Below 40 You’re On Your Own

 Is there anything left to be said about the 40 vs. 45 vs. 50 debate when it comes to the starting age for screening mammography? Not really, but there are always new ways of representing the old. For instance, one could summarize the entire controversy by stating that those favoring age 40 are more concerned about women’s lives, while those endorsing age 50 are more concerned about cost-effective medicine.

This is a very old debate, by the way. Yes, the U.S. Preventive Services Task Force stirred the pot in 2009 with their position reversal – switching to 50 rather than their 2002 recommendation for age 40 – even though their meta-analysis of benefit (15% mortality reduction) was identical in 2002 and 2009. “Science,” they said. But in fact, they had merely orchestrated a new way of calculating the harms of screening. And then, for that final step – harms vs. benefits – there is no science at all. It is 100% subjective.

I have a 35mm slide from 30 years ago showing which organizations favor 40 vs. those that favor 50. Indeed, the debate was launched with the very first mammography screening trial in the 1960s – the Health Insurance Plan of Greater New York. Investigators made several errors in study design that put the 40-49 results into question. You can read the details of the HIP study in my book, Mammography and Early Breast Cancer Detection: How Screening Saves Lives (McFarland & Co., 2016) where I have done my best to tell the story of breast cancer screening as though I were writing a novel. As one reviewer correctly noted, “Many of the fun facts are in the Chapter Notes at the end” (even though I originally placed them within the narrative so that the reader didn’t have to flip back and forth).

But 40 vs. 50 is not what this blogatorial is about. I’m writing this month about women under 40. What do we offer them for early detection? The answer is: Prior to 2007, we offered absolutely nothing. They were disenfranchised. Self-exam is often touted, in spite of no evidence of efficacy in this age group. I keep a database on patients diagnosed at our breast center at Mercy—OKC, and one of the things I follow is “method of detection.” 95% of the time, if the patient is under 40, her diagnosis will be made by palpation, and the Stage will be II or worse.

In 2007, the American Cancer Society introduced high-risk screening with MRI as a recommendation if patients met certain criteria for elevated risk. Every bit as important as introducing supplemental MRI to mammography was the lowering of the age to begin screening from 40 to 30 (and later, age 25 with certain genetic predispositions).

But this option is greatly underutilized. Even though we have a busy risk assessment/genetic testing program at my facility, with many women undergoing early-age MRI screening, the overwhelming majority of breast cancers discovered in the under-40 group are through palpation. Sometimes, these patients would have qualified for high-risk MRI, but did not undergo risk assessment (for a variety of reasons). But most of the time, these young women develop breast cancer without substantial risk factors. They don’t meet the requirements for early-age screening.

In 2009, I was halfway finished writing a book on the “under 40 problem.” My premise was simple: “Now that we’ve settled on 40 as a starting age for routine screening mammography, here’s what we can do about women under 40.” But then came the U.S.P.S.T.F. move to age 50, and I was forced to start over writing a different book simply to support the status quo of age 40. This became the aforementioned book on screening, published in 2016.

In that book, I presented a diagram on breast cancer incidence per annum plotted by age. One can see that the incidence starts creeping up in the 20s and 30s, but the steep rise occurs in the decade of the 40s. It is this curve that prompted the inclusion of women in their 40s in the historical screening trials.

Incidence of BC from mammo book


I make the point in my book that if we start at age 50 rather than 40, we will exclude 20% of eventual breast cancer patients from an opportunity at early detection. Furthermore, the U.S.P.S.T.F. and others have suggested stopping screening at age 70-75, which will exclude another 25% of eventual breast cancer patients. And when you add the 5% of new cases under age 40, then the Task Force’s dream-come-true will be the exclusion of ONE-HALF of the eventual breast cancer patients from early detection.

And to think – I was writing a book about what to do with the neglected 5%!

To that end, by the way, I have several proposals for younger women, but the most intriguing option has always been blood testing that could prompt diagnostic imaging only if the blood test is positive. Today, everyone is a-buzz about “liquid biopsies” and the Grail Trial, etc., but my quest for the Holy Grail began in 1991 with the “placental ferritin assay” developed by Dr. Chaya Moroz in Israel. Nearly 30 years have passed since I began working with basic scientists to develop a screening blood test for breast cancer. 10,000 samples later, distributed worldwide, working with multiple entities, we still do not have an approved test (though we’re getting closer).

Such a test would provide an option for young women under 40, women over 40 who refuse routine mammography, and for women in countries without a screening infrastructure.

The remarkable thing to me has always been the apathy that surrounds the under-40 group when it comes to screening. Apparently, it was easy to forget about these women when we were allowed to screen 95% of eventual breast cancer victims. After all, we were neglecting “only” 5%.

But my approach on this neglected 5% has always been casting the number in a different light. How many breast cancer diagnoses are we talking about?

First, let me ask the reader this question: How many cases of cervical cancer – all ages – are diagnosed in the U.S. every year? We have huge awareness on this problem. Pap smears became an institution. Well, the answer is 13,000 women every year.

Now, how many women under age 40 are diagnosed with breast cancer every year, with nearly zero awareness and no good options outside of high-risk MRI screening. Well, the answer is 13,000 women every year.

 Breast cancer has that unique feature of being so incredibly common that small percentages translate to a large number of women. The sad state of affairs today is that the disenfranchised 5% will now be joined by an additional 20% (or, approximately 50,000 disenfranchised women per year) if the Task Force, the American College of Physicians, and the American Academy of Family Physicians were to have their way. Yet, this tragedy has been portrayed to the public with an Orwellian ring, couched in language that is nearly opposite to the truth. Science writers ask, “Why do so many breast radiologists and surgeons ignore the scientific evidence and still recommend age 40?”

Yes, the benefit of screening is relatively small when considered in terms of the general population. Yes, the sensitivity of mammography has been overstated for many years. Yes, the false positives are an issue. Yes, some cancers found on screening would have been unlikely to cause problems during the lifetime of the patient.

However, consider the alternative – if you want to rely on self-exams, you are settling for Stage II breast cancer much of the time, or worse. With the American Society of Breast Surgeons recently endorsing age 40, supporting the American College of Radiology/Society of Breast Imaging, hopefully we can get back to worrying about the 5% rather than the 50% of eventual breast cancer victims whose lives are being jeopardized by the Task Force and their ilk.

As a post-script, it is a curious fact that the “engine” behind the HIP of Greater New York screening study – the first effort at early detection through screening mammography – was a general practitioner turned quasi-radiologist by the name of Philip Strax, MD whose wife died of breast cancer at age 39.

NEW Recommendations for Breast Cancer Screening from the ASBrS


From: The American Society of Breast Surgeons
Sent: Friday, May 03, 2019 1:06 PM
To: The American Society of Breast Surgeons
Subject: New ASBrS Position Statement on Screening Mammography


May 3, 2019

Dear Colleague:

The American Society of Breast Surgeons (ASBrS) now recommends formal breast cancer risk assessment for all women to guide personalized screening based on calculated risk.  Ideally, risk assessment should be done at age 25 or as early as reasonably possible thereafter. For average risk, the society recommends annual screening mammography starting at age 40. For a woman with higher calculated risk, the society strongly recommends access to supplemental screening methods such as MRI based on her doctor’s recommendation and her informed preference.

The leadership reflected on the rationale for adding yet another screening guideline to the existing pool of disparate recommendations that have been endorsed by various academic and professional organizations over the past ten years. Many of these groups have advocated delayed initiation of screening mammography until age 50 or prolonged intervals between imaging, citing justifications related to cost efficiency, anxiety associated with imaging or biopsy and risks of over-diagnosis. In contrast, as physicians that guide women through decisions regarding diagnosis and treatment of breast cancer every day, breast surgeons have unique perspectives regarding the value of early detection and lives saved vs cost efficiency and possible anxiety. We wanted a mammography screening statement that was clear, concise, and based upon the strongest evidence available regarding effectiveness in saving the most lives from breast cancer.

This position statement includes robust consideration of race/ethnicity-associated variation in breast cancer burden. While acknowledging the complexity of breast cancer disparities as well as the limitations of currently-available breast imaging technology, we recognize the potential value of a strong and unequivocal screening mammography recommendation in the quest to achieve health equity in the United States. The position statement concludes: “These screening recommendations for the overall diverse population of adult women represent an opportunity to minimize breast cancer disparities through earlier detection of disease in all.”

This statement was formulated by an expert panel on behalf of the board and unanimously approved by the board of directors. Please see list of panel members and their disclosures below.


Walton Taylor


Co-Chair:  Shawna C. Willey, MD, FACS, Professor of Clinical Surgery, Director, MedStar Regional Breast Health Program, Chief of Surgery, MedStar Georgetown University Hospital, Washington, DC

Co-Chair:  Pat Whitworth, MD, FACS, Director, Nashville Breast Center, Nashville, TN

Susan K. Boolbol, MD, Chief of Breast Surgery, Mount Sinai Beth Israel, New York, NY

Judy C. Boughey, MD, FACS, Professor of Surgery, Mayo Clinic, Rochester MN

Jill Dietz, MD, FACS, Director of Breast Center Operations, Associate Professor, Case Western Reserve University, Beechwood, OH

Alan Hollingsworth, MD, FACS, Mercy Breast Center, Mercy Hospital, Oklahoma City, OK

Kevin S. Hughes, M.D., FACS, Professor of Surgery, Harvard Medical School, Co-Director, Avon

Comprehensive Breast Evaluation Center Massachusetts General Hospital, Boston, MA

Ismail Jatoi, MD, PhD, FACS, Professor and Chief, Division of Surgical Oncology and Endocrine Surgery, University of Texas Health Center, San Antonio, TX

Julie Margenthaler, MD, FACS, Director of Breast Surgical Services of the Joanne Knight Breast Center at Siteman Cancer Center, Professor of Surgery, Washington University School of Medicine, St. Louis, MO

Lisa Newman, MD, MPH, FACS, Chief of the Section of Breast Surgery at New York-Presbyterian/Weill Cornell Medical Center and Weill Cornell Medicine, New York, NY

Walton A. Taylor, MD, FACS, Texas Health Physicians Group, Dallas, TX



Relevant Author Disclosures

Alan Hollingsworth, MD – Scientific Advisory Board, Aurora Healthcare US Corp (breast-dedicated MRI)

Kevin Hughes – Honoraria from Focal Therapeutics (Surgical implant for radiation planning with breast conservation), 23andMe, and is a founder of and has a financial interest in CRA Health (Formerly Hughes RiskApps). Dr. Hughes’s interests were reviewed and are managed by Massachusetts General Hospital and Partners Health Care in accordance with their conflict of interest policies.

