The Health Care Act and the Hippocratic Oath

               I almost never “surf the net” and have no idea what’s circulating unless someone forwards something they want me to know about.  That’s how I ended up watching a YouTube video http://www.youtube.com/watch?v=6e3udzHIiVs in which Dr. Jill Vecchio rails against the Supreme Court’s decision regarding the Affordable Health Care Act.¹ When I last looked, the video had been viewed more than 750,000 times.

                For a video less than three minutes long, it contains a remarkable number of misleading statements about the Affordable Health Care Act and screening mammography. I’m dismayed by the number of individuals who have viewed the video and by Dr. Vecchio’s not-so-subtle threats that if President Obama is not defeated and the Health Care Act not overturned, we all will be abandoned by our physicians. It’s to counteract the misleading statements and her threats that I’ve written this post. Please forward it to others if you think they might find it useful.

Dr. Jill Vecchio

                Dr. Vecchio is one of 28 radiologists at Rocky Mountain Radiologists, a professional corporation located in Denver, Colorado.  Rocky Mountain Radiologists provides services to imaging centers in the Denver metropolitan area and much of the northwest corner of Colorado. It reviews films read by non-radiologists for a multitude of private practices and urgent care centers throughout Colorado and has recently expanded to other states and countries outside the U.S.² It also provides, for a nominal fee, a condominium in Steamboat Springs so its employees can enjoy the ski slopes.³

                Dr. Vecchio specializes in “Women’s Imaging” and mammography at Rocky Mountain Radiologists. And she is Director of the Exempla Lutheran Breast Care Center in Wheat Ridge, Colorado.⁴

The Video

                Taxing is not forcing. Near the beginning of her video Dr. Vecchio implies that “by taxing, they are forcing us….” I’m not sure exactly what she thinks we’re being forced to do by the Health Care Act. But whatever it is she thinks it is doing, the Affordable Health Care Act is not forcing anyone to participate in a Federal health insurance program. Section 1555 of the Act explicitly states that “No individual, company, business, nonprofit entity, or health insurance issuer offering group or individual health shall be required to participate in Federal health insurance program created under this Act (or any amendments made by this Act), or in any Federal health insurance program expanded by this Act (or any such amendments), and there shall be no penalty or fine imposed upon such issuer for choosing not to participate in such programs.”

                If someone however, chooses not to have any health insurance at all, they will have to pay a penalty. Originally this was known as the “shared responsibility requirement” or “individual mandate.” On June 28, 2012, it was renamed by the Supreme Court as a “tax” on those who do not have health insurance.

                According to the Act, starting January 1, 2014 all individuals not covered by health insurance plan (employer-sponsored, Medicare, Medicaid, other public insurance programs or an approved private insurance policy) will be required to pay a penalty---unless he or she is a member of a recognized religious sect exempted by the Internal Revenue Service or the least expensive policy would exceed 8% of their income. The annual penalty will be $95, or up to 1% of income over the filing minimum whichever is greater and will increase to a minimum of $695 ($2,085 for families) or 2.5% of income over the filing minimum by 2016.  

             

                Near the end of her video Dr. Vecchio appears to be making some kind of dire warning about employers. Again, I’m not sure what she’s talking about, but I think it’s probably the penalty which companies with more than 50 employees will have to pay if they should decide not to offer health Insurance. The tax is $2,000 for each full-time employee. The first 30 employees however, are exempted. And, very small businesses will be able to get subsidies if they decide to purchase insurance through an exchange. Again, as for individuals, businesses are not forced to provide insurance for their employees.  But they, like individuals who don’t want health insurance, will have to pay a tax.

                Given its recent expansions, I wouldn’t be surprised if Rocky Mountain Radiologists P.C. has more than 50 employees and will be required to either offer health insurance to their employees or pay the tax if it should choose not to---putting Dr. Vecchio in a position of conflict of interest.

                Mammography screening guidelines. Dr. Vecchio claims that the Health Act makes her violate the Hippocratic Oath and that she will be jailed, fined or not paid if she abides by the Hippocratic Oath instead of the Health Act. As far as I can tell, there is nothing, not one word, in the Health Act that says anything about doctors’ being fined or jailed. I searched.

                As of September 23, 2010, all new insurance plans began covering preventive care and medical screenings rated Grade A or B by the U.S. Preventive Services Task Force.  Grade A preventive services are recommended because “there is a high certainty that the net benefit is substantial;” Grade B services are recommended because “there is a high certainty that the net benefit is moderate or there is moderate certainty that the net benefit is moderate to substantial.” (Grade C is “no recommendation” Grade D, a “recommendation against, and Grade I---no recommendation due to insufficient evidence”) Note the provision is directed to insurers, not physicians.

                The Task Force recommends biennial, not annual, screening mammograms for women age 50-74 (Grade B). And, it does not recommend any regular (biennial or annual) mammography screening for women age 40-49 (Grade C) or over the age of 74 (Grade I). However, the Task Force guidelines do permit physicians to use their discretion for preventive services that receive a lower grade.

                So, Dr. Vecchio will not be fined.  She will not be jailed. But she may not be reimbursed by insurance companies for yearly mammograms and mammograms for women in their 40s or over 74. Unless her patients are willing to pay out-of-pocket for non-recommended screening mammograms, her income could be reduced--- again placing her in a position of conflict of interest. Thus, it is not surprising that in the video she advocates for the American Cancer Society’s guidelines which recommend “yearly mammograms starting at age 40 and continuing for as long as a woman is in good health.” ⁵

                Why the different guidelines? The American Cancer Society is a non-profit organization. It has a Board of Directors and is supported by donations. It is the oldest non-profit organization in the U.S.⁶  It has been a major funder of cancer research; 46 of the cancer researchers it has supported have gone on to win the Nobel Prize.⁷ Unlike the U.S. Preventive Services Task Force however, it’s not a group of scientists and physicians specializing in preventive care. Nonetheless, it has played an important part in the history of cancer prevention in the U.S. and worldwide.⁸

                         After finding evidence of a relationship between tobacco smoking and cancer in the late 1940s, it battled the cigarette companies and took upon itself the fight to reduce cigarette smoking in the U.S.  And since the 1950s, the Society has been instrumental in persuading women to have pap smears to prevent cervical cancer. Unfortunately, I think the overwhelming success of cervical screening may have led the American Society and many others to have unrealistically high expectations of early detection for breast cancer.

