14 August 2017: 

In this ageing world, the field of the 'epidemiology of longevity' has been expanding rapidly in recent years. With a dramatic increase in survival rate to advanced old age over the past century, longevity can be described as an epidemic. Many studies have evaluated the impact of factors such as low socioeconomics in childhood, genetics, environmental, dietary and lifestyle (smoking and alcohol use), which negatively affect longevity. Although mortality rates for females are lower at each age than those of men, a close association between reproductive characteristics and longevity was recently documented. 

Several reproductive factors, such as the age at first birth, parity and age of menopause, have been found to be associated with women's longevity. The recent prospective (WHI) study, in a large multi-ethnic cohort of postmenopausal women, examined 20,248 women from 40 clinical centers (aged 50–79 years, mean age at baseline 74.6 years); 10,909 (54%) of these women survived to age 90 years [1]. The odds of longevity were significantly higher in women with later age at first childbirth (adjusted odds ratio 1.11; 95% confidence interval 1.02–1.21 for age 25 years or older vs. younger than 25 years; p for trend = 0.04). Among parous women, the relationship between parity and longevity was significant among White but not Black women, while women with two to four term pregnancies compared with one term pregnancy had higher odds of longevity. This long-term, follow-up study reported that a rising number of pregnancies were associated with higher likelihood of longevity in the participants who survived to the age of 90 years. It was pointed that this was independent of demographic characteristics, socioeconomic position, lifestyle behaviors, reproductive factors and health-related factors. Despite these strengths, the authors pointed at a limitation of the study: women included in this study were on average aged 75 years at enrolment and may have had a higher likelihood of achieving longevity as they had already survived to their seventies. Also, with respect to historical events, participants may have had different experiences that may have influenced their life expectancy. So, because of potential selection bias, this cannot be applicable to the general population of childbearing women.

31 July 2017: 

Pharmacogenomics is the study of how genes affect a person's response to drugs. This relatively new field combines pharmacology and genomics (the study of genes and their functions) to develop effective, safe medications and doses that will be tailored to a person's genetic make-up [1]. Many drugs that are currently available are 'one size fits all', but they don't work the same way for everyone. It can be difficult to predict who will benefit from a medication, who will not respond at all, and who will experience negative side-effects. Pharmacogenomics aims to develop rational means to optimize drug therapy, with respect to the patient's genotype, and to ensure maximum efficacy with minimal adverse effects.

Personalized management of menopausal symptoms and other menopause-related disorders should be based, among other variables, on pharmacogenomics. One main example is hormone therapy (HT), as nicely discussed in the Editorial by Moyer and colleagues [2]. Typically, dosing is targeted toward symptom relief, but there is significant variability in the doses required for symptom relief among women. In addition, if therapy is needed not only for symptoms but also for prevention of chronic diseases of old age, such as osteoporosis or cardiovascular diseases, then the effective doses might be different. Pharmacogenomic approaches may help identify women with different estrogen-dose requirements based on identification of genetic variants in enzymes involved in hormone/drug metabolism and impacting hormone/drug targets. The Kronos study provided data on the impact of genetic variations on the development of atherosclerosis in healthy, recently menopausal women receiving HT [3].

24 July 2017: 

Since its launch in 2008, the web-based fracture risk assessment tool FRAX^® [1] has been evaluated thoroughly in additional validation studies and widely published in meta-analyses and clinical review papers. Furthermore, its predictive and discriminative powers have been compared with other osteoporotic fracture risk prediction tools [2]. Two recent papers elucidate different aspects of the tool, one assessing its diagnostic accuracy in women and men from five different non-US populations [3], the other one calculating the time to 'clinically relevant' risk scores in US postmenopausal women [4], and both using the 10-year intervention thresholds of 20% for major osteoporotic fractures (MOF) and 3% for hip fractures (HF), as suggested by the National Osteoporosis Foundation (NOF) [5].

