Could perimenopausal oestrogen prevent breast cancer?

It has now been 30 years since the first epidemiologic report linked menopausal estrogen therapy—the exogenous estrogens that, along with progestins, came to be known as “hormone replacement therapy”—with an increased risk of breast cancer ([1][1]). Today, the body of evidence on this

Prior to the unexpected early termination of the Women’s Health Initiative (WHI) trial of continuous conjugated equine estrogens (CEE) and medroxyprogesterone acetate (MPA), the prevailing view was that hormone replacement therapy (HRT) was a low-risk intervention with immediate value for symptom relief in recently menopausal women, and that it probably conferred long-term protection against the major chronic diseases that affect women after menopause. Rather than replicating prior studies, the WHI was designed to test whether the beneficial associations consistently seen in women starting HRT near menopause would be found in women well beyond menopause. Views of the benefits and risks of HRT changed dramatically in 2002 with the unexpected early termination of the CEE + MPA trial and the alarming initial WHI report. HRT use plummeted world-wide, driven by fear of breast cancer and skepticism about cardiovascular benefits. Stunningly, the contrasting findings of the WHI trial of CEE alone reported 2 years later – suggesting prevention of coronary heart disease in women who began HRT at age <60 years, and a reduction in breast cancer overall – were largely ignored. Key lessons from the WHI are that the effects of HRT on most organ systems vary by age and time since last physiologic exposure to hormones and that there are differences between regimens. In the years since the first WHI report, we have learned much about the characteristics of women who are likely to benefit from HRT. The range of HRT regimens has also increased. Not all women have indications for HRT, but for those who do and who initiate within 10 years of menopause, benefits are both short-term (vasomotor, dyspareunia), and long-term (bone health, coronary risk reduction). Critically, the ‘facts’ that most women and clinicians consider in making the decision to use, or not use, HRT are frequently wrong or incorrectly applied.

Low-Dose Hormone Replacement Therapy for Hot Flashes–Reply–I

Although postmenopausal hormone replacement therapy (HRT) is widely used in the United States, new evidence about its benefits and harms requires reconsideration of its use for the primary prevention of chronic conditions. To assess the benefits and harms of HRT for the primary prevention of cardiovascular disease, thromboembolism, osteoporosis, cancer, dementia, and cholecystitis by reviewing the literature, conducting meta-analyses, and calculating outcome rates. All relevant English-language studies were identified in MEDLINE (1966-2001), HealthSTAR (1975-2001), Cochrane Library databases, and reference lists of key articles. Recent results of the Women's Health Initiative (WHI) and the Heart and Estrogen/progestin Replacement Study (HERS) are included for reported outcomes. We used all published studies of HRT if they contained a comparison group of HRT nonusers and reported data relating to HRT use and clinical outcomes of interest. Studies were excluded if the population was selected according to prior events or presence of conditions associated with higher risks for targeted outcomes. Meta-analyses of observational studies indicated summary relative risks (RRs) for coronary heart disease (CHD) incidence and mortality that were significantly reduced among current HRT users only, although risk for incidence was not reduced when only studies that controlled for socioeconomic status were included. The WHI reported increased CHD events (hazard ratio [HR], 1.29; 95% confidence interval [CI], 1.02-1.63). Stroke incidence but not mortality was significantly increased among HRT users in the meta-analysis and the WHI. The meta-analysis indicated that risk was significantly elevated for thromboembolic stroke (RR, 1.20; 95% CI, 1.01-1.40) but not subarachnoid or intracerebral stroke. Risk of venous thromboembolism among current HRT users was increased overall (RR, 2.14; 95% CI, 1.64-2.81) and was highest during the first year of use (RR, 3.49; 95% CI, 2.33-5.59) according to a meta-analysis of 12 studies. Protection against osteoporotic fractures is supported by a meta-analysis of 22 estrogen trials, cohort studies, results of the WHI, and trials with bone density outcomes. Current estrogen users have an increased risk of breast cancer that increases with duration of use. Endometrial cancer incidence, but not mortality, is increased with unopposed estrogen use but not with estrogen with progestin. A meta-analysis of 18 observational studies showed a 20% reduction in colon cancer incidence among women who had ever used HRT (RR, 0.80; 95% CI, 0.74-0.86), a finding supported by the WHI. Women symptomatic from menopause had improvement in certain aspects of cognition. Current studies of estrogen and dementia are not definitive. In a cohort study, current HRT users had an age-adjusted RR for cholecystitis of 1.8 (95% CI, 1.6-2.0), increasing to 2.5 (95% CI, 2.0-2.9) after 5 years of use. Benefits of HRT include prevention of osteoporotic fractures and colorectal cancer, while prevention of dementia is uncertain. Harms include CHD, stroke, thromboembolic events, breast cancer with 5 or more years of use, and cholecystitis.