                Breast cancer is not like cervical cancer. Cervical cancer tends to be indolent (i.e., it develops very slowly) and starts as a precancerous condition (dysplasia) that happens to be 100% treatable.⁹  Since it’s indolent, it’s not that urgent it be found early. In fact, cervical screening works well even if women don’t have pap smears every year--- which is good because many women don’t.

                 In the case of breast cancers however, only some are indolent. Others are aggressive. And, by the time they’re large enough to be detected by mammography, neither indolent nor aggressive breast cancers are 100% treatable or precancerous (except for some in situe breast cancers).

                Even the American Cancer Society itself has been ambivalent about breast cancer screening. In the 1970s it urged annual mammography screening for women 35 and older.  When it learned radiation was carcinogenic and mammography could cause adverse side effects, it changed its recommendation to annual mammography screening for women 50 and older in 1980. But by the 1990s it had almost completely reverted to its previous position and is now recommending annual mammography screening for women 40 and older.

                I don’t know what’s influencing the Society’s current stance on screening mammography. One hypothesis is that it’s still overwhelmed by the success of its cervical screening drive. Another possibility is, as in the case of Dr. Vecchio, conflict of interest.

                The American Cancer Society is the richest non-profit organization in the United States.¹⁰ In 2010, its net assets totaled $1.3 trillion; its total revenue equaled $919,264,859, and it paid its chief executive officer $2,081,246.¹¹ Five of its past presidents have been radiologists and many of its decisions appear to have reflected the interests of the major manufacturers of mammogram machines and films (Siemens, DuPont, General Electric, Eastman Kodak and Piker). Members of the mammography industry have donated large sums of money, sat on American Cancer Society advisory boards and conducted research for the Society and its grantees.¹⁰

                 Furthermore, pre-menopausal women, in particular, appear to be an important target. An American Cancer Society advertisement in a leading Massachusetts newspaper featured a photograph of two women in their twenties promising that early detection will result in a cure “nearly 100 percent of the time.” In an article published by the Massachusetts Women’s Community’s journal, Cancer, an American Cancer Society communications director when responding to journalist Kate Dempsey’s question, revealed, “The ad isn’t based on a study. When you make an advertisement, you just say what you can to get women in the door. You exaggerate a point….Mammography is a lucrative [and] highly competitive business.”¹⁰ Apparently premenopausal women’s participation in routine screening contributes half of health care facilities’ annual revenue.¹⁰

                Screening effectiveness. Dr. Vecchio boasts that “just” screening mammography, by itself, decreases the numbers of deaths from breast cancer by 30-40%. Wow! I wonder what surgeons, radiation therapists, oncologists, and the pharmaceutical companies would say to that. I bet they think they’re contributing to the decrease in death rate.

                Even if screening mammography were 100% accurate, it could not, just by itself, prevent a single death. Before the advent of successful adjuvant chemotherapies and the discovery of the drug tamoxifen, so few women with breast cancer survived, it was difficult to tell if screening had any effect at all on the death rate.

                According to the report accompanying the U.S. Preventive Service Task Force’s new guidelines, there’s a 39.4% reduction in mortality for women age 40-84 when they are screened annually. But that’s versus NO screening at all. That’s not what we’re talking about here. What’s important here is the difference in the reduction of mortality between women who are screened annually (the American Cancer Society guidelines) versus those who are screened biennially (the U.S. Preventive Services Task Force Guidelines).

                 According to the Task Force’s report, there’s a 31.8% reduction in mortality for women age 40-84 when they are screened biennially. The difference between the two screening strategies is a 7.8% reduction in mortality. Given that 3% of women who are not screened die of breast cancer, it means that 2.34 fewer women per 1000 will die of breast cancer if they’re screened annually rather than biennially.

                 The costs of the additional 17,842 mammograms needed for annual screening are: 1,398 false positives; 1,198 women undergoing unnecessary additional imaging; and 86 women having unnecessary biopsies. The costs of the additional exposure to ionizing radiation are more difficult to assess.  Experts don’t agree on how to measure the effect of mammography radiation on breast tissue.

                I’m confident of only three things about the danger of mammography screening itself leading to the development of breast cancer.  The first is that annual rather than biennial screening doubles the risk of ionizing radiation leading to the development of breast cancer. The second that, specifically for the case of women age 40-84, the probability of one mammogram leading to breast cancer must be very small, less than 0.01%. If it’s equal to or greater than that, annual mammography could potentially lead to more breast cancers than the number of additional lives it saves. And the third is that the probability of mammography leading to breast cancer is higher for premenopausal women than postmenopausal women. Experts do agree that the premenopausal female breast is one of the most radiosensitive organs in the body

                Threats.  At the beginning and the end of her video Dr. Vecchio suggests that if President Obama is re-elected and the Health Act not overturned, hundreds of thousands (possibly 800,000) physicians will close up shop and leave us all in the lurch because they, like she, will be forced by the Health Act to violate the Hippocratic Oath.

                Will we be abandoned by our doctors if the Health Care Act remains the law of the land? Probably we will be by some, but probably not by all 800,000. Their past track record hasn’t been that great though.

                 In 1937, President Roosevelt signed the National Cancer Institute Act. It established a National Advisory Council. Four of its six members were American Cancer Society Directors. That year, many doctors, worried that the Society’s alliance with the government might lead to socialized medicine, stopped donating to the Society.⁸

                 In 1944, the California Medical Association hired Whitaker and Baxter, founders of Campaigns Inc., the first political consulting company in the world.  H.R. Haldeman, the person who ran Nixon’s presidential campaign, learned the tools of his trade from Whitaker and Baxter. The Association paid Campaigns Inc. $45,000 a year to scuttle Governor Earl Warren’s proposal for a comprehensive, compulsory health insurance plan in California.¹²

                The following year, the American Medical Association paid Whitaker and Baxter $100,000 a year to fight President Truman’s health care plan for the country’s children. The Association assessed each of its members $25.00 a year to raise the money. ¹²

                To their credit, a number of doctors resigned. Dr. James Means, Professor of Medicine at Harvard and Chief of Medicine at Massachusetts General Hospital, wrote that he was no longer willing to support something “contrary to public welfare and unworthy of a learned profession.” That fall, the Association let Baxter and Whitaker go.¹²

                I don’t know for sure, but I doubt that that many physicians will give up their profession if President Obama wins the coming election and the Health Act remains the law of the land. I even doubt that Dr. Vecchio will. If some do though, I believe, in the long run, we will all be much better off without them than without the Health Act.