In the first paper, a systematic review and meta-analysis of seven studies from New Zealand, Canada, the USA, France and Poland, which tested FRAX^® in populations other than the derivation cohorts, the tool 'performed better in identifying patients who will not have a MOF or HF within 10 years, than those who will. A substantial number of patients who developed fractures, especially MOF within 10 years of follow-up, were missed by the baseline FRAX^® assessment', as stated by the authors in their conclusion.

For MOF prediction, the mean sensitivity, specificity, and diagnostic odds ratio (DOR) along with their 95% confidence intervals (CI) were 10.25% (3.76–25.06%), 97.02% (91.17–99.03%) and 3.71 (2.73–5.05); for HF prediction 45.70% (24.88–68.13%), 84.70% (76.41–90.44%) and 4.66 (2.39–9.08), respectively, the latter one being less precise because of its larger confidence region.

FRAX^® is freely available and easy to use, not least because of its condensed and time-saving features. But this is at the expense of its sensitivity. Tools with a larger number of clinical risk factors, e.g. QFracture^®, may be more sensitive but less feasible [2]. Lowering the intervention threshold may also improve sensitivity but increase over-treatment [6].

The second paper estimates the timing of occurring ‘clinically relevant’ scores, i.e. treatment-level FRAX^® scores, according to 2014 National Osteoporosis Foundation guidelines [5], and screening-level FRAX^® scores, according to 2011 US Preventive Services Task Force (USPSTF) guidelines [7], in postmenopausal women of the Women’s Health Initiative (WHI) cohort.

17 July, 2017: 

Several guidelines have been reported for bone-directed treatment in women with early breast cancer for averting fractures, particularly during aromatase inhibitor (AI) therapy. A systematic literature review identified both several fracture-related risk factors as well as recent advances in the management of aromatase inhibitor-associated bone loss (AIBL). Although the FRAX algorithm includes fracture risk factors in addition to bone mineral density (BMD), it does not seem to adequately address the effects of AIBL. Several antiresorptive agents can prevent and treat AIBL. However, concerns regarding compliance and long-term safety remain. Overall, the evidence for fracture prevention is strongest for denosumab 60 mg s.c. every 6 months. Additionally, recent studies as well as an individual patient data meta-analysis of all available randomized trial data support additional anticancer benefits from adjuvant bisphosphonate treatment in postmenopausal women, with a 34% relative risk reduction in bone metastasis and 17% relative risk decrease in breast cancer mortality that needs to be taken into account when advising on management of AIBL.

A Joint Position Statement of the International Osteoporosis Foundation, the Cancer and Bone Society, the European Calcified Tissue Society, the International Expert Group for AIBL, the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases, the International Society for Geriatric Oncology and the International Menopause Society recently provided a treatment algorithm [1]. In all patients initiating AI treatment, fracture risk should be assessed and recommendation with regard to exercise and calcium/vitamin D supplementation given. Bone-directed therapy should be given to all patients with a T-score <−2.0 or with a T-score of < –1.5 SD with one additional risk factor, or with two or more risk factors (without BMD) for the duration of AI treatment. Patients with a T-score > −1.5 SD and no risk factors should be managed based on BMD loss during the first year and the local guidelines for postmenopausal osteoporosis. Compliance should be regularly assessed as well as BMD on treatment after 12–24 months. Furthermore, because of the decreased incidence of bone recurrence and breast cancer-specific mortality, adjuvant bisphosphonates are recommended for all postmenopausal women at significant risk of disease recurrence.

Comment

The use of adjuvant endocrine therapy in women with hormone-sensitive breast cancer is divided, usually by menopausal status, between the selective estrogen receptor modulator tamoxifen and the newer class of drugs known as aromatase inhibitors. The latter are indicated in postmenopausal women only. A Cochrane systematic review [2] found that disease-free survival and overall survival were improved with AI monotherapy compared to tamoxifen. Sequenced therapy with AI to tamoxifen (or vice versa) improved disease-free survival compared to tamoxifen but not overall survival. Fractures were more frequently associated with AI use. Thromboembolic disease and endometrial cancer were more frequently associated with tamoxifen use. AIs have largely replaced tamoxifen in adjuvant treatment of postmenopausal hormone receptor-positive breast cancers.

