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Putting the risk of breast cancer in perspective

Education and debate
Putting the risk of breast cancer in perspective
John P Bunker, Joan Houghton,Michael Baum
Patients are frequently given the opportunity to
participate in making decisions about their care. To
assist them in making their decisions data that are as
accurate and as complete as appropriate will need to
be quickly available. These data will be needed not
only by patients but also by their doctors. A life table
constructed from regularly published statistics on
national morbidity and mortality can be used to
display the likelihood of developing or dying of a
disease (a cumulative probability) at any given age.
Such a life table may be a valuable tool in helping
patients to make decisions about their care. In this
paper we discuss the use of life tables to present to
patients the absolute and relative risks of breast cancer
and their use in comparing the risks from breast
cancer with those from other life threatening
Cumulative incidence
Recently, notices in London’s underground warned
that women havea1in12riskofdeveloping breast
cancer. Women in America have been warned that
their risk is 1 in 8; consequently, “fear of breast cancer
is so pervasive among US women that it is causing
them to ignore far more serious health threats.”1For
women who manage to escape other, greater health
risks and survive to age 75 or 80, risks of 1 in 12 and 1
in 8 are approximately correct. (The greater risk in
America may reflect the earlier introduction of mass
screening, the fact that women are screened at younger
ages, and the overdiagnosis of tumours of low grade
malignancy or of ductal carcinoma in situ
that might never become clinically detectable or life
More relevant to the concerns of younger women is
the risk of developing breast cancer earlier in their
lives. A life table analysis of the cumulative incidence of
breast cancer in England and Wales shows that the risk
for women under age 35 is 1 in 625. This rises to 1 in
56 by age 50, to 1 in 18 by age 65, and to 1 in 13 by age
75.4This type of age specific data should offset dispro-
portionate fear of the disease among women but it falls
short of meeting the information needs of individuals.
Life table estimates based on the entire population are
averages; the risk for an individual varies depending on
the presence or absence of predisposing risk factors
such as a family history of the disease, age at menarche,
age at first pregnancy, age at menopause, whether oral
contraceptives have been used, and the amount of
alcohol consumed. In postmenopausal women risk
factors include the use of hormone replacement
therapy and obesity in women not receiving hormone
replacement therapy.
Coordinating absolute and relative risks
The quantitative significance of risk factors has been
poorly presented to both the public and the medical
profession. In 1996, many women were concerned
after publication of a review of the association between
breast cancer and hormonal contraceptives which
stated that the risk of breast cancer was increased by
20% among women who used oral contraceptives.5If
the risk had been presented as a cumulative increase in
absolute risk from 16 to 18.7 per 10 000 women for a
woman aged between 30 and 35, which was how it was
presented in the review (table 15), then different assess-
ments of personal risk might have occurred. This
increase in absolute risk represents one additional case
of breast cancer occurring annually (excess cumulative
incidence) among 3700 women taking oral contracep-
tives; this would increase to one additional case occur-
ring among 2100 women as a woman became five
years older. For a woman aged 30 to 35 this could be
Summary points
A life table constructed from national statistics on
morbidity and mortality can be a valuable
resource in helping patients to make decisions
about their care
Coordinating absolute and relative risks in a life
table offers patients and doctors the opportunity
to make more informed judgments
Life table analysis allows patients and doctors to
estimate the cumulative probability of dying of
breast cancer before a patient reaches a given age
The risk of developing or dying of breast cancer
should be seen in the context of other life
threatening conditions
For women who smoke the cumulative probability
of dying of lung cancer matches that of dying of
breast cancer when women reach their early 50s;
this probability doubles by age 65 and triples by
age 75
Cancer Research
Campaign and
UCL Cancer Trials
Centre, University
College London
Medical School,
London W1P 8AN
John P Bunker,
visiting professor
Joan Houghton,
senior lecturer,
department of
Department of
Surgery, University
College London
Middlesex Hospitals
Trust, London
Michael Baum,
professor of surgery
Correspondence to:
Dr Bunker
BMJ 1998;317:1307–9
1307BMJ VOLUME 317 7 NOVEMBER 1998
compared to a 40% increase in the risk of developing
breast cancer if she consumed the equivalent of “24 g
(1 oz) of absolute alcohol daily (about two drinks
daily).”6This risk would convert to an excess cumulative
incidence of one additional case of breast cancer
occurring among about 1500 women.