                Why 750,000+ hits? William Gavin, another Nixon political advisor, once wrote, “Voters are basically lazy, basically uninterested in making an effort to understand what we’re talking about. Reason requires a higher degree of discipline, of concentration; impression is easier. Reason pushes the viewer back, it assaults him, it demands that he agree or disagree. Impressions can envelop him, invite him in, without making an intellectual demand …. When we argue with him, we demand that he make the effort of replying. We seek to engage his intellect, and for most people this is the most difficult work of all. The emotions are more easily roused, closer to the surface, more malleable.”¹² That may explain the 750,000+ hits.

                The Hippocratic Oath¹³  Since the Health Care Act does not force doctors to do anything; it cannot make them violate the Hippocratic Oath. If a doctor advises a patient to have a treatment that is not covered by insurance and the patient wants that treatment and is willing to pay for it, there is no problem. No one will be fined. No one will be jailed. The doctor will be paid. And the Hippocratic Oath will not be violated.

                The Oath, on the other hand, does constrain doctors. It includes a promise “to abstain from doing harm.” That means that radiologists who, like Dr. Vecchio, specialize in screening mammography, must take into account screening’s potential harms for pre-menopausal women.

                Even I, who was less than enthralled by the U.S. Preventive Services Task Force research and guidelines, found its research and conclusions regarding women in their 40s convincing. The data show that too many women in their 40s have to be screened to detect one cancer---556 versus an average of 198 mammograms for women 50-89 years old---and too many undergo additional imaging; 47 versus an average of 14 for women 50-89 years old. And, apparently pre- and post-menopausal breasts are so different, premenopausal screenings are even useless for baseline comparisons.

Conclusion

                It seems clear to me that by not recommending regular mammograms for women age 40-49, the U.S. Preventative Services Task Force guidelines are protecting the health of premenopausal women and, by using the Task Force’s guidelines, the Affordable Health Care Act is doing a better job of preventing harm and upholding the Hippocratic Oath than Dr. Vecchio appears to be able or willing to do.

References        

¹ http://www.youtube.com/watch?v=6e3udzHIiVs

² http://www.rockymountainradiologists.com/

³ http://www.rockymountainradiologists.com/index.php?s=69

⁴ http://www.rockymountainradiologists.com/index.php?s=114&t=1&f=4

⁵ http://www.cancer.org/Healthy/FindCancerEarly/CancerScreeningGuidelines/american-cancer-society-guidelines-for-the-early-detection-of-cancer

⁶ http://www.cancer.org/acs/groups/content/@nho/documents/document/timelineofaccomplishmentspdf.pdf

⁷ http://www.cancer.org/Research/ResearchAccomplishments/nobel-prize-winner

⁸ http://www.fundinguniverse.com/company-histories/the-american-cancer-society-history/

⁹ http://www.ncbi.nlm.nih.gov/pubmedhealth/n/pmh_adam/A001491/

¹⁰ http://www.preventcancer.com/losing/acs/wealthiest_links.htm

¹¹ http://www.charitynavigator.org/index.cfm?bay=search.reviews&orgid=6495

¹² Lepore, Jill, (9/24/12). The Lie Factory, The New Yorker, pp. 50-59.

¹³ http://en.wikipedia.org/wiki/Hippocratic_Oath

Task Force Recommendations: Screening and Age

                In 2002 when the Task Force treated women over the age of 39 as a homogeneous group, it recommended all women 40 years and older be screened every one to two years.

               In 2009 when it reviewed screening for women of different ages, it recommended women age 50-74 be screened biennially rather than annually, advised against routine screening for women age 40-49, and because it felt the data were scanty, made no recommendation for women 75 and older.

                  The public backlash to the new recommendations was fierce and immediate.  In response, the Task Force changed one--- its recommendation against routine screening of women age 40-49. The revised recommendation reads: “The decision to start regular, biennial screening mammography before the age of 50 years should be an individual one and take patient context into account, including the patient’s values regarding specific benefits and harms.”  As explanation, the Task Force added the following footnote to its website: “On December 4 2009, the USPSTF unanimously voted to update the language of their recommendation regarding women less than 50 years of age to clarify their original and continued intention.”

                I reviewed the Task Force’s research.  I agree with some, not all, of the recommendations.

                I chose to focus on three sections of the Task Force’s research: (1) the data obtained from the Breast Cancer Surveillance Consortium, (2) the predictions by six models of reduction-in-mortality rates for twenty different screening strategies, and (3) the results of the decision analysis used to decide between routine annual and biennial screening. I think the three provide enough information to understand how the Task Force arrived at its recommendations.

The Breast Cancer Surveillance Consortium Data

                The Consortium is part of the National Cancer Institute.  It consists of a network of seven mammography registries linked to tumor and pathology registries and a central Statistical Coordinating Center. The Consortium supplied the Task Force with information for 600,830 women age 40 years and older who had at least one screening mammogram every two years between 2000 and 2005. If a woman had two or more mammograms during that period, one was randomly selected.

                 The Consortium data in the first table below provide information about screening mammography for the following five age groups: 40-49, 50-59, 60-69, 70-79, and 80-89 years. The table is like a composite photograph of screening mammography for women of different ages.

                 The top third of the table contains the rates (per 1000 screening mammograms) for invasive breast cancer (cancer that’s moved outside a duct), DCIS (cancer that’s fully enclosed by duct), and the number of false-positives and false-negatives. The middle third contains the number of patients (per 1000 screening mammograms) undergoing: (1) mammography to diagnose one case of invasive breast, (2) additional imaging to diagnose one case of invasive breast cancer and (3) biopsy to diagnose one case of invasive breast cancer. As you read across the rows, you can see how the numbers change as the groups get older. 

                The bottom third of the table contains the results of calculations I made for (1) the number of true positives (the number of screen-detected DCIS plus the number of invasive breast cancers), (2) the number of true negatives (1000 minus the sum of the true positives, false positives and false negatives), (3) the sensitivity, (4) the specificity and (5) the positive predictive value (PPV) of screening mammography for each of the age groups. (In case you’ve forgotten, true positives occur when radiologists detect breast cancer in women who have it and false positives when the women don’t. True negatives occur when radiologists don’t detect breast in women who don’t have it and false negatives when the women do.)

                Sensitivity and specificity are the most popular measures of the effectiveness of screening.  Sensitivity is equal to the number of true-positives divided by the sum of the number of true positives and false negatives. It’s a measure of how well a method detects all those who have a disease.