Pat Whitworth MD – Principal, Targeted Medical Education; Consultant, Medtronic, Cianna Medical


The American Society of Breast Surgeons

10330 Old Columbia Road, Suite 100

Columbia, MD 21046

Hotel Del — Part Two

Hotel Del

This month, I’m continuing to resurrect memories from the 19th National Conference on Breast Cancer, held in 1981 (Never heard of this conference?…check out last month’s blog — March 2019). This interdisciplinary breast cancer meeting began its run in 1962, long before San Antonio (1977), but never made it to today’s line-up. Best I can tell, it switched from annual meetings to biennial, then later merged with other American College of Radiology activities. Nevertheless, I was there 38 years ago, completely ignorant of everything being presented.

Surgical approaches were all over the map. Recall that the NSABP B-06 had not yet reported their results in 1981, so lumpectomy was not a “given” by any stretch. Mastectomy still ruled. However, the Italians were there, talking about QUART (quadrantectomy, axillary dissection and radiation therapy) in the Milan I trial, a shocking concept for those of us who only had one tool in the box – mastectomy. I don’t recall if Veronesi was the presenter or not (I wouldn’t have known Umberto from Adam anyway), but at a minimum, a member of his team showed how a surgeon could conserve the breast with relative ease (preferably, with the lesion in the UOQ, given that the approach was still en bloc resection of tumor with nodes, if possible).


Veronesi et al would beat the NSABP to the punch by publishing their initial results for Milan I in the NEJM three months after I heard their presentation in 1981 – in brief, claiming survival equivalency. I suppose Bernie Fisher was forever galled that he was not “first,” given that he had originated the groundwork for conservation, had tested the underlying principles (e.g., “common vascular channel theory”) in the lab using rat models, and had carefully prepared a scientific approach to proving his “Alternative Theory” using prospective, randomized clinical trials that had already injured Halstedians with the B-04 trial – whew! – all of his efforts beginning in the 1950s. In contrast, Veronesi had been in the extended radical camp shortly before he decided to switch to QUART, a concept still grounded in Halstedian principles. As I would understand many years later, it was the closest thing to industrial sabotage in the world of breast cancer at the time (comparable to Christiaan Barnard slipping in that first heart transplant wherein the patient lived 18 days, while Norman Shumway at Stanford spent a career in preparation for a safe and successful “first” transplant, only to end up in second place).


Although the conference sponsors did not include a single surgical society, some of the big names were there, mostly defending the modified radical mastectomy as a replacement for the Halsted radical. But there were also proponents of “ultra-radical” or “extended radical” or “super-radical mastectomies” where it was believed that Halsted was correct about the biology of breast cancer, but he simply didn’t take it far enough. Those pesky internal mammary nodes needed en bloc chest wall resection, and darned if that clavicle doesn’t get in the way when trying to remove those supraclavicular nodes.

A French plastic surgeon wearing a white suit and a dashing persona, confidently explained that breast cancer was a bilateral disease, and the only procedure that was ever appropriate was bilateral mastectomy, along with bilateral reconstruction. The premise of his argument was that microscopic cancers could be identified with regularity on the opposite side. Few at that time considered that pathology findings might not correlate exactly with the emergence of clinical disease. Having seen this issue argued (in several organ systems) during my surgical pathology fellowship at UCLA (1977-78), I was not tricked. Still, it was a thought-provoking presentation, squelched to a degree by marginal cosmesis with the reconstructions of the day.

Last month, I mentioned the Rube Goldberg apparatus that filled a room, all for the purpose of bilateral screening ultrasound, with the patient lying face down and her breasts submerged in a pool of gel. It would be more than 30 years before this concept of “whole breast” ultrasound made it into the clinic. Nevertheless, I saw the pre-pre-prototype. Breast imaging was HUGE at this conference. Mammography was considered a brand new test, barely proven, so it should be no surprise that competing forms of imaging were discussed at great length.

For instance, thermography and its various iterations was a popular topic, even though the technology had been condemned already by the American College of Radiology. The huge BCDDP was still in progress, testing the feasibility of mass population screening, initially with both mammography and thermography. But results had been so poor with thermography that it had been deleted from the BCDDP before completion of the study. Yet, here we were, 3 years after thermograms had been kicked out of the BCDDP, and all sorts of heat-seeking missiles were being proposed.

The most bizarre, I recall, was a bra with built-in heat sensors that changed color like a mood ring when the breast heated up focally, identifying a problem and narrowing it to one quadrant. There was precious little data to support its use, even in that era when it might be said that data was optional. And when an audience member attacked the speaker as being outrageously premature at best, unethical at worst (my words, but you get the picture…she was angry at the speaker for his deplorable science), the inventor finally stormed off the stage with his bra, stating: “Well, it doesn’t matter what you say, these things will be available in stores next month, and we’ve already planned a huge marketing campaign.” Catcalls followed. (We might have been in the dark ages, but the absence of light was remarkably colorful.)

You may or may not be aware that this concept of a “mood ring” bra never went away (Google “thermography bra”). Just last month, a patient of mine asked me to look at a device that was being proposed to her company (she was in charge of employee health) as a disc to be placed inside a bra, with several strips of plastic radiating from the center, another “mood ring” approach. It was the exact concept I’d seen presented at the Hotel Del nearly 40 years ago. It is noteworthy that the FDA recently had to yell “Stop” to the thermography powerbrokers who, having failed to convince the medical community, were planting their devices in spas and resorts. In a way, it’s a shame. It’s always possible that the technology will evolve into something useful, but the bias against thermography is so powerful now due to its sneaky attempts at introduction that I don’t think a valid approach would ever get a fair shake (nor would it likely add anything to the multi-modality approaches already available).

By far, the most vivid memory I have from the Hotel Del Coronado in 1981 is that of a female audience member standing up in the middle of the crowd to interrupt a speaker, and chewing him out to the point that he could barely continue. Never saw it before. Never seen it since. She made the anti-mood-ring-bra protestor seem like a wimp. Here’s how it went down:

Oddly enough, in these prehistoric days of breast cancer management, at the dawn of the revolution, male presenters (which were the overwhelming majority) would sometimes begin their talks with 35mm slides showing “artsy” breast photos. I don’t know…maybe they still do at plastic surgery meetings. But the practice has dwindled away over the years, as men became gradually sensitized to the fact that breast adulation walks a tightrope over the pit of junior high jokes. But it was so common back then that it was nearly the norm — the introductory slide would show marble breasts from a nude sculpture (at best) or a sexy actress in a low-cut top (at worst). But what I witnessed at the Hotel Del was the worst of the worst.

An older physician (who clearly had no time to contemplate anachronisms) opened his presentation with a cartoon review of breast shapes and sizes, each with a specific tag. Imagine a window-paned backdrop, containing perhaps 16 frames, each with a different breast shape, and each with its own moniker. If he had only zipped through the slide quickly, he might have made it to safety, but instead, he chose to read the “funny” names one by one.

About 3 or 4 breasts into the frivolity, a woman rose above the sea of bodies and began yelling at the speaker. I couldn’t understand her at first, as the caveman kept the hilarity going for a moment until she could be ignored no longer. After the room turned deadly silent, this was what rang out: “I can’t believe that we’re sitting here trying to defeat a disease that is killing thousands and thousands of women every year, and you’re up there like a school boy making a mockery of women and their breasts, turning our deaths into a X#!X! joke.” She followed this with a litany of insulting adjectives. I almost felt sorry for the poor guy, blindsided by 1981, completely oblivious that the 20th century had arrived and that women were making a most unusual claim – that they should be treated respectfully and as equals to men. The poor old soul just hung his head, apologized and tried to continue. (I don’t even remember his topic.)

One thing for sure – after that, I never made a joke about breasts, either through slide presentations or conversations. Not even a casual or slang reference. I never used a work of art to open a talk, and I certainly never used a busty actress. I didn’t even try to slip by, like some were doing, with various double-mound formations that occur in nature. Once, a medical oncologist gave me a slide he’d taken in Europe, a road sign with no words, just a drawing that warned motorists about two bumps in the road that were coming up soon – I never used the slide. In short, that woman at the Hotel Del nearly 40 years ago, whoever she was, scared the bejesus out of me.


Next month – Before the Hotel Del – Part 3

Blame It On the Hotel Del

Today, the decision barely raises an eyebrow. But going back to the days when the word BREAST was considered inappropriate for public signage, those of us who left general surgery to become breast surgeons unwittingly became curiosities at the same time. “Why would you do that?” (friends and colleagues would say). Breast surgery wasn’t even a recognized sub-specialty. There were no fellowships, no special certificates, and no movement toward any of these credentialing efforts.