10 July, 2017: 

The radiographic appearance of the breast on mammography varies among women. Fat appears dark on a mammogram, whereas connective and epithelial tissues are radiologically dense and appear white. This is the basis for determining the mammographic density, and the relative percentage of dense versus lucent breast areas (percent mammographic density, PMD). It has been well established that parameters of breast density correlate with breast cancer risk, with a four- to six-fold-fold gradient in risk between women with 75% or more PMD compared with those with 10% or less [1]. A systematic meta-analysis of data for more than 14,000 cases and 226,000 non-cases from 42 studies found that greater PMD was consistently associated with an increased risk of breast cancer [2]. No differences were observed by age/menopausal status at mammography or by ethnicity. For PMD using pre-diagnostic mammograms, combined relative risks of incident breast cancer in the general population were 1.79 (95% CI 1.48–2.16), 2.11 (95% CI 1.70–2.63), 2.92 (95% CI 2.49–3.42), and 4.64 (95% CI 3.64–5.91) for categories 5–24%, 25–49%, 50–74%, and greater than or equal to 75% relative to less than 5%. While this generalized notion is actually 'old news', there might be, in fact, some deviations from the core principle, which relate to the exact parameter evaluated, the characteristics of the cohort and the technique of density measurement. Some studies picked breast density as the main tested parameter, whereas others used PMD, or changes over time in density or in PMD. As an example, in a study of 6710 women aged 40–49 at intermediate familial risk of breast cancer (average lifetime risk of 23%), the absolute density, but not percent density, was a significant risk factor for breast cancer after adjusting for area of non-dense tissue (OR per 10 cm² = 1.07, 95% CI 1.00–1.15, p = 0.04) [3]. The effect was stronger in premenopausal women, who made up the majority of the study population. Absolute density remained a significant predictor of breast cancer risk after adjusting for age at menarche, age at first live birth, parity, past or present hormone replacement therapy, and the Tyrer-Cuzick 10-year relative risk estimate of breast cancer. Eng and colleagues drew attention to the potential impact of the mammography technique on the measured density [4]. They pointed out that there is currently no validated estimation method for full-field digital mammography, while differences in the obtained results may occur if various techniques are compared.

26 June 2017: 

Mikkola and colleagues examined the association between use of hormone therapy (HT) and death from Alzheimer’s disease (AD) or vascular dementia (VaD) in a sample of 489,105 Finnish women who had documented use of systemic HT on a nationwide drug reimbursement register [1]. A nationwide Finnish death register indicated that 1057 of those women died of AD and 581 died of VaD. Findings revealed that, compared to population averages, women who used HT for at least 5 years had a 15–19% reduced risk of death from AD, and use of HT for any period of time was associated with a 37–39% reduced risk of death from VaD. No reduction in AD was observed among women who used HT for less than 5 years, nor did age at initiation (< 60 years versus > 60 years) influence risk of AD or VaD.

Comment

Concern about the risks of dementia with HT stems primarily from the Women’s Health Initiative Memory Study (WHIMS), which showed a doubling of the risk of all-cause dementia with conjugated equine estrogen (CEE) and medroxyprogesterone acetate (MPA) [2]. These findings were observed in a sample of women aged 65 years and older, and questions regarding the generalizability of those findings to younger women and to other formulations of HT have been the topic of much debate. A definitive answer to those questions is unlikely to be determined, as it is not feasible to conduct a long-term, large-scale, randomized, controlled trial of HT for primary prevention of dementia among early postmenopausal women. For that reason, we must rely on observational studies to guide understanding of HT and dementia.

Observational studies of HT and dementia risk focus primarily on AD, the most common form of dementia, and less on VaD, the second most common form of dementia. Meta-analyses of HT and AD risk generally provide support for the view that HT lowers AD risk [3,4]. However, observational studies, particularly those in the United States, are difficult to interpret because of the healthy-user bias, the tendency for women who use HT to be healthier and better educated than those who do not use HT, and the tendency to rely on self-report of HT exposure (not optimal for a memory study!). Additionally, the most common form of HT used in those studies is CEE with or without MPA and little is known about estradiol, which is used widely outside of the United States.