                 Specificity is equal to the number of true negatives divided by the sum of the number of true negatives and false positives. It’s a measure of how well a method detects all those who don’t have a disease. According to the Task Force report, the sensitivity of screening mammography generally ranges from 77% to 95% and the specificity from 94% to 97%. The sensitivity and specificity for the Consortium sample of women are somewhat lower. 

                 Positive predictive value (PPV) is equal to the number of true positives divided by the sum of true and false positives. It’s a measure of how well a method detects only those who have a disease and reveals how likely radiologists’ suspicions of breast cancer will be true or false.

                 For the Consortium sample, positive predictive value ranges from 2.6% to 12.5%. In other words, 87.5% to 97.4% of positive screenings turned out to be false alarms.  Mammography screening is not nearly as impressive looking when measured by positive predictive value. It’s unfortunate that it’s reported so rarely. If women knew how often radiologists’ suspicions of breast cancer are false positives, they might feel a lot less anxious when asked to come back for additional imaging and/or biopsies.

                                                                                                 Age Group 
Screening Result                                            40-49     50-59     60-69     70-79    80-89

False negatives                                                   1.0          1.1         1.4          1.5        1.4

False positives                                                  97.8        86.6       79.0        68.8      59.4

Additional imaging                                          84.3        75.9       70.2        64.0     56.3

Biopsy                                                                 9.3        10.8        11.6        12.2      10.5

Screen-detected invasive cancer                        1.8          3.4         5.0          6.5       7.0

Screen-detected DCIS                                        0.8           1.3         1.5          1.4        1.5

# Patients undergoing mammography            556         294        200         154       143

       to diagnose one case invasive cancer

# Patients undergoing additional imaging         47           22           14           10           8

        to diagnose one case invasive cancer

# Patients undergoing biopsy                                5             3             2             2        1.5

        to diagnose one case invasive cancer

True positives                                                      2.6           4.7          6.5          7.9        8.5

True negatives                                                 898.5        907.6      913.1      921.8    930.7

Sensitivity                                                           72%          81%        83%        84%      86%

Specificity                                                           90%          91%        92%        93%      94%

PPV                                                                    2.6%         5.1%       7.6%     10.3%    12.5% 

                The data in the table show that the sensitivity and number of true positives for 40-49 year-old women are too low relative to those in the next older age group ( 50-59 year-old women). In addition, the numbers of patients undergoing mammography and additional imaging to diagnose one invasive breast cancer for women in their 40s are almost twice as high than for women in their 50s. The differences between the two adjacent age groups suggest a discontinuity from one developmental stage to another, analogous to leaving childhood and entering adolescence.  The changes between the two groups do not resemble the smaller, more continuous-looking changes between the four older age groups.

                The average age of menopause for U.S. women is 51 years. Most women in their 40s are premenopausal. Pre- and post-menopausal breasts differ. Premenopausal breast tissue tends to be dense. It may resemble and/or obscure breast cancer on a mammogram. Tissue that appears to be breast cancer or may be hiding breast cancers will invariably lead to too many false positives, additional images, and biopsies. The Consortium data indicate screening mammography is less effective and potentially more harmful for premenopausal women.

                In contrast, the data indicate that screening mammography is increasingly more effective for postmenopausal women as they age.  The numbers of false positives, additional imagining, the numbers of patients undergoing mammography /additional imaging/biopsy to detect one invasive cancer, sensitivity, specificity and positive predictive value all improve. The potential benefit of mammography screening, in fact, appears to be quite good for women in their 70s and 80s.

                The Consortium data don’t link screening outcomes to treatment.  We don’t know how women detected with breast cancer fared during or after treatment. The six models, in contrast, do attempt to link screening and treatment.

The Six Models 

                 Models are used to make predictions. They use available data. And, they make assumptions about the data. The reality their predictions depict is less like a photograph and more like a cubist painting.

 

                Generally speaking, models are tested against reality. We know how accurate their predictions are and how much we can rely on them. The models with which we have the most experience are probably those that forecast the weather.

                In previous collaborations, the six models estimated how much treatment or screening each contributed to decreases in breast cancer mortality rate. According to the Task Force, their “qualitative estimates” were “similar.” That’s not saying much. It means their predictions lined up in the same order from high to low, but the absolute values of their predictions didn’t match. It’s like having a weather forecast that can reliably tell you it’s going to be warmer tomorrow, but not what the temperature will be.

                 Each model was developed at a different cancer center: Dana-Farber Cancer Institute, Boston; Erasmus Medical Center, Rotterdam; Georgetown University, Washington, D.C./Albert Einstein College of Medicine, Bronx; M.D. Anderson Cancer Center, Huston; Stanford University, Palo Alto; and the University of Wisconsin, Madison/Harvard, Boston.  Their task was to predict the percentage of reduction in breast cancer mortality associated with screening vs. no screening for twenty screening strategies (ten annual and ten biennial) beginning and ending at different ages (40-69 years, 40-79 years, 40-84 years, 45-69 years, 50-69 years, 50-74 years, 50-79 years, 50-84 years, 55-69 years, and 60-69 years).

                The models compared the probability of unscreened women dying of breast cancer to the probability of screened women dying of breast cancer during their lifetime. To estimate the probability of unscreened women dying of breast cancer from age 40 to death, the models used data gathered from a cohort of women born in 1960 being followed from the age of 25 until their death. Estimates of the future incidence of breast cancer were extrapolated forward using breast cancer incidence data available in 2000. Using the data and extrapolations, the models estimated 3% of unscreened women will die of breast cancer.

                Thus, if a model predicts 2.7% of screened women will die of breast cancer, the probability of dying is 0.3% less than 3% and equivalent to a 10% reduction in mortality rate. A 0.3% reduction in deaths (or 10% reduction in mortality rate) is equal to about three fewer women dying of breast cancer per 1000 women screened.

                I averaged the reduction-of-mortality rate across the six models for each of the twenty screening strategies and arranged them from highest to lowest reduction in mortality rate in the following table.  Without exception the reduction in mortality rate is higher for each annual screening strategy than its corresponding biennial screening strategy.