The closest thing to getting some sort of training in breast surgery was through a surgical oncology fellowship, wherein breast cancer was a relatively small part of the picture. One of the fellowships I checked out in the early 1980s was dedicated to one guiding principle – the administration of chemotherapy. The purpose was clear: “We can’t let the new specialty of medical oncology take away a treatment strategy that was begun by surgeons.”

Then there are personal reasons for the switch from general to breast as well. In most cases, it’s probably multi-factorial. I sometimes joke (that is, half-joke) that it was my experience as a trauma surgeon (no sleep) that convinced me to become a breast surgeon (sleep). Many observers, however, insist on clear-cut motivations, to the point that beliefs emerge out of nowhere, such as one claim often stated about me: “His mother died of breast cancer, and he decided to dedicate his life to the disease.” Not true.

As one starts to visualize a horizon ahead that says “you won’t be working forever,” you can get a little sentimental, posing to yourself the simple question: “How did I end up here?” Recently, I decided a worthy project over the next few years would be to transfer several thousand 35mm slides to digital format. That process has brought back memories, good and bad. But a few slides reminded me recently of the REAL reason that I switched to breast cancer, at least the most significant event that pointed me in that direction, albeit a 7-year delay before it actually happened.

The year? 1981.

My practice location at the time? Marina del Rey, CA

Marina del Rey

A CME event: the 19th National Conference on Breast Cancer

Location of CME event: Hotel del Coronado, Coronado, CA (San Diego)

Hotel Del


To practice general surgery in Los Angeles, you needed a niche. “General” was just too broad of a stroke. All signs pointed to trauma surgery for me, not the least of which was the fact that I was the only surgeon at my hospital who had opted to get ATLS certified, then instructor-certified. This happened at the same time when the current Trauma Center System was introduced nationally, and my hospital (Daniel Freeman) decided to make a bid for Level II status, one of 15 centers needed to cover Los Angeles. After our bid was successful, I was named Medical Director by default.

Back to 1981, when I had just completed my boards and felt that I deserved a vacation, I spotted a CME offering at the Hotel del Coronado, a.k.a. the Hotel Del. I had very little, if any, interest in breast cancer at the time (biopsy-mastectomy was not very challenging), but I was not going for the educational experience. CME attendance in those days was semi-optional, so I would sign in, listen to a talk or two, then head for the beach. After all, what could I learn at this point, after I had just aced my Boards.

But a funny thing happened on the way to the beach. One talk turned into “just one more,” which turned into another, and 5 days later, I’d attended every presentation. Why? Because every talk, every subject, every presentation, was completely foreign to me. I didn’t have a clue what was going on in the world of breast cancer. And for the most part, neither did the American College of Surgeons.

The sponsors of that meeting were the American College of Radiology, co-sponsored by the American Cancer Society, the College of American Pathologists, and the Society for the Study of Breast Disease. A long list of other supporting organizations was printed on the program, and the only thing I remember is the total absence of any organization representing the specialty that insisted they were in total control of the management of breast cancer – general surgeons.

Yet, what I heard at the 5-day conference was stunning – the Italians were there with their “quadrantectomy” results coupled to the crazy idea of giving chemotherapy even without proof of metastatic disease (“adjuvant” was a new concept). The radiologists showed mammograms (the first ones I’d ever seen), showing how little clusters of calcium could actually be early cancer. Alternative forms of imaging were introduced – I remember one photo of an entire room full of equipment arranged Rube Goldberg-style, with a woman in the middle of the room, face down, her breasts emerged in a pool of gel (it was a prototype of something new on the market today – whole breast ultrasound). I was overwhelmed. My thoughts: No one in my circle knows this is going on, and I don’t think the public does either. When this stuff goes mainstream, there’s going to be a revolution. Yet, my specialty is not even listed in the program.

Shortly after returning from the conference, I encountered my first patient who requested the newfangled “lumpectomy” for her breast cancer. She had decided that she would rather be seen by a so-called breast surgeon, a certain Mel Silverstein, MD, who had just opened the first freestanding breast center in Van Nuys, 45 minutes north of my office in Marina del Rey.

Meanwhile, I wore myself to the bone trying to run a trauma center at one hospital (Daniel Freemen – Inglewood) with my private practice at another hospital (Daniel Freeman Marina).

Then, a new plastic surgeon joined our staff at the Marina fresh out of training (Dr. Grant Stevens who would later become the famous Dr. Grant Stevens, MD).

Grant Stevens, MD

Grant encouraged me to think about violating the taboos associated with immediate reconstruction, and I “broke the rules” by including Grant on my mastectomies whereupon he skillfully restored patients. One thing led to another, and we began to partner in a strategy to compete with the popular breast center at Van Nuys. We approached our administration about the idea of a “breast center,” and shortly thereafter, the Daniel Freeman Marina Breast Center was born. At least, it was born in the sense of newspaper ads and a lot of talk and publicity. We were still missing some key components, starting with a true multidisciplinary effort.

Daniel Freeman Breast Center

Several years had gone by since the Hotel Del experience, but its effects were long-lasting. And if I were to direct the Daniel Freeman Marina Breast Center, I should self-educate accordingly. Step One was reading the Harris text, Breast Diseases (Lippincott), the 1987 hot-of-the-press edition – cover to cover, complete with highlighting and re-reading. This had the same effect as Hotel Del, only magnified. The amount of clinically useful information “out there” about breast cancer was overwhelming.

The story then takes a circuitous path after a chance meeting with my old mentor in Oklahoma, G. Rainey Williams, MD, Chairman of the Department of Surgery at OU. Dr. Williams informed me that they were trying to organize a multidisciplinary breast cancer program at the University of Oklahoma…and would I be interested in returning to join the faculty at my alma mater?

After I said “Yes,” I kicked my self-induced-fellowship into high gear, focusing on two areas of interest – 1) Borderline breast lesions where I procured several sets of teaching slides – and since I’d done a one-year pathology fellowship at UCLA, was able to develop expertise. Then, Dr. David Page at Vanderbilt served as my resource, reviewing difficult slides for many years thereafter. And then, 2) Breast Imaging where I became an early skeptic of mammographic sensitivity as related to breast density, based on my patient population, with this particular pathway eventually leading me out of surgery entirely (2005) to focus on multi-modality imaging approaches.

This whole sentimental journey back to the Hotel Del began with a different intent. I was trying to document the history of “breast conferences” and could not remember the name of the meeting I’d attended in San Diego in 1981. While many believe the San Antonio Breast Cancer Symposium to be the oldest conference, you might have noticed something different from the name of my Hotel Del meeting – the 19th National Conference on Breast Cancer. This means the conference began in 1962, long before San Antonio was established in 1977.

As I tried to trace the “National Conference on Breast Cancer” throughout the years, it seems to have lost its luster with the arrival of new players on the scene. For instance, the popular Miami Breast Cancer Conference began in 1983, then a whole slew of conference options appeared on the scene. Best I can tell, the “National Conference on Breast Cancer” switched to a biennial format, with the last documented meeting I found taking place in 2014. I don’t know if this outreach of the American College of Radiology was phased out with the rise of the Society of Breast Imaging, or perhaps, the ancient conference is still in existence under a different name.

But then, in the process of searching for the fate of the National Conference on Breast Cancer, my eyes fell again upon the sponsors where I found the Society for the Study of Breast Disease (which, of course, meant nothing to me in 1981). But in 1992, I joined that society, a relative late-comer when one considers it was founded in 1979 (by two gynecologists). Dr. Istvan Nyirjesy and Dr. Doug Marchant had toyed with the idea of such a society as early as 1976, and I’m not certain of the official date of the founding, but both men served as presidents of the SSBD, first Nyirjesy in 1979-1981, then Marchant from 1981-1983. Dr. Marchant also had the distinction of starting the first university-based multidisciplinary breast center at Tufts in 1977. (Dr. Silverstein’s claim as “first” is still intact, given that he always includes the qualifier “free-standing.”)

In 1992, I sent my application to the Society for the Study of Breast Disease, to the late George Peters, MD, in Dallas, who served as the society’s 8th president. Circa 1994, the name of the society seemed a bit tedious, and we became the American Society of Breast Disease. This multidisciplinary organization thrived, and it was the society where I intended to participate actively. In 2006 (one year before ACS guidelines for screening MRI), I became the first non-radiologist to present screening data for breast MRI, my talk given to the general assembly of the American Society of Breast Disease, along with my strategy of patient selection (combining density with risk levels in a scoring system that translated to a screening interval for MRI – to this day, I still think it’s a much better approach than current guidelines).

That said, the ASBD was at its peak around this time, while a maverick organization (the American Society of Breast Surgeons) was making its mark and stealing thunder. Soon, the ASBD withered away and was gobbled up by the National Consortium of Breast Centers (2015, I believe), and was never heard from again.

I had bet on the wrong horse, but decided by then that I didn’t need to belong to the new ASBrS because I was no longer doing surgery, devoting my time entirely to multi-modality high-risk screening and genetics. But I was pulled through the back door to join ASBrS when, after several years of speaking at its meetings, I got a phone call from then-president Peter Beitsch, MD, who said (in more colorful words than I’ve stated here): “I just found out that you’re not even a member of ASBrS, yet I just appointed you to our ad hoc committee on screening. You need to join up.” So I did.

It’s been almost 40 years since my beach blanket bingo trip to the Hotel Del backfired on me and turned me into a breast disease specialist. And what a ride it’s been! As you get older and begin to contemplate an exit strategy, you drum up mixed feelings, not really sure what to do in your remaining productive years. My solution?…Take a trip to the Hotel Del and see what happens next.

Blunt Truth or False Hope?