The benefits and risks of treatment are perceived
differently by health professionals78 and the public
depending on whether they are presented as absolute
or relative improvements.Members of a health author-
ity were presented with the results of a large Swedish
trial in which a relative risk reduction of 34% was
reported and asked if they would vote to fund
mammographic screening.89 The majority said that
they would favour funding the screening. When the
same results were disguised as a different trial and pre-
sented as an absolute risk reduction of 0.06%, the
majority indicated that they would vote against funding
screening. When presented with 1592 patients as the
number needed to treat to save one life, half of those
surveyed indicated that they would be in favour of
screening. Presenting these data in a life table similar to
table 1 would have offered a better opportunity for the
members of the health authority to make a more
informed judgment.
Cumulative mortality
A woman probably wants to know her risk of develop-
ing breast cancer at her age and with her risk factors;
she may have a better appreciation of the risk if the
numbers can be seen as absolute as well as relative
risks. But this is not enough. A woman will also want to
know her prognosis and, in particular, the probability
that she will live or die. She might also want to know
how such a probability compares with that of dying of
other life threatening conditions.
Analysing death rates may lead to some surprises
for doctors and their patients. The first surprise is that
there is an increasingly large discrepancy between the
incidence of and mortality from breast cancer in
America; since 1940 mortality has remained constant
while incidence has nearly doubled.2This discrepancy
can only partially be accounted for by the growing
success of treatment. Thus, the woman concerned
about the possibility of developing breast cancer in the
future should know that the likelihood of subse-
quently dying of breast cancer is relatively small and is
becoming smaller each year. A life table analysis based
on 1995 mortality statistics for England and Wales10
allows us to estimate the cumulative probability of a
patient dying of breast cancer before she reaches a
given age.
Mortality from breast cancer among women in dif-
ferent age groups was derived from data from the
Office for National Statistics (table 2).10 The data were
adjusted for the number of women surviving in each
age group. The number of women dying from all
causes in each age group was calculated from the
resulting life table, which was based on mortality in the
female population. The cumulative number of deaths
from breast cancer is found by adding the number of
deaths from the disease occurring at each age interval.
The per cent probability of dying from breast cancer
before the end of each age interval is found by dividing
the number in the cumulative risk column by 1000. In
England and Wales before the age of 50 only one
woman out of 136 dies of breast cancer. By the age of
60 this is one out of 65, by the age of 70 it is one out of
39, and by the age of 80 only one woman out of 26 dies
of breast cancer (table 2).
The risk of dying of breast cancer should be seen
in the context of other risks to a woman’s life. The risk
of dying of heart disease has been underestimated by
women and its threat is perceived to be low.11 Women
may believe that deaths from cardiac causes primarily
affect men and elderly women whereas, at least in
smokers, the number of deaths occurring in women as
a result of cardiac causes exceeds the number of
deaths from breast cancer at all ages (figure).11 Fearing
death from breast cancer more than death from heart
disease reflects not simply an ignorance of probabili-
ties. “Heart disease, which offers at least the possibility
of sudden death, may not frighten people quite as
much [as cancer]: for many, for perhaps irrational
reasons, it is preferred. That certainly is the conclusion
from responses to the question ‘How would you like
to die?’1
Death from heart disease may be preferred by some
to death from breast cancer; death from lung cancer,