This post is not about quackery, nor university politics. It is about inference, How do we know what we should eat? The question interests everyone, but what do we actually know? Not as much as you might think from the number of column-inches devoted to the topic. The discussion below is a synopsis of parts of an article called "In praise of randomisation", written as a contribution to a forthcoming book, Evidence, Inference and Enquiry. About a year ago just about every newspaper carried a story much like this one in the Daily Telegraph, What, I wondered, was the evidence behind these dire warnings. They did not come from a lifestyle guru, a diet faddist or a supplement salesman. This is nothing to do with quackery. The numbers come from the 2007 report of the World Cancer Research Fund and American Institute for Cancer Research, with the title ' Food, Nutrition, Physical Activity, and the Prevention of Cancer: a Global Perspective'. This is a 537 page report with over 4,400 references. Its panel was chaired by Professor Sir Michael Marmot, UCL's professor of Epidemiology and Public Health. He is a distinguished epidemiologist, renowned for his work on the relation between poverty and health. Nevertheless there has never been a randomised trial to test the carcinogenicity of bacon, so it seems reasonable to ask how strong is the evidence that you shouldn't eat it? It turns out to be surprisingly flimsy. In praise of randomisation Everyone knows about the problem of causality in principle. Post hoc ergo propter hoc; confusion of sequence and consequence; confusion of correlation and cause. This is not a trivial problem. It is probably the main reason why ineffective treatments often appear to work. It is traded on by the vast and unscrupulous alternative medicine industry. It is, very probably, the reason why we are bombarded every day with conflicting advice on what to eat. This is a bad thing, for two reasons. First, we end up confused about what we should eat. But worse still, the conflicting nature of the advice gives science as a whole a bad reputation. Every time a white-coated scientist appears in the media to tell us that a glass of wine per day is good/bad for us (delete according to the phase of the moon) the general public just laugh. In the case of sausages and bacon, suppose that there is a correlation between eating them and developing colorectal cancer. How do we know that it was eating the bacon that caused the cancer - that the relationship is causal? The answer is that there is no way to be sure if we have simply observed the association. It could always be that the sort of people who eat bacon are also the sort of people who get colorectal cancer. But the question of causality is absolutely crucial, because if it is not causal, then stopping eating bacon won't reduce your risk of cancer. The recommendation to avoid all processed meat in the WCRF report (2007) is sensible only if the relationship is causal. Barker Bausell said: [Page39] "But why should nonscientists care one iota about something as esoteric as causal inference? I believe that the answer to this question is because the making of causal inferences is part of our job description as Homo Sapiens." That should be the mantra of every health journalist, and every newspaper reader. Briefly, a lady claims to be able to tell whether the milk was put in the cup before or after the tea was poured. Fisher points out that to test this you need to present the lady with an equal number of cups that are 'milk first' or 'tea first' (but otherwise indistinguishable) in random order, and count how many she gets right. There is a beautiful analysis of it in Stephen Senn's book, Dicing with Death: Chance, Risk and Health. As it happens, Google books has the whole of the relevant section Fisher's tea test (geddit?), but buy the book anyway. Such is the fame of this example that it was used as the title of a book, The Lady Tasting Tea was published by David Salsburg (my review of it is here) Most studies of diet and health fall into one of three types, case-control studies, cohort (or prospective) studies, or randomised controlled trials (RCTs). Case-control studies are the least satisfactory: they look at people who already have the disease and look back to see how they differ from similar people who don't have the disease. They are retrospective. Cohort studies are better because they are prospective: a large group of people is followed for a long period and their health and diet is recorded and later their disease and death is recorded. But in both sorts of studies,each person decides for him/herself what to eat or what drugs to take. Such studies can never demonstrate causality, though if the effect is really big (like cigarette-smoking and lung cancer) they can give a very good indication. The difference in an RCT is that each person does not choose what to eat, but their diet is allocated randomly to them by someone else. This means that, on average, all other factors that might influence the response are balanced equally between the two groups. Only RCTs can demonstrate causality. Randomisation is a rather beautiful idea. It allows one to remove, in a statistical sense, bias that might result from all the sources that you hadn't realised were there. If you are aware of a source of bias, then measure it. The danger arises from the things you don't know about, or can't measure ( Senn, 2004; Senn, 2003). Although it guarantees freedom from bias only in a long run statistical sense, that is the best that can be done. Everything else is worse. Ben Goldacre has referred memorably to the newspapers' ongoing "Sisyphean task of dividing all the inanimate objects in the world into the ones that either cause or cure cancer" ( Goldacre, 2008). This has even given rise to a blog. " The Daily Mail Oncological Ontology Project ". The problem arises in assessing causality. It wouldn't be so bad if the problem were restricted to the media. It is much more worrying that the problem of establishing causality often seems to be underestimated by the authors of papers themselves. It is a matter of speculation why this happens. Part of the reason is, no doubt, a genuine wish to discover something that will benefit mankind. But it is hard not to think that hubris and self-promotion may also play a role. Anything whatsoever that purports to relate diet to health is guaranteed to get uncritical newspaper headlines. At the heart of the problem lies the great difficulty in doing randomised studies of the effect of diet and health. There can be no better illustration of the vital importance of randomisation than in this field. And, notwithstanding the generally uncritical reporting of stories about diet and health, one of the best accounts of the need for randomisation was written by a journalist, Gary Taubes, and it appeared in the New York Times ( Taubes, 2007). The case of hormone replacement therapy In the 1990s hormone replacement therapy (HRT) was recommended not only to relieve the unpleasant symptoms of the menopause, but also because cohort studies suggested that HRT would reduce heart disease and osteoporosis in older women. For these reasons, by 2001, 15 million US women (perhaps 5 million older women) were taking HRT ( Taubes, 2007). These recommendations were based largely on the Harvard Nurses' Study. This was a prospective cohort study in which 122,000 nurses were followed over time, starting in 1976 (these are the ones who responded out of the 170,000 requests sent out). In 1994, it was said ( Manson, 1994) that nearly all of the more than 30 observational studies suggested a reduced risk of coronary heart disease (CHD) among women receiving oestrogen therapy. A meta-analysis gave an estimated 44% reduction of CHD. Although warnings were given about the lack of randomised studies, the results were nevertheless acted upon as though they were true. But they were wrong. When proper randomised studies were done, not only did it turn out that CHD was not reduced: it was actually increased. The Women's Health Initiative Study ( Rossouw et al., 2002) was a randomized double blind trial on 16,608 postmenopausal women aged 50-79 years and its results contradicted the conclusions from all the earlier cohort studies. HRT increased risks of heart disease, stroke, blood clots, breast cancer (though possibly helped with osteoporosis and perhaps colorectal cancer). After an average 5.2 years of follow-up, the trial was stopped because of the apparent increase in breast cancer in the HRT group. The relative risk (HRT relative to placebo) of CHD was 1.29 (95% confidence interval 1.02 to 1.63) (286 cases altogether) and for breast cancer 1.26 (1.00 -1.59) (290 cases). Rather than there being a 44% reduction of risk, it seems that there was actually a 30% increase in risk. Notice that these are actually quite small risks, and on the margin of statistical significance. For the purposes of communicating the nature of the risk to an individual person it is usually better to specify the absolute risk rather than relative risk. The absolute number of CHD cases per 10,000 person-years is about 29 on placebo and 36 on HRT, so the increased risk of any individual is quite small. Multiplied over the whole population though, the number is no longer small. Several plausible reasons for these contradictory results are discussed by Taubes,(2007): it seems that women who choose to take HRT are healthier than those who don't. In fact the story has become a bit more complicated since then: the effect of HRT depends on when it is started and on how long it is taken ( Vandenbroucke, 2009). This is perhaps one of the most dramatic illustrations of the value of randomised controlled trials (RCTs). Reliance on observations of correlations suggested a 44% reduction in CHD, the randomised trial gave a 30% increase in CHD. Insistence on randomisation is not just pedantry. It is essential if you want to get the right answer. Having dealt with the cautionary tale of HRT, we can now get back to the 'Sisyphean task of dividing all the inanimate objects in the world into the ones that either cause or cure cancer'. The case of processed meat The WCRF report (2007) makes some pretty firm recommendations. Don't get overweight Be moderately physically active, equivalent to brisk walking for at least 30 minutes every day Consume energy-dense foods sparingly. Avoid sugary drinks. Consume 'fast foods' sparingly, if at all Eat at least five portions/servings (at least 400 g or 14 oz) of a variety of non-starchy vegetables and of fruits every day. Eat relatively unprocessed cereals (grains) and/or pulses (legumes) with every meal. Limit refined starchy foods People who eat red meat to consume less than 500 g (18 oz) a week, very little if any to be processed. If alcoholic drinks are consumed, limit consumption to no more than two drinks a day for men and one drink a day for women. Avoid salt-preserved, salted, or salty foods; preserve foods without using salt. Limit consumption of processed foods with added salt to ensure an intake of less than 6 g (2.4 g sodium) a day. Dietary supplements are not recommended for cancer prevention. These all sound pretty sensible but they are very prescriptive. And of course the recommendations make sense only insofar as the various dietary factors cause cancer. If the association is not causal, changing your diet won't help. Note that dietary supplements are NOT recommended. I'll concentrate on the evidence that lies behind "People who . . . very little if any to be processed." The problem of establishing causality is dicussed in the report in detail. In section 3.4 the report says " . . . causal relationships between food and nutrition, and physical activity can be confidently inferred when epidemiological evidence, and experimental and other biological findings, are consistent, unbiased, strong, graded, coherent, repeated, and plausible." The case of processed meat is dealt with in chapter 4.3 (p. 148) of the report. "Processed meats" include sausages and frankfurters, and 'hot dogs', to which nitrates/nitrites or other preservatives are added, are also processed meats. Minced meats sometimes, but not always, fall inside this definition if they are preserved chemically. The same point applies to 'hamburgers'. The evidence for harmfulness of processed meat was described as "convincing", and this is the highest level of confidence in the report, though this conclusion has been challenged ( Truswell, 2009) . How well does the evidence obey the criteria for the relationship being causal? Twelve prospective cohort studies showed increased risk for the highest intake group when compared to the lowest, though this was statistically significant in only three of them. One study reported non-significant decreased risk and one study reported that there was no effect on risk. These results are summarised in this forest plot (see also Lewis &amp; Clark, 2001) Each line represents a separate study. The size of the square represents the precision (weight) for each. The horizontal bars show the 95% confidence intervals. If it were possible to repeat the observations many times on the same population, the 95% CL would be different on each repeat experiment, but 19 out of 20 (95%) of the intervals would contain the true value (and 1 in 20 would not contain the true value). If the bar does not overlap the vertical line at relative risk = 1 (i.e. no effect) this is equivalent to saying that there is a statistically significant difference from 1 with P &lt; 0.05. That means, very roughly, that there is a 1 in 20 chance of making a fool of yourself if you claim that the association is real, rather than being a result of chance ( more detail here), There is certainly a tendency for the relative risks to be above one, though not by much, Pooling the results sounds like a good idea. The method for doing this is called meta-analysis . Meta-analysis was possible on five studies, shown below. The outcome is shown by the red diamond at the bottom, labelled "summary effect", and the width of the diamond indicates the 95% confidence interval. In this case the final result for association between processed meat intake and colorectal cancer was a relative risk of 1.21 (95% CI 1.04-1.42) per 50 g/day. This is presumably where the headline value of a 20% increase in risk came from. Support came from a meta-analysis of 14 cohort studies, which reported a relative risk for processed meat of 1.09 (95% CI 1.05 - 1.13) per 30 g/day ( Larsson &amp; Wolk, 2006). Since then another study has come up with similar numbers ( Sinha etal. , 2009). This consistency suggests a real association, but it cannot be taken as evidence for causality. Observational studies on HRT were just as consistent, but they were wrong. The accompanying editorial ( Popkin, 2009) points out that there are rather more important reasons to limit meat consumption, like the environmental footprint of most meat production, water supply, deforestation and so on. So the outcome from vast numbers of observations is an association that only just reaches the P = 0.05 level of statistical significance. But even if the association is real, not a result of chance sampling error, that doesn't help in the least in establishing causality. There are two more criteria that might help, a good relationship between dose and response, and a plausible mechanism. Dose - response relationship Doll &amp; Peto, 1978 There have been six studies that relate consumption of processed meat to incidence of colorectal cancer. All six dose-response relationships are shown in the WCRG report. Here they are. This Figure was later revised to This is the point where my credulity begins to get strained. Dose - response curves are part of the stock in trade of pharmacologists. The technical description of these six curves is, roughly, 'bloody horizontal'. The report says "A dose-response relationship was also apparent from cohort studies that consumption in I simply cannot that any relationship whatsoever is They are certainly the least dose-response relationships I have Nevertheless a meta-analysis came up with a for response that just the level of statistical significance. The conclusion of the report for processed meat and colorectal cancer was as is a of evidence, with a dose-response relationship apparent from cohort studies. There is strong evidence for plausible in meat is a cause of colorectal But the dose-response curves look and it is reasonable to ask whether public should be based on a 1 in 20 chance of being quite in 20 at best Senn, 2008). I certainly wouldn't want to risk my on like that, never it as a for public So we are with as the bit of evidence for causality. who has much experimental work knows that it is possible to up a plausible of any result Most are and so is a pretty play is of the fact that meats contain and but there is no real evidence that the they contain is The main source of in the diet is not from meat but from vegetables vegetables like and which - of The in processed meat is - but - 400 with a limit of - 400 Dietary intake was not with risk for colorectal cancer in two cohort 2004; for Research on 2006). to the another cohort study on over people compared and from and from all were not different between and meat ( et al., more the incidence of all was among than among meat the was colorectal cancer which a incidence in than in meat ( et al., et compared cohort studies and RCTs for of diet on risk of coronary heart disease. for was for intake of and and of intake of and foods with a There was also a bit less strong evidence for of and for intake of whole dietary and and But RCTs showed evidence only for and for of the As a final in the of case studies, to &amp; from a of case studies in association was between consumption (at least one of per and the risk of of the with relative risks of for and for for for and for on is one to make of should be on the Health to a reduction in As the authors may simply a general and of a It is observations like this that to make a of making causal inferences from studies. They are simply the observed association even The most about the of red meat and processed meat is not only that they are small but also that they only just the 5 level of statistical significance. It has been in these real are to be in size ( Senn, 2008). still, there as some good reasons to think that many (perhaps even of the that are in this sort of study are not real ( The of the of is to be in small studies, so it is that the large meta-analysis by Larsson &amp; Wolk, "In the present the of the relationship of processed meat consumption with colorectal cancer risk was than in the earlier This is all with the well tendency of randomized trials to show a good effect of but trials to show The reasons, and the for this worrying problem are discussed by ( &amp; &amp; 2009) do randomized studies tell The only of evidence for causality from randomised controlled The in people to over long of time are and that is no one reason why there are RCTs than there are observational studies. But when they have been the results often those from cohort studies. The RCTs of hormone replacement therapy above contradicted the cohort studies and the advice given to women about more illustrations of how plausible about diet can be by RCTs supplements and RCTs have shown that various of supplement do no good and may even do (see At least we now know that per do you no The that might be good for you was never more than a plausible and like so many plausible it has out to be a The is now no more than a though it very for unscrupulous The randomised Women's Health Initiative Dietary ( et al., showed of dietary on though the conclusion has been challenged on the of the possible of reported diet ( et al., 2006). to much about ( et al., 2009) no in over two years between very different They randomly overweight to one of The of from and in the were and and and and and difference could be between the different all that for was the number of It should be added, though, that there were some reasons to think that the may not have to their very well ( 2009). The one gets from RCTs is that the of diet are not like as important as has been inferred from observational studies. So does processed meat give you After all we can to the sausages or bacon give you colorectal The is that really I do know that, on the of the evidence, it seems to to be an to that evidence is that processed meat is a cause of In the there were 5 cases of colorectal cancer per 10,000 population in so a 20% even if it were real, and would result in 6 rather than 5 cases per 10,000 That makes the risk sound trivial for any the other there were cases of colorectal cancer in the in A 20% increase would if the association were causal, about cases as a result of eating processed but no cases if the association were not causal. For the purposes of public health about the question of causality is One has for the that they have to because they are to on the of If it were not already the discussed above make it very that the only sound to causality is a randomised The only to that are when are really The relative risk of lung cancer for a is 20 times that of a and there is a very relationship between dose per and response cancer as shown That is a increase in risk, very different from the 20% for processed meat (and many other dietary could the causality in that The about whether to eat bacon and sausages has to be a It depends on your to the principle. The observations do in my strong evidence for causality, but they are certainly with causality. It could be true so if you want to be on the then avoid course would not be much if your were based on things that just could be true. would be to any relative risk based on observational if it was less than about The Cancer Institute ( 2002) that relative risks less than should be with but to what with means in so the advice very In fact any of the relative risks reported in the WCRF report (2007) this all relative risks are less than (or than for it is best to worrying and get on with your At some point it to to diet on the of There is a to for being It the risk of making people that has a sound It the risk of of And it science into when people at the contradictory of observational The question of how diet and other health is to There is reason to think that it For example one study that breast cancer incidence increased in women who to and up to in the Since then has been put into out The great was but that is the only similar have come to after of and or and cancer count as The WCRF report (2007) has 537 and over and we don't I think we should don't rather more to Ben The of the Part 1 and Part and at Risk The and of about diet and supplements up the of seems to like the line at according to his blog. of the The report has been in Project This studies up to The result of of the was to reduce the apparent risk from eating processed meat from 1.21 (95% CI = 1.04-1.42) in the study to (95% CI = in the The is small to much, though it is in for the that the dose-response curves are The evidence for causality is by of the of processed meat and colorectal cancer