Age          Screening Interval   Reduction Mortality Rate  # Mammograms  Efficiency Rating                                                                                               

                                                                                          

40-84            Annual                            39.5                               36,550                   E (8^th)

    “                Biennial                           31.8                                18,708                   E (7^th)

40-79            Annual                            36.8                                34,078                      b

    “                Biennial                           29.2                                17,241                       b

50-84           Annual                             35.0                                26,905                       b

    “               Biennial                            28.5                                13,837                    E (6^th)

50-79           Annual                             32.7                                24,419                        b

    “               Biennial                            26.2                                12,366                     E (5^th)

50-74           Annual                             28.7                                21,330                         i

    “                Biennial                           23.2                                11,066                     E (4^th)

40-69           Annual                              28.5                                27,428*                      i

    “               Biennial                             21.7                               13, 831*                       i

45-69            Annual                             26.8                                22,546*                      i

    “                Biennial                            21.2                                 11,694*                      i

50-69            Annual                             23.8                                 17,737                        i

    “                Biennial                            18.3                                  8,947                    E (3^rd)

55-69            Annual                             19.5                                13,009                        i

    “                Biennial                            15.7                                  6,890                    E (2nd)

60-69            Annual                              14.3                                 8,438                        i

    “                Biennial                             11.0                                 4,263                    E (1^st)

Mean            Annual                               29.0                               23,244

    “               Biennial                              22.7                               10,884            ________

               

                The models estimate annual screening will reduce mortality rate by an average of 29% and biennial screening, by 22.7%. For annual mammography that translates into a 2.1% probability of dying from breast cancer (about 9 fewer deaths) and biennial mammography a 2.3% probability of dying from breast cancer (about 7 fewer deaths).  Thus, annual screening would result in about two fewer deaths per 1000 women screened than biennial screening. In terms of number of deaths averted (ignoring the harms of screening), the benefit of biennially screening is about 77% of the benefit of annual screening. (Using slightly different figures, the Task Force found “screening biennially maintained an average of 81% of the benefit of annual screening.”)

                I don’t trust the screening strategies save as many lives as the models predict given that the average number of true positives in the Consortium data is 5.6 detected per 1000 women for one screening round or 11.2 detected per 1000 women per two screening rounds. Biennial screening can’t possibly save more lives (7) than the number breast cancers detected (5.6). And, although it’s not impossible, it’s highly unlikely that annual screening saves 9 of the 11.2 breast cancers detected.

                I am more inclined however, to trust that annual screening saves about two more lives than biennial screening.  A major advantage of modeling is that one is able to select certain conditions, hold them constant and apply them to different possibilities. That means exactly the same data and assumptions were applied to each annual screening strategy and its corresponding biennial strategy. Given they were perfectly matched, it’s highly likely the rate of mortality is higher for annual screening and probably averts two more deaths than biennial screening.

                In an earlier post I wrote that I believed early detection didn’t save lives.  One reason is that I’ve always worried about how many non-life-threatening cancers and non-existent cancers (biopsy errors) contributed to the number of lives “saved by screening.” The result that under identical conditions annual screening saves more lives than biennial screening indicates that more frequent screening and by implication, early detection, might save lives.

                Two models (Erasmus Medical Center and the University of Wisconsin) explicating assumed there would be cases of DCIS that would not be life-threatening and the University of Wisconsin model assumed, in addition, some small invasive cancers would not be life-threatening.  The Erasmus model’s predictions indicate annual screening would save an additional two lives and the University of Wisconsin model’s predictions, an additional three lives, again indicating that screening more frequently would save lives and implying that early detection could save lives, even when non-life-threatening breast cancers are removed from the data.

                This is the first research I’ve seen that directly addresses some of my doubts and I’m beginning to believe that early detection might, in fact, save lives. However, the only model (M.D. Anderson) that explicitly assumed a better prognosis for screening-detected than for clinically-detected early-stage breast cancers predicted the lowest average reduction-in-mortality rates (20.5 for annual and 21.7 for biennial screening strategies) ---lower than the overall averages for both annual and biennial screening strategies.

The Decision Analysis  

                The Task Force rated the screening strategies’ effectiveness on two dimensions simultaneously: (1) number of mammography screenings they required (a measure of human and financial cost) and (2) reduction in mortality rate (a measure of benefit).  To do this, it borrowed and adapted a decision analysis from economics.

                 A screening strategy was “efficient” if it had a higher reduction in mortality rate and required fewer mammograms than another.  It was “inefficient” (“dominated” in economics lingo) if it either had a lower reduction in mortality rate or required more mammograms.

                 The strategies were classified into three categories: (1) if a strategy was dominated by other strategies in five of the six models, it was “inefficient;” (2) if was never dominated, it was “efficient” and (3) in all other cases, it was “borderline.” The Task Force’s categorizations---efficient (E), borderline (b) and inefficient (i) ----for each of the twenty screening strategies are listed in the rightmost column of the table above.

                Seven of the eight “efficient” screening strategies turned out to be biennial and six of the eight initiated screening with women their 50s.  These two results contributed to the Task Force’s recommendations for biennial screening for women 50- to 74-years-old and against routine screening for women in their 40s.

                 The large differences between the number of screenings required and the small differences in reductions of rate of mortality between screening strategies make it difficult to see if one of the two dimensions (number of mammograms and reduction in mortality rate) trumped the other.

                I’ve included in the rightmost column of the table above the order in which the “efficient” strategies were listed in the Task Force’s table from top (1^st) to bottom (8^th). The order from 1^st to 8^th is in exact reverse order to reduction-in-mortality rate and in perfect corresponding order with number of mammograms.

           

                I also calculated two correlation coefficients, one between the rank, from 1 to 20, of each of the twenty strategies with its reduction-of-mortality rate and the other with number of mammograms each strategy required. The correlation (0.22) with predicted reduction in mortality  was too low to be significant, indicating no association the strategies’ rankings and their predicted reduction in mortality.  The second correlation (0.43) with number of mammograms, was significant, indicating a positive association between the strategies’ rankings and the number of mammograms they required.

                It  appears the decision analysis as adapted by the Task Force did, in fact, favor the harms of screening (as measured by the number of mammograms required) over the benefits of screening (as measured by the reduction in rate of mortality).  That’s not good, but neither is it necessarily that bad.

                A woman who is recalled for additional screening and learns she doesn’t have breast cancer may experience several days of additional anxiety.  A woman recalled for biopsy may experience greater anxiety for a longer period of time, pain and/or disfigurement. A woman whose screening culminates in a true positive who doesn’t have breast cancer (a biopsy error) or whose breast cancer will never be life-threatening may experience life-long anxiety, life-long discomfort of lymphedema caused in an arm by auxiliary lymph node extraction, recurring pain due to the severing of nerves during lumpectomies or mastectomies and many other side effects of treatment---all for no benefit whatsoever.