certainly as unpleasant as that from breast cancer, offers
a more apposite comparison. For women who smoke
Table 1 Estimated number of cases of breast cancer occurring in Europe or North
America in women who never used combined oral contraceptives and in women who
used them from age 25 to 29.5Used with permission from Elsevier Science
Age at
Breast cancers diagnosed in
women who never used
combined oral contraceptives
(n=10 000)
Breast cancers diagnosed in women who used
combined oral contraceptives from age 25 to 29
(n=10 000)
5 year
5 year
incidence (SD)
Using estimates of relative risk for all users:
20-24 0.5 0.5 1 0.5 0.5 0
25-29 3.5 4 1.24 4.3 4.8 0.8 (0.1)
30-34 12 16 1.15 13.9 18.7 2.7 (0.5)
35-39 28 44 1.07 30.0 48.7 4.7 (1.0)
40-44 56 100 0.98 55.1 103.7 3.7 (2.0)
45-49 80 180 1.01 80.8 184.5 4.5 (3.6)
Using estimates of relative risk for users with total duration of use of oral contraceptives >1 year:
20-24 0.5 0.5 1 0.5 0.5 0
25-29 3.5 4 1.22 4.3 4.8 0.8 (0.1)
30-34 12 16 1.15 13.8 18.6 2.6 (0.5)
35-39 28 44 1.06 29.6 48.2 4.2 (1.0)
40-44 56 100 0.96 53.8 102.0 2.0 (2.0)
45-49 80 180 0.98 78.5 180.5 0.5 (3.9)
*Annual incidences per 100 000 never users were assumed to be 160 at ages 45-49 and 0.007(age17) at
ages 20-44; these rates are intermediate between rates in the United Kingdom and the United States in the
Table 2 Cumulative probability of death from breast cancer in England and Wales in
1995 per 100 000 women. Mortality was adjusted for the number of women surviving
in each age group. Data derived from Office for National Statistics10
Age interval
No of women dying of
breast cancer in each age
interval/100 000 women
Cumulative No of deaths from breast
cancer occurring by the end of each
age interval/100 000 women
Probability of dying of
breast cancer by end
of each age interval
25-34 34.6 34.6 1/2873
35-44 176.3 210.9 1/474
45-54 522.5 733.4 1/136
55-64 794.7 1528.1 1/65
65-74 1060.4 2588.0 1/39
75-84 1189.5 3778.0 1/26
Education and debate
1308 BMJ VOLUME 317 7 NOVEMBER 1998
the cumulative probability of dying of lung cancer
matches that of dying of breast cancer when women
reach their early 50s; this probability doubles by age 65
and triples by age 75 (figure). Although there has been a
modest fall in the number of women who smoke
(mainly among older women), there is little evidence
that the fear of developing lung cancer matches the fear
of developing breast cancer. Ironically, lung cancer has a
cure rate of < 5% and can be almost entirely prevented
by avoiding tobacco but, on average, 70% of patients
treated for breast cancer can expect to survive for 10
years. In contrast to lung cancer there is comparatively
little that can be done to prevent breast cancer.
The statistic that 1 in 12 women will develop breast
cancer is thus correct only for women who have
escaped a number of equally serious but more likely
threats to life at an earlier age. For most women the
lifetime risk of dying of breast cancer is only 1 in 26;
the other 25 women will die of something else. Life
table analyses show that the incidence of breast cancer
and mortality from the disease are much lower among
younger women and these risks should be understood
in the context of other serious threats to life.
1 Assessing the odds [editor ial].Lancet 1997;350:1563.
2 Har ris JR, Lippman ME, Veronesi U,Willett W. Breast cancer. New Engl J
Med 1992;327:319-28.
3 Feuer EJ, Wun L-M. How much of the recent rise in breast cancer
incidence can be explained by increases in mammography utilization? A
dynamic population model approach. Am J Epidemiol 1992;136:1423-36.
4 Office for National Statistics. 1991 cancer statistics registrations. London:
Stationery Office, 1997. (Series MB1, No 24.)
5 Collaborative Group on Hormonal Factors in Breast Cancer. Breast can-
cer and hormonal contraceptives: further results. Contraception
1996;54(suppl 3):1-106S.
6 Longnecker MP, Berlin JA, Orza MJ, Chalmers TC. A meta-analysis of
alcohol consumption in relation to risk of breast cancer. JAMA
7 Fahey T, Griffiths S, Peters TJ. Evidence based purchasing: understanding
results of clinical trials and systematic reviews. BMJ 1995;311:1056-60.