As we write the editorial for this edition, a very public row has broken out over the principal findings of the Million Women Study (MWS). It was this study, in combination with the principal findings of the Women’s Health Initiative (WHI), that completely transformed the opinion of professionals and patients worldwide with regard to almost any hormone therapy. Various estimates of the quantitative effect on hormone-replacement therapy (HRT) prescribing exist depending on the markets examined but it is clear that the overall effect is a halving in the use of HRT globally. It is highly likely that most HRT prescribers reduced the numbers of prescriptions immediately after the publication of these studies. Thus, was what many of us did right? Before we changed our prescribing habits or advice to patients, did we look at the data with the same level of scrutiny we would apply were we personally to be the ones about to start or continue therapy? Did we follow the investigators’ conclusions, or worse the conclusions from the media to influence our actions? Most of us recall the frenzy of sensationalism that accompanied these publications. Newspaper front pages screamed about the dangers of HRT and interviews with lead investigators promulgated their conclusions further. It was all too easy to take the path of least resistance and accept the indirect recommendations from investigators and press and the more direct guidance from some regulatory authorities. What we all should have done right from the start is to make our own minds up, either sit down, read the papers in detail or discuss them in a practice or multiprofessional meeting. Following the herd may have been the safest thing to do from a purely professional point of view but did we do the right thing for our patients? Without a doubt there may have been patients taking HRT who were not being regularly assessed and having their risk profiles assessed yearly who should have considered stopping. The worrying thing is the number of patients who had their treatment stopped suddenly without an option to discuss things further. With this probably well-intentioned risk-reducing manoeuvre, many women were plunged suddenly into a hormone-free hell. Many women suffered a significant and sudden reduction in quality of life, seeking out alternatives such as phytoestrogens and other drugs that are largely less well researched than HRT. It was easy to see the immediate effects on quality of life but other unwanted effects of cessation such as bone loss, vulvovaginal atrophy and short-term cognitive effects would take longer to present. Thus, what should we do with the reawakened debate about the validity of the MWS? Firstly, it should be considered that the recent publication does not actually provide new factual challenge to the MWS, it provides challenges to the methodological processes that lead to the main conclusion that HRT causes breast cancer. This conclusion has been challenged in several publications since the MWS was published and now adds further concern that the validity of the data and subsequent recommendations from regulatory authorities may need urgent review. Professionals new to the area of menopause are right to be confused. Have we been practising proper evidencebased medicine? Has there been a formal revision of the advice that arose from the main conclusions of the WHI and MWS? Whether a revision is needed or not we should all be practising an individualized approach to HRT prescribing, known risks and benefits should be carefully discussed prior to the decision to prescribe with effectiveness, tolerance and both shortand long-term effects monitored to facilitate continued prescription. What is urgently required is a formal expert group reappraisal resulting in a balanced assessment of whether women can feel safer on HRT and whether prescribers can have a greater degree of professional support from a regulatory body. In the meantime, please encourage colleagues to be aware of the debate, keep their professional ears to the ground and remain open to the possibility that HRT administration to the right woman at the right time in her life might actually be good for her.