                If we could assign weights to the harms, our estimates of screening’s harms would be better. But we can’t. The data don’t exist. And, since there’s no way to identify either those women whose biopsy results were wrong or those whose cancers will never become life-threatening, they will always appear to have benefited the most from screening, when in fact they are the most grievously harmed.

                 Unfortunately, number of mammograms is the only estimate of harm we have. We know the less often a woman is screened, the less she’s likely to be harmed. And, depending upon how one would weigh the possible harms if one could, a bias in favor of number of mammograms could be wrong---or right.

                The Task Force’s recommendation against routine screening for women aged 40-49 is not biased. Neither is its recommendation for women 74 years-old and older, although, I think, given the Consortium data, it may be too conservative.

                If you follow the columns listing the number of mammograms and the reduction in rate of mortality from the top row down of the table above, you can see that the number of mammograms required for the screening strategies consistently decrease in order with the decreases in reduction of mortality rate until you reach the “40-69 years annual and biennial screening strategies” and  ”45-69 years annual and biennial screening strategies.”  The number of mammograms required for these strategies are out of line; they’re too high (see asterisks in the fourth column of the table above).

                That’s not true however, when the screening strategy groups women in their 40s with women in their 70s and 80s (See the four top rows of the table.)  It appears the benefits of screening for women over 70 may compensate for the extra mammograms needed for women in their 40s.

                I compared the predicted reductions-in-mortality rate for the four screening strategies initiating screening beginning with women in their 40s and ending with women in their 70s and 80s to those beginning with women in their 50s (e.g., annual screening of 40-84 year-olds vs. annual screening of 50-84 year-old women, etc.). When 40-year-old women are included a strategy, the probability of dying from breast is 2.9% (about one fewer death per 1000 women screened).  (Using a different analysis of the data, the Task Force concluded that “greater mortality reductions could be achieved by stopping at an older age than by initiating screening at an earlier age.”) 

                In general, the models’ predictions for women in their 40s, 70s and 80s confirm what the Consortium data suggest for women in these age groups--- screening appears to be better for women in their 70s and 80s and worse for those in their 40s. The results indicate the models do, to some extent, accurately reflect the different realities for women in their 40s, 70s, and 80s with breast cancer. 

     

                Breast cancers diagnosed in 40-year-old women are more likely to be aggressive; the cells of their breast cancers are more likely to divide and proliferate more quickly; and, the women are more likely to die of their breast cancer no matter how soon their breast cancers are detected or treated. In contrast, breast cancers diagnosed in older women are more likely to be indolent; the cells of their breast cancers more likely to divide and proliferate more slowly; and the older the woman, the more likely her breast cancer will be indolent and her treatment successful.

                The models made many assumptions about treatment.  I’m going to discuss the two assumptions I know something about: (1) that premenopausal women with hormone-receptor-positive breast cancers would be treated with tamoxifen and postmenopausal women with hormone-receptor-positive breast cancers treated with an aromatase inhibitor and (2) that patients would be 100% compliant with these treatments.

                Tamoxifen and aromatase inhibitors interfere with the growth and spread of breast cancer; tamoxifen by attaching itself to estrogen-receptor-positive breast cancer cells and acting as a barrier between the cells and estrogen; and aromatase inhibitors by stopping the action of aromatase, an enzyme needed to manufacture estrogen. Since most of the estrogen in premenopausal women is produced directly by their ovaries and is not dependent upon the enzyme, aromatase inhibitors can only interfere with the production of estrogen elsewhere, e.g. in women’s adrenal glands or bones. 

                The Food and Drug Administration approved aromatase inhibitors for postmenopausal women, but many doctors prescribe them “off-label” for premenopausal women.  That means the women must either have their ovaries removed or take another potent drug to eliminate the estrogen being produced by their ovaries.

                They become postmenopausal in a matter of weeks. Their hair thins. Their skin thins and dries out, often making sex painful and unpleasant.  Some lose bone mass, a serious problem for women as young as 40. And many suffer from bone, muscle and/or joint pain. Some take the drug irregularly to deal with the side effects. Others stop completely.  

                The results of trials comparing tamoxifen to aromatase inhibitors show that aromatase inhibitors benefit some women by allowing them to live longer before their breast cancer recurs, but it doesn’t prolong their lives overall.

                Neither of the models’ assumptions about the treatment of premenopausal women with hormone-receptive breast cancer is realistic. Many premenopausal women are not treated with tamoxifen and neither the women nor their doctors are 100% compliant. Unrealistic assumptions about treatment undermine the reliability of the models’ absolute predictions of the reduction in rate of mortality. In this case, they may have contributed to their being too high.

                That said, I appreciate the model builders’ taking treatment into account; very little data exists linking screening and treatment.  It’s as if an impenetrable door exists between the two.  For example, the Consortium data don’t follow up women who’ve been diagnosed with breast cancer. And, trials evaluating treatment don’t report if participants have been screened. In neither case do we know how screened patients fared. Assumptions made by models may be better than nothing. Actual data would be a lot better.

Rationing of Health Care 

                I think the Task Force’s biggest mistake was failing to adequately communicate the results of its research before announcing its new recommendations. That failure pretty much guaranteed its recommendations would be perceived by many as a crude attempt to ration health care.  And, its subsequent retraction of the recommendation for women in their 40s probably reinforced that perception.

                Although rationing screening would immediately ration treatment, not much, if any, money would be saved. Everyone with a cancer eventually shows up in a doctor’s office, a clinic or a hospital complaining of symptoms and needing treatment.  It anything is rationed, it seems more reasonable, I think, to ration treatment directly.

                 Compared to the cost of treatment, the cost of screening is insignificant, insignificant enough that one hospital is willing to provide prostate screening for free.  An article about Dr. Otis Brawley, medical director of the American Cancer Society, published in USA Today last January, related that the hospital’s marketing  executive voluntarily told Dr. Brawley about how his (the marketing executive’s) hospital was providing “’free’ prostate screenings as a way to find patients for more lucrative radiation treatments, cancer surgeries, even incontinence therapy and impotence drugs.”

                Finally, based on what I know: (1) if I were 40 and/or premenopausal, I wouldn’t be screened (In fact, I can hardly believe the Task Force retracted the one recommendation for which it had the best evidence.) ; (2) if I were in my 70s or 80s, taking into account my age and how likely my breast cancer would be indolent, I would be screened maybe every 2 to 3 years and would make sure I was treated with the least aggressive treatment; and (3) if I were between 50 and 70 years old, I would consider being screened biennially in my 50s and annually in my 60s.