8 McColl A, Smith H, White P,Field J. General practitioner s’ perceptions of
the route to evidence based medicine: a questionnaire survey. BMJ
9 Tabar L, Fagerberg CJG, Gad A, Baldetorp L, Holmberg LH, Grontoft O,
et al. Reduction in mortality from breast cancer after mass screening with
mammography: randomised trial from the Breast Cancer Screening
Working Group of the Swedish National Board of Health and Welfare.
Lancet 1985;i:829-32.
10 Office for National Statistics. 1995 mortality statistics: cause. London:
Stationery Office, 1997. (Series DH2, No 22.)
11 Pilote L, Hlatky MA. Attitudes of women toward hormone therapy and
prevention of heart disease. Am Heart J 1995;129:1237-8.
12 Peto R,Lopez AD, Boreham J, Thun M, Heath C. Mortality from tobacco
in developed countries: indirect estimation from national vital statistics.
Lancet 1992;339:1268-78.
(Accepted 26 June 1998)
Confidence intervals for the number needed to treat
Douglas G Altman
The number needed to treat (NNT) is a useful way of
reporting the results of randomised controlled trials.1
In a trial comparing a new treatment with a standard
one, the number needed to treat is the estimated
number of patients who need to be treated with the
new treatment rather than the standard treatment for
one additional patient to benefit. It can be obtained for
any trial that has reported a binary outcome.
Trials with binary end points yield a proportion of
patients in each group with the outcome of interest.
When the outcome event is an adverse one, the differ-
ence between the proportions with the outcome in the
new treatment (pN) and standard treatment (pS) groups
is called the absolute risk reduction (ARR = pNpS).
The number needed to treat is simply the reciprocal of
the absolute risk difference, or 1/ARR (or 100/ARR if
percentages are used rather than proportions). A large
treatment effect, in the absolute scale, leads to a small
number needed to treat. A treatment that will lead to
one saved life for every 10 patients treated is clearly
better than a competing treatment that saves one life
for every 50 treated. Note that when there is no
treatment effect the absolute risk reduction is zero and
the number needed to treat is infinite. As we will see
below,this causes problems.
As with other estimates, it is important that the
uncertainty in the estimated number needed to treat is
accompanied by a confidence interval. A confidence
Age at death
No of deaths
706050403020 80
10 000
15 000
20 000
25 000
30 000
35 000
Breast cancer
Lung cancer, smokers
Heart disease, smokers
Heart disease, non-smokers
Cumulative number of deaths in 1995 from breast cancer, lung
cancer in smokers, heart disease in smokers, and heart disease in
non-smokers per 100 000 women in England and Wales. A risk ratio
of 12.5:1 for lung cancer and 2.3:1 for heart disease for smokers v
non-smokers was assumed12
Summary points
The number needed to treat is a useful way of
reporting results of randomised clinical trials
When the difference between the two treatments
is not statistically significant, the confidence
interval for the number needed to treat is difficult
to describe
Sensible confidence intervals can always be
constructed for the number needed to treat
Confidence intervals should be quoted whenever
a number needed to treat value is given
Education and debate
Imperial Cancer
Research Fund
Medical Statistics
Group, Centre for
Statistics in
Medicine, Institute
of Health Sciences,
Oxford OX3 7LF
Douglas G Altman,
professor of statistics
in medicine
BMJ 1998;317:1309–12
1309BMJ VOLUME 317 7 NOVEMBER 1998
... 26 A causal relationship between ERT/HRT and breast cancer, however, remains controversial. 15,17,29 The Impact of Estrogen Therapy on Arthritis ...
... It is not uncommon for the patients to misunderstand their risk for cancer due to widely available information on breast cancer risk 4 assessment . Women tend to overestimate their 5,6 breast cancer risk , and this misjudgment of risk can cause anxiety, which can be significantly enhanced by going through mammography 7 procedure . Although a reasonable concern about breast cancer risk can encourage the women to become more involved in screening mammo- 8 graphy, ...