Inflammatory BC

Inflammatory Breast Cancer — diagnosis is based on the clinical picture that accompanies the underlying cancer

In the days of “surgery alone” for breast cancer, the diagnosis of inflammatory carcinoma was a death sentence, usually in the range of 6 months. But then, reports emerged of 5-year survivors if chemotherapy was used up front, then surgery, then radiation.

And this was the hope in 1994 when I met Ruth (pseudonym), a 34-year-old who was in her first trimester of pregnancy when she presented with classic inflammatory breast cancer. Skin punch biopsy was performed, along with random core needle biopsies that confirmed the diagnosis. Then she underwent chemotherapy, beginning in the 2nd trimester, stopping prior to delivery of a healthy boy. One week after delivery, I performed modified radical mastectomy, which was then followed by radiation therapy.

Inflammatory dermal lymphatics involved

Skin punch biopsy — skin surface to the left, with a focus of dermal lymphatic invasion on the right.  This finding on pathology is not a requirement for the “inflammatory” designation, but is frequently present.

Pathology on the mastectomy specimen was not encouraging. Although the breast had responded both clinically and with only focal areas of invasion on microscopy, she still had 16 of 24 nodes positive. The outlook became even more grim when, one year later, I excised a nodule in her mastectomy scar, and recurrent cancer was confirmed.

 What do you tell the patient then regarding expectations for her future?

Younger physicians might not be aware that the standard of care for centuries was to tell the patient a lie, never disclosing that cancer was present. Plato said (in Greek, of course): “A lie may prevent the occurrence of undesirable views, beliefs or actions.” Although not covered in the Hippocratic Oath, the writings of Hippocrates place him in the same camp as Plato. And this was the prevailing practice for a long, long time, based on the notion that the patient’s attitude was critical for even a temporary recovery. Thus, false hope reigned supreme over the truth to give the patient the best possible odds.

In 1847, the AMA Code of Ethics followed suit by directing physicians to avoid making “gloomy prognostications to the patient,” (oddly, however, the physician was instructed to be completely honest with friends and relatives). “Only if absolutely necessary should the truth be given to the terminal patient.” The authority figure that led to continuation of this policy was Thomas Percival (1740-1803), “codifier of medical ethics,” whose influence extended to the AMA from beyond his grave in the U.K.

This practice of false hope was not without its detractors, however. One Rev. Thomas Gisborne wrote that physicians should be honest with patients on the grounds of conscience and the observation that “lies fail to convince patients anyway.” Instilling hope should be encouraged only “as far as truth and sincerity will admit.”

As for William Osler, apparently, he waffled on the controversy, claiming that the choice about blunt truth vs. false hope depends on context.

Remarkably, this (innocently deceptive) practice continued in the U.S. well into the 1950s and early 1960s, confirmed through several large surveys wherein the majority of doctors were still not honest with patients after a diagnosis of cancer. The rapid and dramatic shift to honesty came in the late 1960s and early 1970s in the U.S. where repeat surveys using the same questions now revealed nearly all physicians were honest about a diagnosis of cancer.

But the U.S. is not the norm. Many countries continue this deception as standard practice today, and a study in U.K. revealed that 37% of physicians still sometimes withhold the true diagnosis (I’m taking this from a 2006 reference, so it may no longer be the case – after all, it’s hard to imagine that in our current era where patients can access their own lab results online, that any deception still occurs in those countries with electronic medical records). Still, for many around the world, this practice of hiding the truth from the terminally ill continues, unchanged from Plato’s time.

At the other extreme, neurosurgeons (and occasionally, all physicians) are notorious for “hanging crepe,” that is, presenting a worse picture than probable, for a variety of reasons, not the least of which is the gross inability to predict the human brain (and many other diseases as well). And, of course, any outcome better than expected generates special praise for the user of the crepe-hanging approach.

As it turns out, breast cancer can be a lot like a head injury or a brain tumor when trying to predict the future.

For Ruth, my patient of 1994-1996, I felt the prognosis was grim, and I can’t recall how I couched the chance of survival, or if I avoided it altogether, leaving the topic for the medical oncologist. But this is my guess: I probably gave her a slightly optimistic outlook, while saying something like, “5-year survival is becoming more the norm and some patients are actually making it to 10 years.”

If I recall the actual numbers from the mid-1990s, I believe it was something like 5-10% were making it to 10 years if there were no distant mets. But for Ruth, 16 positive nodes and a chest wall recurrence so soon after completion of therapy was ominous.

With a newborn son, I have to assume Ruth was hoping for more than 10 years, even though we considered 10 years as a major triumph for a disease that had been universally fatal within months, just a few decades earlier. In truth, however, our prognostications were guesswork. Along with her pastor husband, Ruth would clearly be double-checking our estimated prognosis with the Almighty’s prescience, and would be leaning heavily on miracles of God, rather than the miracles of modern medicine.

The family moved away from Oklahoma City shortly after Ruth’s chest wall recurrence in 1996, and she was lost to follow-up even though I wondered about her on many occasions.

I’m going to pause here and give the reader a final chance to guess the outcome…

 Now, the follow-up…

One week ago (Jan 2019), Ruth’s medical oncologist and I each received a Friend Request on Facebook. It was from Ruth. 24 years had passed since her diagnosis. Disease free. Her 24 y/o son who had chemo in utero was also perfectly healthy.

Medical miracle – or – Miracle miracle?

As it turned out, it didn’t matter whether our approach was the “blunt truth” or “false hope.”  Ruth had her own success firmly arranged all along.

Like Rats Fleeing a Sinking Hypothesis

Megan handling DMBA

I claim to be an expert on rat mammary gland anatomy, a surprisingly complex topic that might seem to be of limited use in today’s world. And like many who claim expertise in a tiny niche, the truth is that it was my assistant in the lab (that is, a medical student) who did all the hard work in discovering nuances in rat anatomy that are not in the textbooks. Still, in accordance with the unwritten rules of academia, I claim all the credit.

You might think I’m kidding, since I often dabble in semi-comedic hyperbole. What could rat mammary gland anatomy possibly have to do with a clinical controversy? So, to avoid burying the lead, here’s where I’m headed – For over 30 years, researchers and clinicians have been quoting the studies of preventive mastectomies performed on female Sprague-Dawley rats in the DMBA (7,12-Dimethylbenz[a]anthracene) carcinogenesis model, wherein the number of cancers emerging after exposure to DMBA is – amazingly – the same whether or not mastectomy is performed. Of several articles on this topic, one of the more commonly referenced publications is from Wong JH et al in Surgery 1986; 99:67-71. Inexplicably, in this and similar studies, preventive mastectomies did not even make a dent in the number of cancers, roughly 5 breast cancers per rat, with or without “mastectomies.”

Then comes a non sequitur – as one prominent breast surgeon stated in the years leading up to the discovery, sequencing, and commercialization of BRCA-1 testing in humans: “Because the BRCA mutation will be present in every cell, it is possible that preventive mastectomy will have no effect whatsoever, as in the case of DMBA-induced tumors that occur with the same frequency whether or not the rat has undergone preventive mastectomy.”

Even at the time (circa 1992), that statement sounded like it contained a logical fallacy, though I couldn’t pinpoint the error from my short experience in Philosophy 101. Yet, there is an enormous difference between a “mutation in every cell,” versus “every cell will become cancer,” or even “every cell is equally at very high risk for cancer.” The human body is estimated to be composed of 32 trillion cells. If we assign 1% of those cells to breast epithelium, we’re talking about 300 billion cells. I attempt this rough calculation to avoid co-opting the phrase, “billions and billions,” attributed to Carl Sagan (but only adopted as mantra after Johnny Carson used the phrase on his TV show). Now, with 300 billion breast epithelial cells already carrying a BRCA-1 mutation, why is it that without preventive surgery, breast cancer will arise from only one or two or three clones over a lifetime? Alternatively stated, 99.999999999% of these cells never become cancer.

From the pre-BRCA era, we knew that patients with very strong hereditary risks were most likely to develop “only” one or two cancers during their lifetimes, the primary difference being earlier age of onset, far more impressive than the actual number of cancers over time. Even without a BRCA mutation, breast cells accumulate many somatic mutations over the course of one’s lifetime, sometimes generating a growth advantage to each clone, so it remains an oddity as to why only one or two clones of cancer cells emerge clinically. Perhaps the first cancer fires up the immune system to keep all the other “premalignant,” mutated cells in check. Perhaps it doesn’t even require a full-blown cancer to accomplish this. Maybe the body recognizes pre-malignant clones and acts accordingly for self-preservation. I don’t know. I only know that the mathematics don’t add up. 300 billion breast epithelial cells primed for cancer, yet only one tumor in most cases, two in some, and three or more in a few?

Many years ago (circa 1989), when I had the delusion that I was going to build a benign breast tissue research empire at the University of Oklahoma, I attended a basic science conference on the topic of early carcinogenesis in breast cancer. In my naiveté, when I checked in, I asked at the registration desk how I would get my CME. The registrar was caught off guard and seemed puzzled as I explained the meaning of CME. But she maintained composure as she broke the news to me – there wasn’t such a thing as CME at a basic science conference. I was the only physician attending.

Anyway, after I settled in, I realized that I was barely able to follow the presentations beyond the introductory 35mm slides. However, one talk was both understandable and memorable – a presentation on the somatic mutations in breast cells having normal morphology under light microscopy. Specifically, in breast cancer patients, when looking at adjacent normal tissue, many of the mutations were identical to those in the tumor, though not quite as many. But even more remarkable, some of these same mutations were present in tissue far away from the tumor, including the opposite breast. After all, what environmental insult (other than focal radiation) generates genetic “hits” in only one breast? The cells might look normal, but they are not. They accumulate somatic mutations long before changes occur under the microscope.