Background: In 2002, trial by Women's Health Initiative that reported the long-term risks of hormone replacement therapy (HRT) of postmenopausal women. Combined estrogen and progestin hormone use outweighed the benefit for women health. This study aimed to examine the time trend and spatial patterns of HRT use and determine whether the declines occurred in Taiwan. Methods: The present study analyzed HRT utilization and influencing factors by the postmenopausal or osteopenic Taiwanese women. We investigated a case-control cohort analysis of a national health insurance (NHI) claimed dataset. NHI outpatient services claimed data of 82,478 beneficiaries aged above 40 had a principal diagnosis of postmenopause (ICD-9-CM Diagnosis Code 627) and osteopenia (ICD-9-CM Diagnosis Code 7330) were included in this study. HRT utilization trend was examined by different diagnostic codes, specialists, hospital level, hospital ownership, physicians' gender and age, also patients' resident area. The geographic variations of HRT use were obtained from 6 national insurance branches to compare the utilization rates before and after 2002. The highest use of HRT of region (eastern branch) was selected with 2,447 cases to compare the risk of usage and duration of HRT. Spatial patterns of rate change of breast cancer incidences between 1998-2002 and 2003-2008 were obtained from Taiwan Cancer Registry to examine changes in spatial trends in relations to HRT use and high mammography screening hospitals. Results: A reduced frequency of use of HRT was reflected in the decrease in hormone prescriptions after 2002. The largest drop was occurred between 2002 and 2003(from 51.5% to 37.9% in 2003). Similar reducing trend of use HRT was also showed in different specialists (8.1% drop in Obstetrics &amp; Gynecology, 4% drop in Orthopedics and 12.8% drop in other department between 2002 and 2003). The HRT use rate for women visited clinic in 2002 and 2003 dropped from 56.2% to 42.8%, but slow decrease between 2004 to 2007 (37.3% in 2004, 34.8% in 2005, 35.0% in 2006 and 34.7% in 2007). There are slight increase use rate between 2005 and 2006. In 2008, there was another larger drop of 3.4%. The eastern branch compared with other branches between two period of time (2000-2002 and 2003-2008). Relative risk of 1.47 (95% CI: 0.72-3.00) before 2002 and 1.57 (95% CI: 0.81-3.11) after 2002. Spatial patterns showed the increasing breast risks in central and southern region (rural area) compare with northern region (metropolitan area). The increase of age-adjusted incidence rate in central and southern region outweighed the increase rate of HRT use. In the contrast to these regions, an increasing rate of HRT use did not observe the similar effect in northern metropolitan regions. Discussion: To our knowledge, this is the first Taiwan study to examine the link between population-level declines in use of hormone replacement therapy among postmenopausal women with different levels of utilization. Spatial observation was also indicated the different between breast incidence and HRT use in Taiwan. Spatial observation found the different pattern change between HRT use and breast incidence rate in term of geographic prospect and urbanization level. Further long-term investigation to determine whether the geographic accessibility and availability of breast screening programs do affect the ascending breast cancer risk. Citation Format: Po-Huang Chiang, Eng-Mei Tsai, Yen-Chen Chang. Time trend and spatial pattern in the use of hormone replacement therapy in Taiwan before and after WHI trial report. [abstract]. In: Proceedings of the Eleventh Annual AACR International Conference on Frontiers in Cancer Prevention Research; 2012 Oct 16-19; Anaheim, CA. Philadelphia (PA): AACR; Cancer Prev Res 2012;5(11 Suppl):Abstract nr A112.

