained undiagnosed.

Our series was intended to address that possibility. We ignored the index DCIS lesion, we ignored other areas of DCIS found on MRI, and we focused entirely on “elsewhere” sites of invasion that were not connected to the known DCIS, and in fact, were either in separate quadrants or were contralateral. Our results were nearly identical to the MD Anderson numbers, with “elsewhere” invasion present in 3.5% of our 285 patients.

Occult ipsilateral invasion might be treated incidentally with whole breast radiation (untreated if partial breast radiation is used), though 4/5 patients with ipsilateral “elsewhere” invasion turned out to have Stage IIA disease. But most unsettling were the findings in the contralateral breast where there will be no treatment other than possible endocrine therapy, generally considered inadequate as sole treatment for invasive disease. And again, there was a surprising proportion of Stage IIA disease, this time in half of the patients. It is very difficult to call untreated Stage IIA breast cancer “subclinical” as was the adjective of choice of a vocal MRI critic in describing all MRI discoveries.

This 2% risk of untreated contralateral invasion introduces an intriguing scenario. What do you do with this bit of knowledge? Do you perform 98 routine MRIs to capture the 2? But if you don’t, you are in essence, performing “wrong side surgery” in 1 out of every 50 DCIS patients. Take that wrong side surgery and apply it anywhere else in the body, and you’ve got gross malpractice. But in DCIS management, you have 2% of 60,000 women every year in the U.S, or 1,200 patients, who have their DCIS treated on one side, while life-threatening cancer is left in place on the opposite side (ignoring the trend toward bilateral mastectomies). I don’t have the answer to the best approach here, but I would run from dogma that says “Don’t routinely perform pre-operative beast MRI.” 1,200 lives are at stake every year with untreated (unknown) contralateral invasive cancer, and the current standard of care says, “Don’t worry about it. Stick your head in the sand. MRI is bad enough for invasive disease and plays no role whatsoever in DCIS.”

Enter the new organization called “Choosing Wisely,” http://www.choosingwisely.org, which asks specialty societies to list 5 things that should NOT be done in their specialty. An organization to which I belong, the American Society of Breast Surgeons, fell for the trap and opted to include “routine pre-op MRI” as one of the five “Don’ts.” This is a new level of dogmatism we haven’t seen since Halsted, something that has no place in science. Rather than guidelines that suggest proper treatment, we are now slipping into different territory, that is, condemnation. The very definition of wisdom decries dogma and eschews condemnation. So, as one who has a strong handle on our own extensive data plus the published literature, it is disconcerting to hear this new school of thought, which says, “WE can’t make it work, so YOU have to stop doing it.”

Our DCIS article should have started a buzz, but it got no attention at all, and to my knowledge has never been referenced. I don’t have the answer, but 2% wrong side surgery is deeply troubling. Some of the mysterious breast cancer-specific deaths of women who have only been diagnosed with DCIS, but then show up with metastatic breast cancer (landmark article in the October 2015 issue of JAMA Oncol 1:888-896 by Narod et al) could easily be due to undiagnosed invasion in the opposite breast. There are other explanations for the bizarre results in that study, of course, but I’m just tossing another possibility into the ring.

Remember, it is not our data that raised the issue of reduced mortality after DCIS and second events. It was the MD Anderson observational data that documented diminished survival in those women who were diagnosed with invasion disease within a mere 2.9 years of their DCIS, most commonly in the opposite breast. Would MRI up front at the time of DCIS diagnosis improved survival? I don’t know, but it is certainly possible. A known delay in diagnosis of invasive breast cancer of even 6 months buys you a guilty verdict in a malpractice trial, but we really don’t know what the consequences are of ignoring the 2% who undergo wrong side surgery for DCIS, when it ought to be invasive cancer treatment for the other breast.

“Choosing Wisely” needs to reconsider their use of the word “wisdom.” Perhaps, they should call themselves “Choosing Efficiently.” And perhaps, the American Society of Breast Surgeons should think again about their willingness to say, “Don’t.” In a sense, knowledge shrinks as wisdom grows (not mine – it’s a quote from philosopher Alred North Whitehead). We need more policy makers who have read Nobel laureate Dr. Richard Feynman’s essays on scientific wisdom. Of the many insightful quips of this transcendent individual, one of my favorites is paraphrased like this: “When your results verify your hypothesis and excitement abounds, stop and think through all possible alternative explanations.”

This is no small issue. Guidelines are just that. Even Johnny Depp in Pirates of the Caribbean, when challenged about not following the “pirate code,” told his adversaries that pirate laws were “really more like guidelines.” Unfortunately, when some policy-makers use the word “guidelines,” what they intend are “rules,” and nothing is more demonstrative that guidelines are morphing into canon than the word “DON’T.” Halsted would be delighted to see this resurrection of dogma. Others have said it before me – dogma is the enemy of science.