12 June 2017

Cardiovascular disease is the leading cause of morbidity and mortality in postmenopausal women [1]. Hormone replacement therapy (HRT) has been shown to reduce future risk of cardiovascular disease when taken within 10 years of the menopause. Avoiding HRT in menopausal women can actually be detrimental to their health. Some experts are now recommending that HRT should be considered as part of a general prevention strategy for women at the onset of the menopause [2]. However, some doctors and nurses feel very apprehensive about this as they are confused about the association of HRT with cardiovascular disease (CVD).

The negative publicity regarding the misinterpretation in the media of the Women’s Health Initiative (WHI) study has led to many women and health-care professionals still being concerned and anxious about the potential risks of HRT [3], in particular regarding HRT and cardiovascular disease (CVD). A large proportion of doctors are still informing women that HRT is associated with a greater risk of CVD and are refusing to prescribe HRT for women who would actually benefit from taking it. Many women with hypertension are still being told to stop taking their HRT. This misperception is resulting in large numbers of women needlessly enduring menopause symptoms and also increasing their future risk of osteoporosis, cardiovascular disease and diabetes by not taking HRT.

8 May, 2017: 

Hot flushes, which are among the most frequent symptoms of menopause, are considered to be the result of the changes in the sex hormone milieu and tissue exposure at midlife and beyond. However, modern medicine tries also to tie physiological processes with the individual gene profile. This was also done in regard to vasomotor symptoms (VMS) in the WHI study, in search of potential associations between VMS and certain genetic variations and single nucleotide polymorphisms (SNPs). After adjustment for bilateral oophorectomy, age, smoking, alcohol intake, physical activity, population structure, body mass index, education, income, and menopausal hormone therapy use, 14 SNPs were associated with increased odds of VMS at a p value threshold < 5 × 10-8 [1]. These 14 SNPs are located within the same region of chromosome 4, the gene which encodes tachykinin receptor 3 (TACR3), and neurokinin B (NKB), a member of the tachykinin family of peptides, preferentially binds to NK3R. NKB mRNA-expressing neurons are located predominantly in the infundibular nucleus and the anterior hypothalamic area. In humans, NKB neurons co-localize with the gonadotropin releasing hormone tract in the infundibular stalk, and the NKB pathway is implicated in pubertal development and hypogonadatropic hypogonadism. Another study showed that the expression of tachykinins and their receptors in the mouse uterus are tightly and differentially regulated by ovarian steroids [2]. Estrogen effects are mainly mediated by estrogen receptor alpha, supporting an essential role for this estrogen receptor in the regulation of the tachykinergic system in the mouse uterus. Furthermore, menopause and/or oophorectomy are associated with changes in NKB gene expression: in the human infundibular nucleus it increases after menopause, and in monkeys and rats ovariectomy induces similar increases in NKB gene expression that are reversed by estradiol therapy [3].

10 April, 2017: 

The title of this commentary is not a joke. Marital status seems to have a major impact on health. Traditionally, stability in intimate relations has positive effects on health and quality of life parameters, especially in old age. This assumption even translates into smaller insurance costs of married versus divorced persons. But recent data from the WHI observational study now challenges this accepted belief [1]. Among 79,094 postmenopausal women, transitions into marriage/marriage-like relationship after menopause were associated with greater increase in body mass index (BMI) and alcohol intake relative to remaining unmarried. Divorce/separation was associated with a reduction in BMI and waist circumference, changes that were accompanied by improvements in diet quality and physical activity, relative to women who remained married. The message coming from these results is that, contrary to earlier literature, in a cohort of well-educated, predominantly non-Hispanic white women, marital transitions after menopause are accompanied by modifiable health outcomes/behaviors that are more favorable for women experiencing divorce/separation than those entering a new marriage.