The Women's Health Initiative (WHI) hormone replacement therapy (HRT) estrogen plus progestin (E+P) and estrogen-only arms are part of a large NIH-sponsored randomized controlled trial (RCT). Both arms were terminated prematurely after 5 and 8 yr, respectively. The E+P arm showed non-statistically significant increased incidences of cardiovascular events and breast cancer, whereas the E-only arm did not. Both arms showed an increased rate of thromboembolic events and stroke. Both arms showed protection against fractures and with protection against colon cancer only in the E+P arm. These results have been widely generalized as indicating a negative risk/benefit ratio for HRT in menopausal women. The WHI results are at odds with results of large epidemiological studies that showed protection against cardiovascular disease. Although the latter data are, in part, confounded by a "healthy user bias," much of the inconsistency may be explained by the fact that women in the latter studies initiated HRT at the menopausal transition, whereas the WHI trial was conducted in older women (mean age 63.3), who were, on average, approx 12 yr postmenopausal. In addition, older trials included women on either unopposed estrogen therapy (ERT) or cyclic HRT regimens. Whatever other forces may have been at work, observational and experimental evidence supports the conclusion that estrogen's atheropreventive effects predominate early, in the absence of vulnerable plaque to be ruptured or thrombotic episodes propagated by narrowed lumens and intravascular turbulence. On the contrary, age-related adverse effects of HRT may prevail once complex atheromas and luminal narrowing/irregularity are established. It is known that prevalence of subclinical "at-risk" atherosclerotic lesions increases in women during the first 5-10 yr after menopause. Furthermore, animal and clinical evidence supports the use of lower doses of estrogen than were employed in the WHI in older/longer postmenopausal women.