Then, the speaker drove the point home – “Halsted was right for the wrong reasons when he described his “field effect” as the justification for mastectomy. In fact, the field effect is real, but it’s a bilateral field effect at the molecular biologic level that only rarely translates to the clinic. And this is the case whether one is talking about accumulating somatic mutations in breast cells over a lifetime, or having germline mutations at birth. Having germline mutations in every cell certainly increases long-term risk of breast cancer, but the eventual crossover to malignancy occurs in surprisingly few cells, be it from either somatic or germline mutations…or both.

Coming at this from another angle, let’s apply the crystal ball to a 25 year-old BRCA-positive patient, and condense her future into the present. Yes, we know there are about 300 billion mutated cells, yet in the crystal ball, we see only 3 cancers emerging over 50 years, one in the RUOQ in the year 2026, one in the RLIQ in the year 2037, and one in the LLOQ in the year 2049. All 3 future cancers, however, are located within the tissue that is removed with bilateral preventive mastectomies. Thus, it does not matter that microscopic tissue containing mutated cells is left in this patient if she opts for preventive surgery, and this seems to be the case in 90-95% of patients who opt for preventive mastectomies.

Whether or not there is a direct correlation between percentage of tissue removed to relative risk reduction is unknown. I suspect those pesky residual cells in BRCA+ patients do, in fact, keep the correlation from being exact, but it’s close. My guess is something like this: If 99% of the breast epithelium is removed, there will be a 90-95% risk reduction. Since it’s a relative risk reduction, the BRCA+ patients will have a higher absolute risk of future cancer after preventive mastectomies than someone at lower risk (e.g., 90% risk reduction applied to 80% absolute risk leaves 8% lifetime risk post-mastectomies in a BRCA+ patient, whereas a 90% risk reduction applied to someone with a 30% risk leaves a 3% remaining risk).

Other variables prevent strict adherence to mathematical probabilities, however. Some patients have well-defined boundaries to their breast parenchyma while others are poorly defined. Then, there are varying degrees of precision from one surgeon to the next in carefully removing all grossly evident breast parenchyma. As for leaving the nipple-areola complex, this should be a moot point – not only are there fewer TDLUs in this area, but also if we resort to our crystal ball again, how many cancers are going to occur directly beneath the nipple? A few, but not many.

In 2017, the oncologic safety of nipple-sparing mastectomy in women with breast cancer was published in the Journal of the American College of Surgeons by Smith BL et al (Vol 225: 361-365). In 311 patients with established cancer, only 3.7% recurred locally, but there were ZERO recurrences near the retained nipple-areola complex. (We await their data on the 2,000 mastectomies performed for risk reduction in patients without cancer.) More pertinent to this blogatorial is the performance of risk-reducing nipple-sparing mastectomies in BRCA-positive patients before cancer occurs, addressed in “Oncologic Safety of Prophylactic Nipple-Sparing Mastectomy in a Population with BRCA Mutations” that appeared in JAMA Surg. 2018; 153:123-129 (and was my prompt to write this article).

In the short-term, 22 cancers were expected in BRCA1 and BRCA2 mutation carriers undergoing preventive surgery, yet no cancers actually developed. That’s ZERO cancers after 548 nipple-sparing mastectomies! In the invited commentary, there it was again, after all these years, just like in 1986: “Although it seems intuitive that reducing the volume of breast tissue would likely reduce the risk of developing breast cancer, BRCA carriers have germline mutations. Any residual breast tissue remains at the same inherent risk of developing breast cancer.”

So, we’re back to the making the distinction between “every cell has the mutation” as distinct from “every cell has an equally high potential to become cancer.” First of all, the only time each cell has perfectly equal propensity for cancer is at conception. After that, somatic mutations begin to accumulate in women (yes, even in utero) with or without germline mutations, and certain clones with a growth advantage will emerge in focal regions, not equally scattered throughout the breast tissue. Within those focal regions, further mutations will provide yet another growth advantage in even fewer focal areas, until there is eventually crossover to malignancy in only a tiny fraction of the original 300 billion cells. (Yes, the “two-hit” hypothesis for tumor suppressor genes is currently the rule, but my guess is that “clinical emergence of cancer” is more complicated than two-hits, as immune surveillance enters the picture.)

Now, back to the rats. It is helpful to note that the 2018 commentary (above) to the JAMA Surg article, reminding us of the “same inherent risk” in residual breast tissue, was written by the lead author of the DMBA article from 32 years ago wherein preventive surgery had zero impact on the rate of development of cancers. One can readily appreciate his skepticism about the short-term clinical data. Nevertheless, it takes working with the DMBA model to understand how it is analogous to the human situation, but more importantly – how the DMBA rats are different.

There are two reasons why the DMBA model is not a good way to study preventive surgery – 1) rat mammary anatomy, and 2) the DMBA carcinogen turns many cells malignant within a very short time frame.

Rat mammary anatomy – speaking as a bona fide expert now, there are indeed some analogies between humans and rats, e.g., breast tissue close to the skin predisposes to residual epithelium, very few TEBs beneath the nipple (TEBs are terminal end buds that are analogous to human TDLUs), etc., but it’s the differences that are important here. In spite of anatomic discussions describing the rat mammary “fat pad” where all the action is, there is no breast mound, or discrete parenchymal cone that one can call a “breast.” The rat has 12 nipples, each with a single duct opening to the outside, but the supporting breast parenchyma is a diffuse sheet that covers nearly the entire ventral surface of the animal, extending from lower jaw to anus and even wrapping around to the dorsal surface of the rat in some places. Diagrams of the extent of this parenchymal sheet indicate a formidable task for the surgeon who believes he or she can remove the diffuse breast tissue associated with 12 nipples. But in “our” experience, the extent of the parenchymal sheet is even more impressive, such that one is talking about removing the breast tissue from approximately one-third of the surface area of the entire animal. And in the words of my medical student assistant: “…a striking feature is the lack of boundaries in the mammary tissue.”

But that’s not where the problems end. As “we” discovered in “our” meticulous dissections, there are some mighty forces that keep the surgeon from a truly extirpative procedure. Again, in the words of James Banta, MS-2 on summer fellowship (who, after his experience with me, became an ophthalmologist): “Approaching the axilla, the most difficult part of the procedure, one encounters the cutaneous trunci muscle. It originates on the lesser tubercle of the humerus and inserts directly into the skin forming a broad, thin sheet that thickens as it approaches the axilla. This muscle penetrates the second and third mammary glands and separates them into superficial and deep layers. While the deep layer is easily removed, the remnant of breast tissue in the superficial layer cannot be properly excised without removing the thickened portion of the cutaneous trunci, which along with the breast tissue remnant, is tightly adherent to the dermis. Removing this muscle, with its breast tissue remnant, requires ligature of numerous tributaries of the dorsal branch of the lateral thoracic artery, resulting in necrosis of the skin flap.”

Yes, we have a difficult time getting rid of all the microscopic breast tissue in humans, too, but if you use Google Images for “DMBA tumors in rats,” you’ll see tumors under the animal’s jaw, or on its back, or near its tail, and it will give the term “residual breast tissue” a whole new meaning.

Add to this the second reason why this particular model is not a good one for surgical prevention — the DMBA carcinogen turns many cells fully malignant within a very short time frame.

 The DMBA model is sometimes used as a good example in distinguishing “initiation” from “promotion,” a basic principle behind carcinogenesis. DMBA does the initiating (mutations), while hormones (esp. estrogen and prolactin) do the promotion. But not so fast. As early as 1962, the prominent breast cancer researcher at Roswell Park, Dr. Thomas Dao, made the case that the hormonal milieu in the DMBA model is part of the initiation of tumor cells. So what? Well, it means that cancer cells are “created” in one lockstep, unlike human carcinogenesis. In addition, these malignant cells are widely scattered throughout all the (diffuse) breast tissue.

On the average, if you give DMBA to female, virgin Sprague-Dawley rats at the age of sexual maturity, you’ll see 100% of them develop 3-5 breast cancers after a short latency of 8 to 22 weeks. And to show how powerful the hormonal contribution is, if you perform oophorectomy on these animals 4 weeks prior to the DMBA, you’ll get zero cancers. As Dr. Dao pointed out, initiation with prompt carcinogenesis (without true promotion) is thus accomplished through the combination of DMBA and hormones together. Hormones might have some additional promoter aspects, but this is secondary. Cancer cells are created at the git-go, and they are widely scattered.

In another departure from human counterparts, these histologically malignant DMBA tumors metastasize only rarely. If it were not for euthanasia, the tumors would kill through their bulk and local effects, draining the animal of all resources for life. So, most studies end by counting the initial wave of cancers, then putting the animal to sleep. So, what happens if you remove these cancers as quickly as they appear? They just keep coming. So many malignant cells are created by DMBA that there’s seemingly no end to the number of cancers.

And this is the scenario that some conceptualize for the BRCA-positive patient when they say “cells are just one step away from being cancer, so the risk is not lowered if any cells remain.” But this ignores our crystal ball for humans where we can see 3 or 4 cancers (max.) spread out over a 50-year time frame. (Yes, I know, we’ve all seen 5 or more simultaneous separate cancers in one breast, but this is a rare exception and raises questions if these are truly 5 different clones or, more likely, a pre-existing widespread DCIS, or intramammary lymphatic spread, or….but I digress.)

Pathology in the DMBA model is usually drawn from palpable tumors. But if you sample anywhere in the diffuse sheet of breast tissue, you’ll find wildly atypical cells that are lying in wait to emerge later. In contrast, when a BRCA-positive patient undergoes preventive mastectomy, most of the tissue is completely normal, maybe with too many lymphocytes in the lobules (perhaps keeping those billions of pre-malignant cells in check).