Background: Worry about risk for breast cancer and pain are associated withmammography use. Both have been found to be a barrier to mammography use by women.Objective: To examine the anxiety and pain associated with mammography use in a sample ofwomen stratified according to breast cancer risk. Design: This prospective observational study.Setting: Department of Obstetric and Gynecology, Benazir Bhutto Hospital. Period: August2011 to June 2012. Patients & Methods: Women awaiting screening mammography in thereception area were asked to complete a questionnaire containing demographics for calculationof breast cancer risk and the Likert scale for anxiety before the procedure and VAS forassessment of pain after the procedure. Results: Our study included 100 women undergoingscreening mammography with an average age of 53.9±8.8 years. 15% were classified “higherrisk” by the Gail model. The average anxiety level was 4.03±1.3 on Likert scale and average painduring the procedure was 3.3±2.18 on VAS. Significant differences (p<0.05) were foundbetween average and higher risk groups. Conclusions: The population of women in this sampleappears to have a level of breast cancer worry and procedure related pain that is proportionalwith their risk for developing breast cancer.
... As such the development of a range of risks, provided in context, would be consistent with the literature regarding the most appropriate way of providing risk information, here specifically relating to breast cancer. To date the "quantitative significance of risk factors has been poorly presented to both the public and the medical profession" (Bunker et al., 1998). ...
Full-text available
Breast cancer is the most common malignancy in women with 36,509 new cases registered in the UK in 2003. Women are often quoted as having a 1 in 9 risk of developing breast cancer at some point during their lifetime, yet data suggests that women often over estimate their risks. An increased perceived risk of developing breast cancer may increase anxiety and worry, but also potentially lead to the inappropriate use of medical services. Equally the underestimation of risk may lead to some women missing out on medical help. Current research suggests that women may prefer a range of estimates as opposed to a single figure and that risk perception may be improved through risk communication that utilises both visual and numerical data together with estimate ranges. The interpretation of risk may also be improved by providing a context for risk estimates. Recent evidence also suggests that the 1 in 9 risk may be out of date, with increasing incidence in recent years but it is also now recognised that some women are at an increased risk of developing breast cancer due to inherited mutations in the BRCA1 and BRCA2 genes. This study provides up to date risk estimates for women in the North West of England, not only for those women within the general population but also for BRCA1 and BRCA2 mutation carriers. The population risks estimates devised here suggest that the risk of developing breast cancer has indeed increased, with a calculated cumulative risk to age 85+ of 1 in 7.41 that a woman will develop breast cancer. Women with inherited mutations are at a vastly increased risk of developing breast cancer at, with a cumulative risk to 85+ that is 6.88 times that of women who do not carry either mutation. Including the competing risk of death from any cause reduces these risks, with the equivalent risk for women in the general population being reduced to 10.47% which equates to 1 in 9.55 risk of developing breast cancer. The analysis here provide age specific risks given that a woman is currently cancer free, in order to provide both lifetime and more short term risks that may allow for improved decision making within the clinical setting.
Full-text available
Objectives To determine the degree to which women with early breast cancer understand the prognostic information communicated by clinicians after breast cancer diagnosis, and their preferences for how this information is presented. Design Cross‐sectional survey conducted within two months of breast cancer diagnosis, using a self‐administered written questionnaire. Participants and setting One hundred women attending five Sydney teaching hospitals and one country hospital, who were diagnosed with early stage breast cancer between January and December 1997. Results The 100 respondents represented 70% of the 143 women originally approached to participate. Many respondents did not fully understand the language typically used by surgeons and cancer specialists to describe prognosis: 53% could not calculate risk reduction (with adjuvant therapy) relative to absolute risk; 73% did not understand the term “median” survival; and 33% believed a cancer specialist could predict an individual patient's outcome. Women in professional/ paraprofessional occupations understood more prognostic information than nonprofessional women. There was no agreement on the descriptive equivalent of a “30%” risk, nor the numerical interpretation of a “good” chance of survival. Forty‐three per cent of women preferred positively framed messages (eg, “chance of cure”), and 33% negatively framed messages (eg, “chance of relapse”). The information women most wanted was that relating to probability of cure, staging of their cancer, chances of treatment being successful, and 10‐year survival figures with and without adjuvant therapy. Conclusions Our results suggest that misunderstanding is responsible for women's confusion about breast cancer prognosis. Clinicians should use a variety of techniques to communicate prognosis and risk, and need to verify that the information has been understood.