As shown in Figure ​Figure1,1, a wide range of epidemiologic and observational data suggest that oestrogens are associated with the development of breast cancer [1,2]. With these data as a background, it was quite surprising that recently published data suggested that women taking postmenopausal hormone therapy (MHT) with oestrogen alone for 5 to 9 years unexpectedly experienced a decrease in the risk for breast cancer [3,4]. However, when taken for more than 20 years, the risk appeared to increase [5,6]. We call this the 'oestrogen paradox' to highlight the fact that short-term oestrogen use decreases the risk for breast cancer whereas long-term use increases it. A second component of the oestrogen paradox is that high-dose oestrogen therapy in postmenopausal women with breast cancer causes tumour regression, whereas the anti-oestrogen tamoxifen is equally effective in causing remissions in similar patient groups [7-9]. It is paradoxical then that both oestrogens and anti-oestrogens cause tumour regressions. Figure 1 Hormonal risk factors associated with an increased risk of breast cancer and related to oestrogen exposure. For references supporting the validity of this figure, see Santen [1]. E, oestrogen; E2, oestradiol; HRT, hormone replacement therapy; OOX, oophorectomy; ... Short-term oestrogen use and breast cancer risk The initial publication of the Women's Health Initiative (WHI) [3] reported a 23% decrease in invasive breast cancer incidence in patients taking oestrogen alone compared with placebo, a finding which narrowly fell short of statistical significance (hazard ratio [HR] 0.77, 95% confidence interval [CI] 0.59 to 1.01). A recent exploratory analysis of updated data from this study examined subgroups to determine whether oestrogens might reduce the incidence of breast cancer significantly in women falling into certain categories [4]. Notably, this analysis reported a statistically significant 33% reduction in invasive breast cancer incidence in patients who strictly adhered to their oestrogen therapy (HR 0.67, 95% CI 0.47 to 0.97). In addition, a 31% lower incidence of localized breast cancer (HR 0.69, 95% CI 0.51 to 0.95) and a 29% reduction in ductal cancers (HR 0.71, 95% CI 0.52 to 0.99) were reported in oestrogen users. The decreases in breast cancer risk were limited to women who had not previously used MHT [4]. In a concurrent report from the Nurses Health Study [2], a significant 26% decrease in risk for breast cancer was observed in obese women, and a nonsignificant 10% decrease in all study participants, taking oestrogen alone for 5 to 9 years. Other observational studies reported a reduction in risk with oestrogen alone but of lesser magnitude and not statistically significant. For example, Schairer and colleagues [5] reported a 7% reduction in breast cancer risk at 6 years in women receiving oestrogen alone, and Lyytinen and coworkers [10] identified a similar 7% reduction. These combined results, although not conclusive, are highly suggestive of a beneficial effect of oestrogen in reducing breast cancer risk. However, this conclusion must be considered provisional until rigorous confirmation in additional studies is reported.