Yes, there is a fairly high rate of focal high-risk lesions in preventive mastectomy specimens, as well as 2-4% with invasive cancer in BRCA+ patients. But compare the reported pathology findings in BRCA-positive mastectomy specimens to the much-lower-risk preventive mastectomy patients, and you won’t find a great deal of difference in the incidence of ADH, ALH/LCIS, borderline lesions, or even occult DCIS (highly dependent on sampling technique, of course). A few articles even describe the BRCA patients with a lower incidence of high-risk lesions. But nothing compares to the DMBA model where it’s hard to find normal breast tissue anywhere. The point is that, in humans, there is a mismatch between the “molecular biologic field effect” that is present with either somatic mutations or germline mutations versus what emerges clinically. Therefore, we should rest our cases on clinical observations and not the DMBA model.

The primary benefit of the DMBA model is to test various hormonal strategies in the prevention and treatment of breast cancer, given that the malignant cells created are usually hormonally responsive. And this was why I had my team at the University of Oklahoma adopt the DMBA model, which is no easy feat when you’re starting from scratch (lab space, funding, animal care and protection regulations, handling of the highly carcinogenic DMBA, etc.). From this, we published on the prevention of rat mammary carcinoma with leuprolide compared to oophorectomy, then again with leuprolide compared to tamoxifen, plus we dabbled in experimental GnRH agonists and melatonin prevention as well.

The summer after the first year of medical school used to be wide open, and I made the decision to offer a (competitive) summer fellowship that was one-half clinical and one-half research. Funded by a small army of women that helped me at the time, the fellowship became very popular and was always filled with top students, such that we tried to take on more every year (we peaked at 4 students one summer). My purpose was not altogether altruistic, as I hoped to make an early impression on the impressionable, developing the future personnel who would fill the multidisciplinary clinical spots as well as the multidisciplinary research spots at OU. It worked well. In fact, our first student in the fellowship, Elizabeth Jett, subsequently became a breast radiologist and is currently the Director of the OU Breast Institute, where I had served as the founding medical director in 1993. One of my favorite photos from that era is Betsy holding a Sprague-Dawley rat while attempting a smile through her disgust.

But of all my prior students, it was poor James Banta, future ophthalmologist, who got caught in a hair-brained scheme I had at the time – laser photodynamic therapy (could we tag indocyanine green to cytokeratin?) to eradicate the residual breast tissue after mastectomy in the Sprague-Dawley rat (with human applications, of course). It seemed like the natural thing to do, that is, remove all the breast tissue you can surgically, then obliterate the remaining epithelium non-surgically. We were not total hacks when it came to the laser approach. We had the expertise and advice from Wei Chen, PhD who, 20 years later, would be awarded an R-01 grant from the NCI for his “laser photodynamic therapy with combined immunologic boost” approach in a variety of cancers. But in the poor Sprague-Dawley rats, it was just too much, even though we applied the laser to just one side of the animal (see photo below for back-of-the-envelope planning as we designed our study groups).

DMBA research


In spite of our best intentions, we had an unacceptable mortality rate, and our never-published paper that followed was a treatise on surgical technique used for preventive mastectomies in rats, coupled with an extensive discussion of aggressive post-op care of the animal to avoid mortality. Like rats fleeing a sinking hypothesis, we ended the laser project. And from that experience, an ophthalmologist was born.

Returning to the question at hand – what is the future breast cancer risk for patients who undergo bilateral preventive mastectomies for BRCA-positivity, or for that matter, any of the strong genetic predispositions? We already know short-term risk is dramatically reduced in several studies. And, longer-term risk is also apparently reduced, as evidenced by the Mayo Clinic data where the mastectomies were done many years ago, then BRCA tested later. Numbers are small (26 with BRCA mutations), but zero cancers occurred after a median follow-up of 13.4 years. Importantly, 90% of the women in the Mayo Clinic series had the old-fashioned “subcutaneous mastectomy” wherein more tissue was left behind than today’s iteration of “nipple-sparing mastectomy.” Perhaps, modern results will be even better. The meta-analysis of De Felice F, et al (Ann Surg Oncol 2015; 22:2876-2880) suggests a 93% relative risk reduction, although a number of caveats exist here (starting with the admitted possibility of some patients from different studies being counted twice).

Since we aren’t certain about lifetime risks (or even 20-year risks) after preventive mastectomies, how do we counsel patients as to future risk? While some are confident that no cancers will occur, and their patients are told “no need for imaging follow-up,” I am biased by a small group of patients in my care who underwent subcutaneous mastectomies (old school technique) many years prior to BRCA testing, then were found later to harbor the mutation (similar to the Mayo Clinic sub-group). Their preventive surgeries were performed on the basis of family history, but then later developed breast cancer in their skin flaps (with the longest interval between surgery and cancer being 37 years in a BRCA1 positive patient – surgery at 40, then triple-negative cancer arising beneath the skin flap at 77). I consider these patients to remain at lifelong risk (probably a linear risk), prompting my policy of ongoing imaging. Interestingly, none of the cancers in my patients arose beneath the salvaged nipple-areolar complex.

As we await better long-term data, I offer another example as to how I handle counseling: If we’re talking about a 40 year-old BRCA+ patient who has 40 more years of life expectancy, and whose strong family history places her at the high end of the wide range of risk (80%), and then she undergoes bilateral salpingo-oophorectomy, her risk will be reduced to an estimated 40% lifetime (50% relative reduction from an absolute 80% to 40%). This remaining risk can also be stated as “1% per year.” Then, for further risk reduction, she undergoes bilateral preventive mastectomies, which takes her from 40% to 4% (lifetime). In this case, the 90% relative risk reduction is applied to the absolute 40%, leaving 4% (or 0.1% per year).

If, however, someone is diagnosed with a BRCA mutation later in life, age 50, after the benefit of early-age BSO is lost with regard to breast cancer, then she has higher risk (though not the “full” 80% that she had at age 25). If she has a strong family history to support the mutation, then she has an approximate 60% remaining lifetime risk spread out over 30 years, or 2% per year. A 90% relative reduction of this 60% leaves her with a 6% lifetime risk of breast cancer after bilateral preventive mastectomies. This 6% is only slightly less than the average risk patient at the same age who has never undergone breast surgery. This is my mathematical justification for continued monitoring and screening in most gene-positive patients who have undergone preventive surgery. In reality, it’s a matter of logic pending data, using lower school math.

For a quick tutorial on the controversies surrounding our current attempts to project risk and counsel patients, let me recommend the invited editorial by David Euhus, MD (Ann Surg Oncol 2015; 22:2807-2809), written in response to the 2015 meta-analysis mentioned above.

And please, no more extracting DMBA data to apply to human preventive surgical approaches. Let the rats off the ship. We have enough clinical evidence to know that preventive surgery in humans lowers risk substantially. Although our data is largely short-term when compared to “lifetime,” there is no reason to believe that these dramatic reductions in risk are only temporary and that the genetically-primed cells are going to “catch up” later on, rendering surgery a waste of time. No, the most pressing data is going to be the impact of surgical prevention on survival. That data is, in fact, starting to trickle in, and things are looking good so far.

Lifetime Risks are Lame – Let Me Count the Ways

Along with the 2007 announcement from the American Cancer Society proclaiming that women at high risk for breast cancer should be screened with MRI came an unfortunate by-product – the golden calf of LIFETIME RISKS.

My choice of “lame” is not without some thought, the implication being that one can still walk if lame, but it can be a struggle.

The often-ignored definition of risk assessment is the calculation of “absolute risk over a defined period of time.” The problem is: “lifetime risk” is poorly defined. There is a world of difference between cumulative lifetime risk (what many conceptualize) and remaining lifetime risk (what the models actually calculate).

In addition, the certainty about the power and persistence of risk grows less and less over time. Many of our lifetime risks are simply linear extensions of shorter studies. For instance, the Tyrer-Cuzick model will calculate almost 70% lifetime risk when a 35 year-old is diagnosed with LCIS, but most follow-up studies are limited to 20 or 30 years. No cohort of LCIS patients has been published with a mean follow-up of 50 years, which is what the T-C model is calculating in a 35 year-old.

Then there is the question about calculating lifetime risks to identify patients to apply screening technology that is unlikely to be in use in 50 years. And the bigger question is whether or not screening for breast cancer will be required at all in 50 years. Eventually, with an effective “cure” for all stages of disease, there will be no need to screen.

Lifetime risk calculations are not without serious hazard. By generating high numbers (esp. to get insurance coverage for MRI screening), there are some women who will “jump ship” and move ahead toward preventive mastectomies based on inflated figures. Lifetime risks have the curious tendency of “piling up” and weighing the patient down as if the entire load is going to come spilling down on her “any day now.” The addition of SNPs to risk modeling has the potential to make that scenario more common, with inflated values for risk that have never been prospectively validated after consolidation (grouping individual SNP risks into a whole).

I was challenged to learn more about risk assessment in 1991 by Dr. David Page who cautioned back then: “Limit risk assessment to a 20-year maximum calculation” (for all the reasons above). It took many years to fully understand this sage advice, now applicable to my longstanding criticism of our MRI screening guidelines.

Admittedly, it was a stretch for the American Cancer Society (ACS) to endorse MRI without mortality reduction data (and with relatively small studies), but they correctly understood that proof of a mortality reduction by adding MRI to mammography would be difficult to come by within a reasonable time frame. Here we are, 11 years later, still with no mortality reduction data for MRI screening, a benefit that will only be confirmed through a prospective, randomized trial.