Finding the optimal use of health-care resources requires the reliable estimation of costs and consequences. Acquiring these estimates may not be difficult for some common treatments. More difficult is the optimization of resources in the area of diagnostics. Only a few attempts have been made to optimize the use of resources in the area of prevention. Several aspects have to be considered when optimizing the resources for prevention: (1) participation rates in structured prevention programs are low, (2), acquiring data on follow-up and outcomes is difficult, (3) there are concerns about the quality of information available to public, and (4), the public is often unaware of scientific assessments of prevention programs. As prevention programs are costly long-term projects, a strategy to select these programs according to possible predictors of success might be useful. The few analyses of cancer prevention in the literature have been directed towards the most common malignant diseases (as assessed by incidence) such as cancer of the breast, colon, lung and prostate. We argue that incidence is a poor marker for selecting secondary prevention programs. Incidence may be a misleading indicator for two reasons: incidence of disease does not predict efficiency of management or good health outcomes, and incidence does not separate clinically significant from non-significant disease. The traditional strategy is based on the assumption that more screening increases the chance of cure. We propose an alternative outcomes model that suggests better disease management justifies new prevention programs. Indicators for better disease management are effective and efficient treatments as well as high-quality screening (sensitivity and specificity) techniques and possibly “side-effects of prevention programs,” which provide early signs of success to motivate the patient's participation, to keep up with the program and finally to succeed.
Breast cancer is the most commonly occurring malignancy among women of reproductive age and the second most common pregnancy-associated cancer, after cervical cancer [1,2]. Pregnancy-associated breast cancer (PABC) is defined as breast cancer diagnosed during pregnancy or within one year postpartum and it is estimated to account for up to 3% of all breast cancers. The prevalence of PABC is between 1 in 3,000 and 1 in 10,000 pregnancies. A high index of suspicion is required when evaluating a breast mass among pregnant and lactating women because of the substantial physiological changes of the female body during pregnancy. When a new breast mass is suspected, diagnostic evaluation must begin promptly. Although mammography is the imaging of choice among nonpregnant women with a breast mass, its sensitivity declines among pregnant and lactating women due to the glandularity and the water content of the breast [1]. In one study, the false-negative mammography rate was significantly higher among pregnant women than among nonpregnant women (14% vs. 6%, respectively; P < 0.0001) [3]. Ultrasound is the modality of choice when PABC is suspected. It has been reported to distinguish solid from cystic lesions in 97% of cases [4], and with 100% sensitivity in a few studies [1,5,6]. There are insufficient evidence-based data regarding the efficacy of magnetic resonance imaging (MRI) and the safety of gadolinium during pregnancy. Thus, the international recommendations from an expert meeting summarized by Loibl et al. recommended against it [7].
Full-text available
A randomised controlled trial to investigate the efficacy of mass screening with single-view mammography in reducing mortality from breast cancer was started in Sweden in 1977. 162 981 women aged 40 years or more and living in the counties of Kopparberg and Ostergötland were enrolled in the study and divided at random into 2 groups. Each woman in the study group was offered screening every 2 or 3 years depending on age. Women in the control group were not offered screening. This report is confined to the 134 867 women aged 40-74 years at date of entry. The results to the end of 1984 show a 31% reduction in mortality from breast cancer and a 25% reduction in the rate of stage II or more advanced breast cancers in the group invited to screening. 7 years after the start of the study the excess of stage I cancers in the study group largely outweighs the deficit of advanced cancers.