                That’s based on what I know, but it's not enough. I would like to know more. For instance I would like to know how many DCIS or invasive breast cancers are not life-threatening and when they’re likely to occur. That would mean we would have to know enough about breast cancers to identify those that are not-life-threatening.  Unfortunately, I think the path which much of breast cancer research appears to be on is not likely to lead to that information.

                My next post will be about how the marketing of medicine cultivates our ignorance, takes advantage of our trust and misdirects cancer research.

p.s. I learned about aromatase inhibitors when I volunteered to help analyze the data of a study on their side effects. Two reports were published online by Breast Cancer Action, a non-profit advocacy group.  If you’re interested, they can be found at http://bcaction.org/wp-content/uploads/2011/11/bca_ai_report_jan_23-indd.pdf and http://archive.bcaction.org/uploads/PDF/AIReport.pdf.

Computer-aided-detection & Ionizing Radiation

Computer-aided-detection

                Reading screening mammograms is difficult. Just two to six cases of breast cancer are typically detected per thousand mammograms.  Radiologists compare the task to “looking for a needle in a haystack.”

                Radiologists would rather not make mistakes, but if they do, it seems they prefer making false positives to false negatives; they would rather erroneously decide a woman might have breast cancer than miss a breast cancer.  I can think of two possible reasons for this.

                One, they’re more likely to be sued for false negatives than false positives.  Missed or late diagnoses of breast cancer are the leading cause of radiology malpractice lawsuits in the U.S.

                Two, there seems to be a general bias in medicine to avoid misses.   For example, the common wisdom amongst surgeons seems to be that if they haven’t operated a certain number times for a non-existent appendicitis, they’re not diagnosing appendicitis often enough--- a reasonable strategy since missing an appendicitis can be immediately catastrophic.  Patients could die, not in months or years, but in the next few days if not sooner. Plus, the patients are sick, not well.  They are usually in lots of pain.  Although avoiding misses is a good strategy for imminent catastrophe and ill patients, it may not be in other cases.

                Radiologists have strategies for avoiding mistakes.  In clinics and departments that have a number of radiologists, the more accurate mammography readers will be the ones who screen mammograms. If previous mammograms are available, radiologists will use them to check for changes. And, in some places in the U.S., mammograms are read independently by two radiologists. If their readings differ, no decision is made until they agree.  Of all the strategies, double-reading is the most accurate.

 

                Computer-aided detection (CAD) was developed about eight years ago to improve the accuracy of a single radiologist.  And, it does.  When using CAD the accuracy of a lone radiologist almost equals that of double-reading.  Its boost in accuracy however, is achieved primarily by reducing the number of false negatives. It was designed to “avoid false negatives without unduly increasing the number of false positives.”

                CAD searches for suspicious- looking regions on mammograms, marking possible masses and micro-calcifications. It generates an average of one false mark per mammogram.  That’s a lot considering that between 994 and 998 out of 1000 mammograms are likely to be normal. The radiologist considers each mark and accepts or rejects it. Given the bias against missing something, it’s more likely false CAD marks will be accepted, adding to the number of false positives.

                And, there’s a specific protocol. First radiologists interpret a mammogram without CAD. They then review the same mammogram after it’s been marked by CAD.  At this point they may change their interpretation---but not if it’s a false positive.  If a radiologist initially suspected an abnormality and decided to recall a patient for further tests, the patient is recalled even if CAD didn’t mark anything. The protocol makes an increase in false positives almost impossible to avoid.

                Finally, CAD is better at detecting micro-calcifications than masses.  It finds very small abnormalities that may never lead to breast cancer or if biopsied, contain so few cells pathologists are unable to analyze them appropriately.

 

                Recent research reported CAD significantly increased the number of false positives. Its greater ability to avoid missing a breast cancer does not benefit well women.

                If you decide to be screened regularly, you can reduce your risk of being a false negative or a false positive by looking for radiology departments and clinics where the better mammography readers review screening mammograms or, even better, where screening mammograms are double-read.  If neither is available you can ask for a second opinion---preferably from a radiologist at another facility. It might also be a good idea to get second opinions for any biopsies---again preferably from a pathologist at another facility.

                 When radiologists are unsure they will call women back in three or six months for repeat mammograms. There’s no reason you can’t request that yourself.  If it appears that you may have DCIS or LCIS or a miniscule micro-calcification, you might suggest waiting to see if any changes occur before agreeing to a biopsy.  And, if possible, be sure to be screened at the same facility every year. Your risk of being a false positive is cut in half when radiologists have past mammograms for comparison.

Ionizing Radiation

                Screening presents a risk in addition to the risks due to radiologists’ errors.  It’s ionizing radiation, a known carcinogen. 

                I would like you to imagine being in the following experiment.  Your ears are plugged so that you can’t hear; your eyes are covered so that you can’t see. And, at a random time during the day you’re going to run across a highway. The highway has two lanes and little traffic. You avoid getting hit and try again the next day.  Again you’re not hit and think you might be able to run blind and deaf across the highway every day for a month without being hit.  If imagining this is making you begin to feel uncomfortable and sense the danger is getting too great, you’re right.  The risk is thirty times as large.

                The same logic applies to the risk of getting breast cancer from ionizing radiation.  The risk of developing breast cancer from one mammogram is small, but the risk of developing breast cancer from 25 mammograms (the number a woman would have if she had an annual mammogram between the ages of 50 and 74) is 25 times as large.  It’s not that the ionizing radiation is building up in your breast, but that each time you have a mammogram there’s a small risk cells will be damaged and become malignant.  Since each time you have a mammogram that risk is repeated, being screened every other year (biennially) rather than annually will cut your risk in half. But what is the risk?  Maybe it’s so small, you won’t care.

                The dose of ionizing radiation from one mammogram may be as low as 0.30 or as high as 0.42 cGy (centigray).  If a young woman has 10 mammograms and if the dose is 0.30 cGy, her total dose would equal about 3 cGy (10 x 0.3) and could increase her risk of getting breast cancer by 1.2% (Cornell University’s Program on Breast Cancer and Environmental Risks Fact Sheet #52, 2005). Keeping in mind that the older a woman gets the less susceptible her breast tissue is to ionizing radiation, if she has 25 mammograms, her risk increases by about 3%.  That means three additional women out of a hundred over their lifetime will get breast cancer if they’re screened annually. But, if she’s screened biennially her risk would increase by 1.5%.  Between one or two additional women out of a hundred over their lifetime will get breast cancer if they’re screened every other year.