Comment

Marital status is a major parameter in every history-taking that health-care providers do. Thousands of articles have displayed all aspects of quality of life in health, as well as the potential impact on various disease situations adjusted to the marital status. Having a partner and intimate relations are considered as health promotors, while accordingly, marital disruption is perceived as a negative factor. For example, most studies on cardiovascular disease showed better outcomes for married persons, and men who were single generally had the poorest results [2]. Moreover, being married was associated with lower risk factors and better health status, even in the presence of many confounding effects. Physiological processes, such as cardiovascular reactivity, hormonal functionality, inflammatory manifestations and sleep patterns behave differently in the subsets of marital status, and so do many psychological variables [3, 4]. Even bone density was mentioned in this respect, as marriage before age 25 and marital disruptions seem deleterious to bone health in men, whereas marital quality was associated with better bone health in women [5].

24 April, 2017: 

A friend has just told me that sleep is a waste of time, because every minute being awake does count and should be used to enjoy life. Well, I guess he was wrong, since sleep is mandatory not only for relaxation, but also for the initiation of many active neuro-physiological processes which are vital. Extreme and prolonged deprivation of sleep may even eventually lead to death. The duration of sleep seems an important factor in maintaining optimal health. There is a consensus that a 7-hour night sleep should be recommended [1], whereas shorter or longer sleeps might be associated with a higher rate of health derangements and mortality risk [2]. Although there is probably no gender difference in the impact of sleep duration, herein are some clinical data related to women and menopause.

Cardiovascular disease: In the Women's Health Initiative observational study (n = 86,329; 50–79 years old, 10.3 years follow-up), shorter (5 h or less) and longer (10 h or more) sleep duration demonstrated significantly higher incident coronary heart disease (CHD) (25%) and cardiovascular disease (19%) in age- and race-adjusted models, but this was not significant in fully adjusted models [3]. Women with long sleep demonstrated the greatest risk of incident CHD compared to midrange sleep duration (hazard ratio =1.93, 95% CI 1.06–3.51) in fully adjusted models.

Hypertension: The Nurses' Health Study investigated the relationships between sleep duration and hypertension among women whose sleep durations were self-reported (n = 84,674) [4)]. The prevalence of hypertension was significantly higher among women who slept 5 h or less per night (odds ratio = 1.19, 95% CI 1.14–1.25) compared with 7 h, but further analysis showed that this association was only seen in those aged < 50 years.

Diabetes mellitus: A recent study used data from the China Kadoorie Biobank, coming from a rural county [5]. Sleep duration was shown to have a U-shaped association with diabetes in 33,677 women, in particular in postmenopausal women after adjustment for potential confounders. Compared with 7-h sleepers, odds ratios of sleep duration 5 h or less and 10 h or more for diabetes were 1.32 (95% CI 1.02–1.69) and 1.30 (95% CI 1.03–1.65), respectively.

Cancer: The WHI observational study showed that deviation from the ideal 7-h night sleep increases the risk for colorectal cancer [6]. There were 851 incident cases with an average 11.3 years of follow-up. Compared with 7 h of sleep, the hazard ratios were 1.36 (95% CI 1.06–1.74) and 1.47 (95% CI 1.10–1.96) for short (5 h or less) and long (9 h or more) sleep duration. The Nurses' Health Study experience was summarized as 'no convincing evidence for an association between sleep duration and the incidence of breast cancer' [7]. In few other studies, results were mixed, either a small reduced risk or a small increased risk for women who deviated from the optimal sleep duration.

Cognition: Both the Nurses' Health and WHI studies demonstrated an adverse impact of shorter or longer sleep durations on cognitive function [8]. Also, women whose sleep duration changed by 2 h or more per day over time had worse cognition than women with no change in sleep duration.

To note, despite statistically significant associations between sleep duration and many health aspects, the excessive risks are relatively small or modest, when converted into absolute numbers. Still, sleep is needed for maintaining our normal physiology, and keeping the recommended schedule of a 7-h sleep duration per night will probably promote better health.