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To assess whether the way in which the results of a randomised controlled trial and a systematic review are presented influences health policy decisions. A postal questionnaire to all members of a health authority within one regional health authority. Anglia and Oxford regional health authorities. 182 executive and non-executive members of 13 health authorities, family health services authorities, or health commissions. The average score from all health authority members in terms of their willingness to fund a mammography programme or cardiac rehabilitation programme according to four different ways of presenting the same results of research evidence--namely, as a relative risk reduction, absolute risk reduction, proportion of event free patients, or as the number of patients needed to be treated to prevent an adverse event. The willingness to fund either programme was significantly influenced by the way in which data were presented. Results of both programmes when expressed as relative risk reductions produced significantly higher scores when compared with other methods (P < 0.05). The difference was more extreme for mammography, for which the outcome condition is rarer. The method of reporting trial results has a considerable influence on the health policy decisions made by health authority members.
The Collaborative Group on Hormonal Factors in Breast Cancer has brought together and reanalysed the worldwide epidemiological evidence on breast cancer risk and use of hormonal contraceptives. Original data from 54 studies, representing about 90% of the information available on the topic, were collected, checked and analysed centrally. The 54 studies were performed in 26 countries and include a total of 53,297 women with breast cancer and 100,239 women without breast cancer. The studies were varied in their design, setting and timing. Most information came from case-control studies with controls chosen from the general population; most women resided in Europe or North America and most cancers were diagnosed during the 1980s. Overall 41% of the women with breast cancer and 40% of the women without breast cancer had used oral contraceptives at some time; the median age at first use was 26 years, the median duration of use was 3 years, the median year of first use was 1968, the median time since first use was 16 years, and the median time since last use was 9 years. The main findings, summarised elsewhere, are that there is a small increase in the risk of having breast cancer diagnosed in current users of combined oral contraceptives and in women who had stopped use in the past 10 years but that there is no evidence of an increase in the risk more than 10 years after stopping use. In addition, the cancers diagnosed in women who had used oral contraceptives tended to be less advanced clinically than the cancers diagnosed in women who had not used them. Despite the large number of possibilities investigated, few factors appeared to modify the main findings either in recent or in past users. For recent users who began use before age 20 the relative risks are higher than for recent users who began at older ages. For women whose use of oral contraceptives ceased more than 10 years before there was some suggestion of a reduction in breast cancer risk in certain subgroups, with a deficit of tumors that had spread beyond the breast, especially among women who had used preparations containing the highest doses of oestrogen and progestogen. These findings are unexpected and need to be confirmed. Although these data represent most of the epidemiological evidence on the topic to date, there is still insufficient information to comment reliably about the effects of specific types of oestrogen or of progestogen. What evidence there is suggests, however, no major differences in the effects for specific types of oestrogen or of progestogen and that the pattern of risk associated with use of hormonal contraceptives containing progestogens alone may be similar to that observed for preparations containing both oestrogens and progestogens. On the basis of these results, there is little difference between women who have and have not used combined oral contraceptives in terms of the estimated cumulative number of breast cancers diagnosed during the period from starting use up to 20 years after stopping. The cancers diagnosed in women who have used oral contraceptives are, however, less advanced clinically than the cancers diagnosed in never users. Further research is needed to establish whether the associations described here are due to earlier diagnosis of breast cancer in women who have used oral contraceptives, to the biological effects of the hormonal contraceptives or to a combination of both. Little information is as yet available about the effects on breast cancer risk of oral contraceptive use that ceased more than 20 years before and as such data accumulate it will be necessary to re-examine the worldwide evidence.
Largely unexplained increases in breast cancer incidence of about 1% per year have been documented back to the 1940s. Since 1982, breast cancer incidence in women aged 40 years and above has been increasing at a faster rate than this long-term secular trend, especially in women aged 60 years and above. Increases in the use of mammography since 1982 (which have been documented in population surveys of women) provide the most plausible explanation for the incidence increase over the long-term secular trend. A study by White et al. (J Natl Cancer Inst 1990;82:1546-52) found that, for women aged 45-64 years, the increase in mammography utilization could explain the incidence increase, while for women aged 65-74 years, it could account for only half the increase. The authors have developed an alternative model to that of White et al. that incorporates estimates of differential lead time (time from screen detection to clinical detection in the absence of screening) by age group. Using this model, the authors show that if older women have longer lead times, than similar increases in mammography utilization across age groups will lead to a larger incidence increase in older women. Thus, the observed increases in mammography utilization are generally concordant with increases in incidence, even in the older age groups.