Over the last decade, several large-scale randomized trials have reported results that disagreed substantially with the motivating observational studies on the value of various chronic disease–prevention strategies. One high-profile example of these discrepancies was related to postmenopausal hormone therapy (HT) use and its effects on cardiovascular disease and cancer. The Women’s Health Initiative (WHI), a National Heart, Lung, and Blood Institute–sponsored program, was designed to test three interventions for the prevention of chronic diseases in postmenopausal women, each of which was motivated by a decade or more of analytic epidemiology. Specifically, the trials were testing the potential for HT to prevent coronary heart disease (CHD), a low-fat eating pattern to reduce breast and colorectal cancer incidence, and calcium and vitamin D supplements to prevent hip fractures. Over 68,000 postmenopausal women were randomized to one, two, or all three randomized clinical trial (CT) components between 1993 and 1998 at 40 U.S. clinical centers (Anderson et al., 2003a). The HT component consisted of two parallel trials testing the effects of conjugated equine estrogens alone (E-alone) among women with prior hysterectomy and the effect of combined estrogen plus progestin therapy (E+P), in this case conjugated equine estrogens plus medroxyprogesterone acetate, among women with an intact uterus, on the incidence of CHD and overall health. In 2002, the randomized trial of E+P was stopped early, based on an assessment of risks exceeding benefits for chronic disease prevention, raising concerns among millions of menopausal women and their care providers about their use of these medicines. The trial confirmed the benefit of HT for fracture-risk reduction but the expected benefit for CHD, the primary study end point, was not observed. Rather, the trial results documented increased risks of CHD, stroke, venous thromboembolism (VTE), and breast cancer with combined hormones (Writing Group for the Women’s Health Initiative Investigators, 2002). Approximately 18 months later, the E-alone trial was also stopped, based on the finding of an adverse effect on stroke rates and the likelihood that the study would not confirm the CHD-prevention hypothesis.