                Depending upon how you feel about taking those increased risks, you may decide to be screened annually, biennially, or not at all.  In 2002, the U.S. Preventive Services Task Force found an increased risk of 3% acceptable; it no longer was in 2009.  But, an increased risk of 1.5% was.  However, sometimes an increased risk as small as 0.1% is said to be unacceptable.

                One out of a thousand women (0.1%) will get endometrial cancer during their lifetime. If they take tamoxifen for a year, their risk is increased by 0.1% - two out of a thousand (0.2%) will get endometrial cancer. Tamoxifen and aromatase inhibitors (AIs) are two different types of anti-estrogen drugs. They’re often compared. AIs don’t increase one’s risk of developing endometrial cancer, but they have other side effects, one of which is significant bone loss.  One study recently reported a 6.1% decline in bone mineral density in women taking one of the AIs vs.1.8% in women taking a placebo. Women are often warned tamoxifen doubles their risk of developing endometrial cancer, but they’re not told how small the risk is. If they knew, some might choose the 0.1% increased risk of getting endometrial cancer over the bone loss, especially if they had an idea of how painful and crippling osteoporosis can be.

                Be wary. Don’t be satisfied with simply being told a dose is small or a risk is some number of times as great. You have to know the size of the risk and how often you’re going to be exposed to it to make an informed decision.

Next post: Dissecting the Task Force’s recommendations

Breast Cancers, Radiologists and Pathologists

Breast cancer screening is an ongoing experiment in which hundreds of thousands of women, perhaps thousands of radiologists and hundreds of pathologists have participated for about forty years.  Its hypothesis is:  early detection will improve outcomes.  Screening is continually being evaluated because it’s difficult to assess whether outcomes have actually improved and, if they have, whether the improvements are due to early detection.

                Screening does not prevent breast cancer.  In fact mammography increases the risk of getting breast cancer.  Plus, since there is no cure for breast cancer and it can always recur, screening does not save lives. I think the original hope was that early detection itself would be the cure. I think the hope persists. And, I think it’s one of the reasons why so many asymptomatic women decide to be screened year after year. Breast cancer screening is more complicated however, than one would hope.

                First, not all breast cancers are life-threatening. There are some that are so slow-growing that women live out their lives never knowing they had breast cancer. Some types of ductal carcinoma in situ (DCIS) and lobular carcinoma in situ (LCIS) will never progress at all. DCIS and LCIS are usually confined, either to a duct or a lobule, and are less than one centimeter in diameter when detected. They may or may not be life-threatening.  However, since there is currently no way to tell which of the DCIS and LCIS cancers will grow and metastasize and no way to distinguish between very slow-growing and faster growing cancers, they’re all treated as if they were life-threatening.

                For all intents and purposes, women with non-life-threatening breast cancers are well. Detecting their breast cancer and then treating it harms them. They will always be on the alert for signs of a recurrence that will never happen.

                Second, radiologists’ skills range from eagle-eyed expertise to being so inaccurate one might as well toss a coin.  I discovered toss-a-coin radiologists when I reviewed the research on computer-aided-detection and learned that their data had been eliminated from data analyses.

                Although in practice radiologists’ decisions are more complicated, it’s sufficient to divide them into two alternatives: “yes, I see something suspicious” vs. “no, I don’t see something suspicious.”  If we do that, there are four possible outcomes: “false positives,” “false negatives,” “true positives” or “true negatives.”

                “True negatives” occur when radiologists don’t detect an abnormality and the women don’t have breast cancer. All is well. Of the four possible outcomes, only “true negatives” never cause harm.

                “False negatives” happen when radiologists don’t detect an abnormality and the women have breast cancer. Radiologists miss abnormalities when they’re obscured by other tissues in the breast or can’t be distinguished from normal tissue. “False negatives” increase fear and stress in women who discover their breast cancer was missed and who believe early detection always makes a difference.  Most people don’t know there are breast cancers that can be treated successfully no matter when they’re discovered.

                “False positives” may occur when radiologists see something suspicious in a mammogram.  Once a radiologist suspects something might be wrong, he or she may ask for additional diagnostic mammograms, callbacks in three to six months or ultrasound examinations.  If the radiologist remains suspicious, biopsies are taken and tissue specimens sent to a pathologist for microscopic examination.  Pathologists are the final judges.  When they decide specimens do not contain malignant cells, radiologists’ decisions become “false positives.”

                Although it’s always a relief to learn that one does not have breast cancer, “false positives” may be harmful.  Almost all women are anxious during the waiting period between the screening mammogram and the pathologist’s report.  Biopsies may be painful; they may be disfiguring. For some women the stress is extreme and never completely dissipates. They’re harmed.

                Third, “true positives” occur when pathologists confirm radiologists’ suspicions.  Well women are harmed when pathologists make mistakes.

                I believe the public was made aware of pathologists’ errors first in 1977. In 1972, the National Cancer Institute (NCI) launched the Breast Cancer Detection Demonstration Project.  Over 250,000 women were to be screened. In 1977, the NCI asked a pathologist to review the pathology of 506 breast lesions less than one centimeter in diameter.  He found 66 mistakes---women who had been diagnosed with breast cancer, had had mastectomies, but didn’t have breast cancer.  A great debate about the actual number ensued. The debate was never resolved.  And, the 66 women were never informed of the possible misdiagnoses.

                That was forty years ago, but apparently pathologists still make mistakes.  In a July 19^th 2010 New York Times article, Dr. Shahla Masood, the head of pathology at the University of the Florida College of Medicine (Jackson), described diagnosing DCIS  as “a 30-year history of confusion and differences of opinion”…it “occasionally comes down to the flip of a coin.” The article also reported the experience of Dr. Lagios, a pathologist at St. Mary’s Medical Center in San Francisco who reviews slides for women seeking a second opinion.  In 2007-2008 he reviewed 597 cases and found discrepancies in 141; DCIS was misdiagnosed in 27 of the cases.

                It seems that as radiologists become more and more capable of detecting smaller and smaller breast cancers, the problems for pathologists and women whose breast cancers are being detected earlier and earlier are getting worse. If that’s so and continues to be true, we can expect that more and more well women will be harmed.

                Next post: two more complications---computer-aided-detection and ionizing radiation.