Fw: THE EPIDEMIC OF UNNECESSARY MASTECTOMY: HOW NOT TO BE A VICTIM

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From: " Ilena Rose " <ilena@...>

Subject: THE EPIDEMIC OF UNNECESSARY MASTECTOMY: HOW NOT TO BE A VICTIM

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>

> THE EPIDEMIC OF UNNECESSARY MASTECTOMY:

> HOW NOT TO BE A VICTIM

> by

> Norman, Oklahoma

> Copyright 2000

> All rights reserved.

>

> We are living in the age of health scare campaigns. This is because we

> have in the U.S. a massive profit-oriented industry involving doctors,

> hospitals, HMOs, clinics, laboratories, biotechnology companies,

> researchers, and laboratories. All of these enterprises are nourished by

> health scares.

>

> For years, one of the common money-makers for surgery done to women was

> hysterectomy. Unfortunately for the promoters of this type of mutilation,

> the excessive enthusiasm among doctors for it has come to be exposed. For

> example, it was reported by the Journal of the American Medical

> Association (May 12, 1993) that only 58% of a group of 642 hysterectomy

> cases could be justified as appropriate. It has become expedient for

> medical profiteers to develop new markets, and mastectomy has been

> emerging as the current favored gold mine.

>

> A study reported by Reuters (11/28/00) found that 53% of the mastectomies

> done on a group of 142 women were unnecessary. This group could have been

> effectively treated with lumpectomy, but the slash-and-burn surgeons found

> it more profitable to mutilate them. Mastectomies create opportunities for

> their colleagues in the cosmetic breast reconstruction business.

>

> In 1993 Dr. n Whitaker, author of the subscription newsletter Health

> and Healing, pointed out that since 1986, the number of mammogram clinics

> in the U.S. has tripled. Big money has been invested in these clinics, and

> investors profit by scaring women about breast cancer so they will start

> having routine mammograms at an early age. Breast cancer scare stories

> frequently appear in daily newspapers.

>

> Mammogram interpretations are unreliable. According to an article in the

> Journal of the American Medical Association (May 26, 1993) one study

> revealed a false positive rate in the range of 20% to 63%. This suggests

> that huge numbers of women are unnecessarily going through the pain,

> expense, and anxiety of biopsies.

>

> The claim that a woman has " 1 chance in 9 " of developing breast cancer is

> often repeated. This is manipulation and dishonest use of statistics. The

> scare-mongers fail to point out that they are talking about life-time

> cumulative odds, unadjusted for risk factors. In other words, the

> statement means that a woman of average risk has 1 chance in 9 of

> developing breast cancer at some time in her life, before she dies. This

> is very different from annual incidence of breast cancer. Annual incidence

> is about 1 in a 1000 for all women and much less for younger women.

>

> Regarding the " 1-in-9 " claim, Whitaker cites I. Craig , professor

> of medicine at the University of California in San Francisco, who

> calculated that a woman would have to reach the age of 110 before her

> life-time odds of having breast cancer would be as high as 1 in 9 !!

>

> These are just crude odds, and ignore the issue of risk factors. There is

> something very important that breast cancer scare campaigners often

> neglect to tell women: smoking and obesity elevate risk for breast cancer.

> Women who don't smoke and who aren't overweight are at significantly

> reduced risk. On the nutrition side, there is opinion that eating more

> cruciferous vegetables reduces breast cancer risk, and that the

> antioxidant vitamins are cancer-fighters.

>

> Additionally, in 1997 evidence surfaced indicating excessive drinking as a

> breast cancer risk factor. An article published in the medical journal

> Lancet (Nov 22, 1997) describes a study which concluded that 25% of breast

> cancers may be attributable to alcohol consumption, but there was no

> additional risk associated with light drinking. Drinking of " long

> duration " was also mentioned as a risk factor, but only for women who were

> defined as " moderate-to-heavy " drinkers (more than 5 grams of alcohol a

> day). It didn't say how many years were required to be considered " long

> duration. "

>

> The scare campaigners often neglect the task of telling women how they can

> reduce risk through life-style choices. Instead, they talk up the idea of

> a " bad gene " which they say accounts for breast cancer. The typical scare

> campaign message usually goes something like this:

> 1. Either you have this genetic curse or you don't.

> 2. If you have it, then there is no hope for you except through " early

> detection and intervention " through routine mammograms initiated at a

> young age.

> 3. If your mom or grandma had breast cancer, then you probably also have

> the bad gene, so you're in for trouble too.

>

> Women exposed to this kind of talk from doctors or other health personnel

> should ask a few questions. Ask if the epidemiological research involving

> the alleged genetic connection actually controlled for grandma's life

> style. Did grandma smoke? Was she overweight? Did she eat a lot of

> cruciferous vegetables? Did she take anti-oxidant vitamins? Was she a

> heavy drinker? Unless the studies control for these variables, then

> conclusions from research about the " bad gene " are extremely questionable.