Menopause symptoms are often debilitating, affecting personal, social and professional quality of life. The majority of women use hormone replacement therapy (HRT) for valid reasons having carefully weighed up the...

Design of the Women’s Health Initiative Clinical Trial and Observational Study

The last 5 years of trial data demonstrate the ineffectiveness of hormone replacement therapy (HRT). The impact of these trials on age-specific HRT use, HRT discontinuation, and regional HRT variation has not been evaluated extensively. To characterize the relation between HRT trial dissemination and age-specific HRT use, HRT discontinuation, and regional HRT variation before and after the trials' publication. Using the Medco Health database, we analyzed HRT prescription filling, discontinuation, and regional variation among women > or =55 years from May 1998 to May 2003. Approximately 340,000 women were eligible for Medco benefits each month. Within 3 months of the Women's Health Initiative (WHI), HRT prescriptions declined from 12.5% to 9.4%, P< or =.0001. When stratified by age, a statistically significant decline in HRT post-WHI occurred in all age groups, with the biggest decline among women > or =55 to 64 (18% to 11%, P< or =.0001). Among HRT users, we found statistically significant increases in discontinuation in 2002 (67%) compared with 2001 (53%, P<.0001). Prior to the WHI there was substantial regional variation in HRT use, with the West South Central and mid-Atlantic having the highest and lowest proportions, respectively (19% vs 6%, P< or =.0001). Despite a relative decline in HRT use of 25% to 42% across all regions, substantial geographic variation remained. Hormone replacement therapy use decreased significantly immediately post-WHI, suggesting that trial results can have a rapid effect on practice. Marked regional variation in HRT use persisted after the WHI, suggesting that local practice patterns exert a strong effect on clinical behavior even after new evidence is available.

Hormone replacement therapy and the risk of ovarian cancer in BRCA1 and BRCA2 mutation carriers

PII: S0140-6736(03)14599-0