At the same time, there was incontrovertible evidence that MRI was detecting many more cancers than mammography (double to triple the number). Without confirmation of a mortality reduction for MRI, the next best thing is the surrogate of Sensitivity. (Specificity only addresses the practical aspects of screening, not mortality reduction).

Invoking deductive reasoning, the syllogism works something like this:

Major Premise: Early detection with mammography reduces breast cancer mortality by 20-30% with only 40% Sensitivity, indicating that breast cancer biology is quite vulnerable to early detection.

Minor Premise: Screening MRI has a 90% Sensitivity, and Sensitivity and Biology are the only variables involved in mortality reduction.

Conclusion: Screening MRI will result in a mortality reduction well in excess of what is achieved with mammography alone.


Had there not been the foundation of a proven mortality reduction with screening mammography, then a proposal to screen with MRI would have floundered. And if you winced while reading the “40% Sensitivity” for mammography, I did not pull that out of thin air. In fact, that’s the sensitivity level for mammography when compared to MRI in the combined analysis of 5 international MRI screening trials. (Sardanelli F, Podo F. Eur Radiol 2007;17:873-887). If you don’t like this 40%, the ACS weighed in as well, basing their recommendations on 6 international trials (the 5 above plus one more) wherein mammographic sensitivity ranged from 16% to 40% (Saslow D, et al. CA Cancer J Clin 2007; 57:75-89).

So, going out on a long limb, the ACS opted to create guidelines for patient selection that approximated how 6 international MRI screening trials had been designed. And that’s when the problems began. Relying on the strategies used for patient inclusion in those trials laid a faulty foundation. The MRI screening trials were not focused on ideal patient selection, but on proving the benefit of MRI. Lifetime risk was the norm for all studies. This skews the experience to favor younger women where lifetime risks are higher, based on the key word – remaining.

All our mathematical models calculate remaining lifetime risk, not total cumulative lifetime risk. As we age, we “pass through” our various risks, until we finally meet up with that 100% risk of death, wherein the remaining lifetime risk for any new disease is finally 0. Thus, lifetime risks DECLINE over time, while short-term breast cancer incidence INCREASES over time.

By focusing exclusively on empirical data to the exclusion of rational thought, we got our risk strategies perfectly backwards. Consider tamoxifen prevention. Entry requirements for the NSABP P-01 trial were based on short-term risks even though the effect of tamoxifen is durable over the long-term. Here, we should be using 20-year risk calculations, but by sticking to guidelines that duplicate P-01, we use 5-year risks primarily. In contrast, with MRI screening – where we want to know the probability of a mammographically occult cancer in the short-term, specifically on a given day – we use long-term risks that lamely reflect the chance of a cancer being found on an MRI in the short-term.

Granted, when we use lifetime risks, we are increasing cancer detection rates (CDRs) over the long term due to the higher rate of disease incidence. And if we were using MRI to screen only BRCA-positive patients, a substantial difference in CDRs would exist. But when we move down to the 35 year-old at 21% lifetime risk for breast cancer vs. the 35 year-old at 12% general population risk, the difference between CDRs over the next 20 to 30 years is negligible. This is what keeps “precision screening” from being precise. When you convert risk levels to the actual differences in yield, there’s really not that much difference between high risk and normal risk, with the exception of patients at “very high” risk.

Even the initial prevalence screen in high risk vs. baseline risk does not generate as much difference in CDR as one might expect. Check out the prevalence screen data from Dr. Christiane Kuhl’s MRI screening study in the general population (Radiology 2017; 283:361-370) – it’s a comparable CDR on that first screen (22.6 per 1,000) to what one finds in the high-risk international screening trials (i.e., 22, 22, 23, 29, 30 and 36 per 1,000).

Returning to the main reason lifetime risks bomb when put into practical use – the impact of age on remaining lifetime risk – let’s walk through the two different ways in which “lifetime risk” can be conceptualized:

The oft-quoted “12% lifetime” is total risk over the course of an entire lifetime, from birth to age 90 or beyond. This is a cumulative lifetime risk. (And if we take away those women with known risk factors for breast cancer, it’s not 12% — but more like 7% to 8%.) However, this is NOT what the mathematical models calculate. All models calculate remaining lifetime risk, which is directly related to the patient’s age, that is, the remaining number of years anticipated.


powerpoint #1


In the diagram above, the top graph demonstrates how we tend to conceptualize lifetime risks where the solid line indicates lifetime cumulative risk for the general population (12%), starting at age 20, with the patient icon at the end of that long accumulation. The dotted line below the solid one represents the “lifetime risk” that a 60 year-old is facing for her remaining years (7%). These cumulative lifetime risk graphs are deceiving in that one senses a persistent rise in risk over time. In reality, however, the lifetime risk as viewed with the patient icon looking forward in time (bottom graph), reveals that remaining lifetime risk is actually declining.

But that’s only the first step in clearing the confusion. Once you realize we’re talking about a declining number over time, how do you reconcile increasing short-term incidence for breast cancer to a peak age at 55-60? I fashioned the diagram below for my book – Mammography and Early Breast Cancer Detection: How Screening Saves Lives (McFarland, 2016) – trying to illustrate why we have the paradoxical situation of high short-term risk (in terms of rate/100,000) in the face of declining lifetime risk. That is, lifetime risks are going down, while short-term incidence is rising.

Powerpoint #2


To try and explain this paradox, I used two different y-axes. The dotted lines related to the y-axis on the left represent remaining lifetime risk, the top line for a high-risk patient, the bottom line for a baseline risk patient. The solid line relates to short-term incidence with the y-axis on the right. Since there are different units of measurement for the 2 y-axes, the design was created for illustrative purposes to make the point that these two oft-quoted numbers are paradoxically at odds with each other. As one ages, their remaining lifetime risk is in constant decline, whereas the short-term incidence peaks around 55-60, then slightly declines.

As a result of this paradox, the use of lifetime risks is highly discriminatory to the older age groups (and don’t forget the net benefit of mammographic screening, in general, is found from ages 60 to 69). A young woman with risk factors can easily qualify for MRI even though her short-term probabilities of breast cancer might be low, while the older woman with the same risks and high short-term probability fails to meet the Golden Calf standard of “20% or greater lifetime risk,” according to American Cancer Society guidelines (with NCCN and others joining in later using very similar guidelines, endorsing the 20% threshold).

I’ve used the following example of age consequences and discrimination since 2007 in multiple publications and presentations, and it still holds true today:

Powerpoint #3


When it comes to screening MRI, the question we’re asking with selective screening is “How can we maximize cancer detection rates (CDRs) to make this cost-effective? These CDRs are directly related to disease prevalence and incidence in the screened population, and it has been the specious conclusion since 2007 that the best way to do this is through “remaining lifetime risk.” But look what happens in the example above, where the 30 y/o easily qualifies for MRI, but her risk over the next 10 years is only 3.5% (Claus model). Because the 60 y/o with the same risk factors is discriminated against through the use of lifetime risks, she fails to qualify for breast MRI even though her chance of having a mammographically occult breast cancer over the next 10 years is TRIPLE the patient who does qualify for MRI.

And in another twist of the same principle, if a 30 year-old has no risk factors other than a biopsy showing ordinary hyperplasia, the T-C model will calculate a 23% lifetime risk, which is based on 55 years of remaining risk. So this 30 y/o qualifies for MRI, while our 60 y/o in the example above with two first-degree, premenopausal relatives with breast cancer does NOT qualify? And we’ve lived with this since 2007?

In the last scenario on the Powerpoint slide above, if we look at a 60 y/o patient with NO risk factors, her 10-year risk is nearly identical to our “very high risk” 30 year-old. Yet, try to order a screening MRI on a 60 y/o with no risk factors and then watch the brouhaha that follows. Remarkably, the ACS guidelines include the specific admonition that MRI is “not recommended” for women with lifetime risk under 15% — which, through age discrimination, excludes many women with occult cancers at a short-term rate higher than younger patients who qualify for MRI. An active statement against MRI screening based on lifetime risks is emblematic of a serious misunderstanding of the long-term-short-term paradox described above.

If you ever wondered why the NSABP P-01 trial for tamoxifen prevention used “risk of a 60 y/o woman without other risks” as their threshold for inclusion – in effect, turning an average patient into a “high risk” patient – it’s because of the paradox noted above, wherein the NSABP needed quick answers so they focused on short-term incidence rather than remaining lifetime risks. In contrast, the MRI studies and subsequent guidelines did just the opposite, focusing on long-term risk to the exclusion of short-term incidence.

Here’s yet another variation on how age discrimination is an inherent feature of remaining lifetime risk: At the individual level, a woman who barely qualifies for MRI at a young age will be unqualified (or disqualified) later, perhaps within a mere 5 years. Remember, remaining lifetime risks decline over time. And if you’re not updating previously calculated risk every 5 years or so, then you’re quoting a number higher than reality allows. 100% of our patients have declining lifetime risks, and it takes some effort to recalculate those risks periodically. I try to do this every 5 years, though I still encounter patients whose risk calculation is fossilized.

Example: Take the typical patient with one first-degree relative with breast cancer, her mother diagnosed with breast cancer at age 60. When the patient is age 40, the Tyrer-Cuzick model will calculate a 22% lifetime risk for breast cancer, qualifying her for screening MRI. But as time goes on, and the patient reaches age 55, just at the point when short-term incidence is peaking (and closing in on her mother’s age when diagnosed), she has passed through enough risk that the T-C model now calculates 18%. Too bad. No MRI.