Prolonged cigarette smoking causes even more deaths from other diseases than from lung cancer. In developed countries, the absolute age-sex-specific lung cancer rates can be used to indicate the approximate proportions due to tobacco of deaths not only from lung cancer itself but also, indirectly, from vascular disease and from various other categories of disease. Even in the absence of direct information on smoking histories, therefore, national mortality from tobacco can be estimated approximately just from the disease mortality statistics that are available from all major developed countries for about 1985 (and for 1975 and so, by extrapolation, for 1995). The relation between the absolute excess of lung cancer and the proportional excess of other diseases can only be approximate, and so as not to overestimate the effects of tobacco it has been taken to be only half that suggested by a recent large prospective study of smoking and death among one million Americans. Application of such methods indicates that, in developed countries alone, annual deaths from smoking number about 0.9 million in 1965, 1.3 million in 1975, 1.7 million in 1985, and 2.1 million in 1995 (and hence about 21 million in the decade 1990-99: 5-6 million European Community, 5-6 million USA, 5 million former USSR, 3 million Eastern and other Europe, and 2 million elsewhere, [ie, Australia, Canada, Japan, and New Zealand]). More than half these deaths will be at 35-69 years of age: during the 1990s tobacco will in developed countries cause about 30% of all deaths at 35-69 (making it the largest single cause of premature death) plus about 14% of all at older ages. Those killed at older ages are on average already almost 80 years old, however, and might have died soon anyway, but those killed by tobacco at 35-69 lose an average of about 23 years of life. At present just under 20% of all deaths in developed countries are attributed to tobacco, but this percentage is still rising, suggesting that on current smoking patterns just over 20% of those now living in developed countries will eventually be killed by tobacco (ie, about a quarter of a billion, out of a current total population of just under one and a quarter billion).
This article has no abstract; the first 100 words appear below. BREAST cancer is a major public health problem of great interest and importance to physicians in a variety of specialties. Since this topic was last reviewed in the Journal,¹ the incidence of the disease has increased dramatically, heightening concern among physicians and women in general. In addition, long-term results are now available from clinical trials initiated in the 1970s and 1980s to evaluate the usefulness of early detection with mammography and physical examination, breast-conserving treatment with limited breast surgery and irradiation, and adjuvant systemic therapy with hormonal therapy and chemotherapy. Furthermore, in the light of newly gained knowledge, new . . . Source Information From the Departments of Radiation Oncology, Beth Israel Hospital and the Dana–Farber Cancer Institute, and the Joint Center for Radiation Therapy, Harvard Medical School, Boston (J.R.H.); the Vincent T. Lombardi Cancer Research Center and the Departments of Medicine and Pharmacology, Georgetown University Medical Center, Washington, D.C. (M.E.L.); the Istituto Nazionale per lo Studio e la Cura dei Tumori, Milan, Italy (U.V.); and the Departments of Epidemiology and Nutrition, Harvard School of Public Health and the Channing Laboratory, Departments of Medicine, Harvard Medical School and Brigham and Women's Hospital, Boston (W.W.). Address reprint requests to Dr. Harris at the Harvard Joint Center for Radiation Therapy, 50 Binney St., Boston, MA 02115.
Epidemiologic findings regarding the relation between alcohol consumption and risk of breast cancer have been inconsistent. We performed a meta-analysis (a quantitative review) of the available data. To evaluate whether there was a dose-response relation between alcohol consumption and risk of breast cancer, we fitted mathematical models to the pooled data. There was strong evidence to support a dose-response relation in both the case-control and follow-up epidemiologic data. Using the dose-response curves that we calculated, the risk of breast cancer at an alcohol intake of 24 g (1 oz) of absolute alcohol daily (about two drinks daily) relative to nondrinkers was 1.4 (95% confidence interval, 1.0 to 1.8) in the case-control data and was 1.7 (95% confidence interval, 1.4 to 2.2) in the follow-up data. We interpret these findings not as proof of causality, but as strongly supportive of an association between alcohol consumption and risk of breast cancer.