>

>

> News articles in the 1990s began to report that the idea of " preventive

> mastectomy " is being promoted for women believed to carry the " bad gene "

> -- even if they have no sign of breast cancer ! An AP story carried by the

> Dallas Morning News (April 17, 1997) bears the headline " Pre-Cancer

> Mastectomies Success Noted. " The lead paragraph describes the practice of

> removing both breasts while they are still healthy as " increasingly

> common. "

>

> About the " Bad Gene "

>

> There is a school of opinion which holds that inorganic toxins, not

> viruses or " bad genes, " are primarily the causes of cancer. Tobacco use

> associated with lung cancer is a prominent example. This viewpoint does

> not rule out the possibility that some may possess a genetic advantage in

> resisting the effect of the toxins, but genes are not seen as the causal

> agent.

>

> The problem with the toxicology approach is that its wide acceptance would

> be politically unfeasible for the ruling interests of U.S. society.

> Industrial corporations and military organizations which pollute the

> environment would be seen as culpable. Further, drug manufacturers and

> medical enterprises engaged in surgery have far less to gain by focusing

> blame for cancer on toxins. The toxicology approach undermines

> opportunities to peddle vaccines, anti-viral drugs, and " preventive "

> mastectomies.

> Asking Questions and Understanding Diagnostic Procedures

>

> Health care consumers need always to bear in mind the fact that there is

> no such thing as a perfectly accurate diagnostic procedure. Although

> doctors deliver the results of diagnostic tests with God-like authority,

> there is a substantial body of health science literature devoted to the

> measurement of error rates. Women under 50 are being convinced to begin

> having routine mammogram tests. The medical system is already putting them

> on a track which has the potential of leading thousands to unnecessary

> mastectomies resulting from diagnostic error and implementation of the

> bizarre practice of " preventive " mastectomy. Readers need to understand

> some of the vocabulary associated with measurement of diagnostic error in

> order to fully comprehend the danger.

>

> There are obviously two kinds of errors:

> 1. false positive -- concluding that disease is present when it is truly

> absent, and

> 2. false negative -- concluding that a disease is absent when it is truly

> present.

>

> Sensitivity is the accuracy measure associated with false negative error.

> A highly sensitive test will have a low false negative error rate.

> Specificity is the accuracy measure associated with false positive error.

> A highly specific test will have a low false positive error rate.

> More Terms: Incidence and Prevalence

>

> I have earlier used the phrase annual incidence in this document. Like

> income, incidence is a flow: it is the number of new disease cases

> emerging within a specified time interval. Usually it is reported as

> annual cases per 100,000 members of a population. Returning to the

> financial analogy, prevalence can be seen as a stock, such as one's

> assets, existing at a given point in time. It is can be expressed as a

> decimal or percentage. For example, if on any given day 10% of the members

> of your community are infected with a flu virus, then that would be the

> prevalence.

> Bayes Law and False Positives

>

> Bayes Law is a mathematical rule known among health researchers concerned

> with diagnostic errors. It simply means that, at any given level of

> specificity, the false positive error rate will increase as the true

> prevalence of the disease diminishes within the population being tested.

>

> To illustrate Bayes Law in relation to breast cancer diagnosis, assume

> that the joint specificity of the mammogram/biopsy procedure is 99.9%.

> This high level of accuracy will still yield 1 false positive error for

> every 1000 truly non-diseased women tested for breast cancer.

>

> For all women, the annual incidence in the USA is approximately one breast

> cancer case per 1000. I have been so far unable to discover any published

> estimates of prevalence for this group, but accounting for annual

> mortality, treatment, and failure to detect all cases, a fair estimate of

> prevalence might be 1 in 500. This means that for every 1000 women

> selected indiscriminately for the diagnostic procedure, there will be two

> truly diseased cases and one false positive. In other words, one third of

> the positive diagnostic reports will be false. For young women, the risk

> of false positives is higher, since the prevalence is lower.

>

> The key adjective in the above paragraph is indiscriminately. In a

> rational, people-oriented system, women under 50 would be encouraged to

> undergo breast cancer detection procedures only in the presence of

> identifiable risk factors, such as smoking, obesity, and a history of

> heavy drinking.

>

> Women confronting their doctors in discussions of breast cancer diagnosis

> should ask questions about risk factors. Consider, for example, a woman

> who has the following characteristics:

> 1. age 36

> 2. no history of smoking

> 3. non-obese

> 4. no history of excessive drinking

>

> Found in the company of a doctor trying to persuade her to undergo a

> mammogram, she should cite these four characteristics and then ask the

> question:

> What is the prevalence and annual incidence of breast cancer among women

> who have these traits?