In the ACS publication that announced the 2007 guidelines, Table 4 shows the fairly wide variation from one model to the next, using 5 different risk scenarios applied to the “preferred models” as advised by the American Cancer Society (BRCAPRO, Claus, Tyrer-Cuzick). The variation is concerning, yes, but here’s the kicker – All 5 clinical scenarios begin with the patient (or proband) being 35 years old. Why wasn’t there a Table that showed the much wider variation imparted by different age groups? Did the authors consider the difference between “cumulative” and “remaining?” Or, were they so fixated on the starting age for MRI screening, they forgot that many women enter high-risk programs at 50 or older, when the incidence peaks (and where it is harder to qualify for MRI)?

How difficult is it to fix the problem? Even though countless women have been denied breast MRI for the past 11 years due to age discrimination imparted by the faulty guidelines, the “fix” is so simple as to defy logic as to why it has not been done already (new guidelines are due any day now, I’m told). You simply add the option of a short-term risk calculation in addition to the lifetime option. Introduce a 5-year risk number and the problem is fixed (unless the threshold is too high).

As it stands now, we have patients qualifying for MRI but not SERM risk reduction, while others qualify for SERM risk reduction but not MRI. That makes no sense. “Here, take this pill every day for 5 years after reviewing the long list of side effects, including death from DVT….but sorry, you’re not at high enough risk to qualify for MRI screening.”

The trial design of ACRIN 6666 indicates that there are “some out there” who understand that CDRs are boosted through the use of both short-term and long-term risks, the former designed for older women, while the latter for younger women. It’s the only way to handle the paradox of short-term vs. long-term risk. In the ACRIN 6666 trial of screening ultrasound (with a subgroup also getting screened with a single MRI), patients had to have breast density (a complex definition) as well as a single risk factor in addition to the density. The single risk could be a Gail calculation of lifetime risk…..or a 5-year Gail calculation.

Trial design took place prior to widespread adoption of the T-C model, but the rationale used displayed a deep understanding of how to improve yields based on equitable criteria. For instance, the requisite degree of risk was lessened as density increased. Think about it. Two parameters – risk and density – intimately bound when the endgame is the probability of a mammographically occult cancer. Like the high risk patient, the high density patient is more apt to have a mammographically occult cancer than a low density patient. So when the density level is higher, the requisite risk level was relaxed in ACRIN 6666. It’s rational and insightful.

We are doing something similar at Mercy Breast Center in OKC in a NCI-funded study of 4,000 normal mammograms (NCI R01CA197150), using a computer analysis system with machine learning that converts density patterns to a Risk Score, comparing left to right, and year-over-year, a computer program developed by Drs. Bin Zheng and Hong Liu at the University of Oklahoma Advanced Cancer Imaging Lab in Norman. We use a sliding scale, wherein a Risk Score of 0.80 prompts a screening MRI, but if density is Level C, then a score of 0.75 qualifies, and for Level D, a score of 0.70 qualifies.

When the 2007 guidelines for MRI screening were released, there were so many inconsistencies and oddities, I assumed that corrections and modifications would be prompt. That has not been the case. As noted above, the guidelines were largely dependent on the international trials where the focus was on MRI performance, not risk assessment strategies. In fact, if you read the inclusion criteria of the international MRI screening trials, it’s not always clear in some of the studies how patients were selected.

In our 2014 publication that challenged current guidelines for MRI screening (The Breast Journal 2014; 20:192-197), we performed risk calculations using Gail, Claus, and Tyrer-Cuzick on all patients who had their cancer discovered through routine asymptomatic screening with MRI. Most of our MRI discoveries would have never happened had we relied on the ACS guidelines due to the fact that we had incorporated breast density levels into patient selection. This point system was first proposed prior to the 2007 ACS guidelines, although not in print until 2008 (Hollingsworth AB, Stough RG. Breast MRI screening for high risk patients. Semin Breast Dis 2008; 11:67-75.)

At the time when we introduced our point system (2008 in print, 2004 first use), we had only diagnosed 7 patients with MRI screening. None were identified with the Gail model, none with Claus, and only 3 of 7 with Tyrer-Cuzick. The impact of using breast density as an equal parameter to calculated risk was apparent to us early on. Our strategy also took into account the wide variation in the different models (by not relying on their illusion of certainty) and avoiding the paradox of declining lifetime risk in the face of rising incidence by simply placing patients in one of 3 risk level categories: Baseline Risk, High Risk and Very High Risk.

This might seem reactionary, but I’ve never fully embraced the mathematical models. Why? Their merging of risk factors is based on accepted statistical modeling applicable to industry in general, but with no accounting for the biologic interaction between risks. As such, the Gail told us that Atypical Hyperplasia and Family History were synergistic, consistent with the original work of Page and Dupont. But then (with the blessing of Dupont) the Mayo Clinic data now indicates that family history contributes nothing in this situation – the risk of Atypical Hyperplasia trumps family history and imparts the same level of absolute risk regardless of other factors. On a bigger scale, this is biology trumping mathematics.

And to support my skepticism of the mathematical models, look at the c-stats for the various models that reflect “discrimination” at the individual level. They’re not pretty. Better than flipping a coin, but nothing to brag about and well below predictive models in other diseases. The c-stats are comparable to “accuracy” in the statistical sense, and while the original Gail had an embarrassing 0.58, we’re still not above 0.70 with the latest and greatest models. Yes, you might see the word “excellent” associated with various models, but they will be talking about “calibration,” not discrimination. Calibration is the predicted-to-observed ratio, that is, how many cancers will develop in a cohort. And therein lies the unequivocal benefit of mathematical modeling – that is, in the design of clinical trials where investigators need to predict the number of breast cancers that will occur. But at the individual level (discrimination), not so good.

It is probably no surprise that I still like my original scoring system more than any other option. With 4 levels of density and 3 levels of risk, we generated a total that converted to a recommendation of 1) annual MRI, 2) biennial MRI, 3) triennial MRI, or 4) No MRI. In this model, patient age has no impact at all on selection for MRI. As a result, the age distribution in our MRI-discovered cancers closely reflects age-at-diagnosis in the mammographically screened population – that is, 80% of our MRI-discovered cancers are in patients over the age of 50.

Powerpoint #4

By the time of our 2014 publication, we had diagnosed 33 patients with MRI screening. Had we used the Gail model, only 9 of 33 cancers would have been discovered. Had we used the Tyrer-Cuzick model (where calculations are consistently higher), still only 12 of 33 cancers would have been discovered. And poor Claus – originally, the “preferred” model as it was the only model used in the international trials (of the 3 that used modeling) – here, only 1 of 33 patients would have qualified for MRI screening. Using all 3 models and opting for the highest calculated risk, and adding BRCA positivity, we still would have identified only 16 of 33 cancers (48.5%) in this loose interpretation of ACS guidelines.

Clearly, there are problems with the current guidelines. And it’s really quite simple – if you are going to use a second line of defense (MRI, in this case), then its use ought to be predicated on the probability that the first line of defense is going to fail. That first line is mammography, and the probability of failure is based entirely on breast density. Using risk factors alone (without density) to select patients for MRI screening does not address that first line of defense in any fashion whatsoever, an incomprehensible deficiency.

In fact, even though risk and density were equally weighted in our 2008 “point system,” one can make the case to jettison risk calculations entirely, and base MRI screening on density levels alone. Witness what is going on in The Netherlands with the DENSE Trial of MRI screening. This is a prospective, randomized trial of mammography every 2 years versus mammography plus MRI every two years in women aged 50 to 75 (over the course of 3 screens), using a single entry criterion – Level D density.

 Risk levels have been tossed out (other than the inherent risk of Level D mammograms) and the entire study is predicated on the idea that this group of patients will harbor a substantial number of mammographically occult cancers (comparable to the yields in the high risk MRI screening trials). If the ACRIN 6666 subgroup that underwent a single MRI is any indicator, the Dutch will generate a landmark study that, by the way, includes mortality reduction as one of the endpoints.

I began this blogatorial with the intent to focus on the paradox of long-term risks versus short-term incidence, but before I knew it, I had slipped into my chronic, ongoing rant about the treatment of mammographic density as some sort of isolated risk factor that “needs more research” in the 2007 MRI screening guidelines.

But there is so much more in the current guidelines to whine about – such as the disconnect between risk of breast cancer and risk of gene-positivity (addressed by Kevin Hughes, MD and his team in Cancer 2008; 113:3116-3120). Then, there’s the odd approach to tissue risks by the ACS wherein suddenly “lifetime risk” with ADH/ALH/LCIS is tossed out the window and the risks are described with short-term values, such as “12-year follow-up.” So, a young woman at 40% lifetime risk after a diagnosis of ADH does not qualify for MRI while the same woman at 21% lifetime risk due to family history will qualify (thankfully, peer reviewers don’t follow the letter of the law, and the ADH patient will usually qualify.) This is a good thing. We are now up to 52 MRI-discovered cancers, and ADH was the dominant risk factor in 12 of the 52.

Okay, I’m clearly rambling now, and the next thing you know, I’ll be discussing the exclusion of patients with prior breast cancer in the “needs more research category” where I guess we’re supposed to be comfortable with 40% sensitivity for mammography.

The revised MRI screening guidelines – 2nd Edition – were targeted for release several years ago, and I’m not sure what happened. When the ACS released their revised mammography screening guidelines for the general population in 2015, it was stated that the high-risk guidelines would be next. I can’t complain that I didn’t get the opportunity to make my case. Although no one invited me to the party that will decide the new guidelines, I did have the opportunity at a committee meeting to chat with one of the key policymakers at the American Cancer Society who will be guiding the new recommendations. As I discussed the age discrimination problem, it was clear that all the ramifications of our current system had not been considered the first time around, especially as pertains to remaining lifetime risk.

So, we await the new guidelines. After what I’ve seen so far, given the precious few who have devoted careers to the nuances of risk assessment, I’ve got to raise this skeptical toast to the policy-makers: “May you not make things worse than they already are.”