>

> If the doctor doesn't know the answer, then he shouldn't be entrusted with

> decisions about her body, particularly if the possibility of a mastectomy

> is looming on the horizon. Anyone who is ever in the position of trying to

> convince a woman to undergo a mastectomy ought to be able to answer, with

> reasonable precision, a question about prevalence and incidence adjusted

> for risk factors. For purposes of illustration, assume that the prevalence

> of breast cancer for women with the characteristics listed above is 1 in

> 5,000.

>

> A woman advised to have a biopsy, following a positive mammogram, should

> remember that mammograms frequently yield false positive results. Then she

> should ask her doctor the question:

> What is the joint specificity of the mammogram/biopsy procedure?

>

> If the doctor claims to know the answer, she should ask him to cite a

> study in a medical journal, so that she can read it herself. If he is

> unable to do so, or claims that breast cancer diagnostic errors never

> happen, she should walk out the door. One shouldn't trust her body to

> someone who can't defend his practice with scientific literature.

>

> Recalling that a procedure with 99.9% specificity randomly applied will

> yield one false positive error for every 1000 true negatives, within a

> population where the true prevalence is only .0002 (1 in 5,000)

> indiscriminate testing will detect only two truly diseased woman for every

> ten victimized with false positives. In other words, 83% of the positive

> results will be false.

>

> In consideration of the false positive hazard, the following is suggested

> for women being encouraged to have a breast cancer biopsy:

>

> 1. Decide what is an acceptable hazard rate for an unnecessary mastectomy.

> For example, is a 50% chance that the diagnosis will yield an error

> unacceptable?

> 2. Ask the questions suggested above and, if the medical personnel can

> cite scientific literature to defend their answers, do the Bayes Law

> computation. If they can't cite such literature, then go elsewhere for

> medical advice.

>

> The Risk Factor Game

>

> The risk factors I have discussed in this work are behavioral, rather than

> biological. Focusing on behavioral risk factors gives women a greater

> degree of confidence that they can minimize their risk, and be in control

> of their destiny, by making the right choices.

>

> If you discuss breast cancer risk factors with doctors or other medical

> personnel, don't be surprised if they overlook these behavioral factors

> and emphasize the biological risk factors, such as early onset of

> menstruation and " bad genes. " These biological risks are non-controllable,

> and focusing on them while ignoring the behavioral factors leaves women

> with a greater sense of helplessness and susceptibility to manipulation by

> the medical hustlers.

>

> Diagnostic Error and Malpractice Lawsuits

>

> Doctors know that the hazard of facing malpractice lawsuits resulting from

> diagnostic error is much greater for making false negative instead of

> false positive mistakes. The reason for this is obvious. If a cancer-free

> breast is unnecessarily removed after a false positive diagnosis, the

> evidence is gone. On the other hand, if a woman is told by a doctor that

> she is cancer-free, but at a later stage becomes convinced that the

> original diagnosis was an error and the cancer has become more severe in

> the absence of treatment, she is in a position to sue for malpractice.

> Aware of this, doctors are inclined to " err on the side of caution, " to

> avoid being sued. But their caution is not necessarily in the patients'

> interest. It is in the doctors' interests. It is in the patient's interest

> to be on guard against this.

>

> One final word: a woman should never forget that only she is in charge of

> her body.

> ____________________________________________________________________

>

> For further information regarding reprinting and syndication, please call

> at (405) 329-6688, or send e-mail to mpwright9@...

> (Permission granted to download, photocopy and distribute on a

> non-commercial basis.)

> About the Author

>

> P. was graduated from the University of Oklahoma with a BA

> in political science and MA in sociology. His professional record includes

> research in a variety of areas including health science, energy economics,

> American Indian history, and computer software development for health risk

> assessment. He has on several occasions appeared before Oklahoma

> legislative committees in the capacity of expert witness. has also

> been the recipient of four federal grants from the Small Business

> Innovation Research program of the US Public Health Service. In this

> capacity part of his tasks included study of diagnostic error.

>

> is listed in the 24th and 25th editions of Who's Who in the South

> and Southwest, published by Marquis, and the 17th edition of the British

> directory Men of Achievement. He has been published in the American

> Journal of Preventive Medicine (Sept/Oct. 1997), the Journal of the

> American Medical Association (letter, Mar 24/31, 1993), and AIDS Education

> and Prevention (fall 1991). Additionally, his work has been presented in

> the proceedings of the Oklahoma Symposium on Artificial Intelligence

> (November 1993, Oklahoma State University), and he has been a guest

> opinion writer for the San Francisco Chronicle (May 24, 2000).

>

>