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25 September 2017: 

The saga of the Women's Health Initiative (WHI) seems to have come to a turning point with a declaration that should vibrate now throughout the whole world. A new release of data from the WHI study has concluded that 'Among postmenopausal women, hormone therapy with CEE [conjugated equine estrogen] plus MPA [medroxyprogesterone acetate] for a median of 5.6 years or with CEE alone for a median of 7.2 years was not associated with risk of all-cause, cardiovascular, or cancer mortality during a cumulative follow-up of 18 years' [1]. Amazing as it is, the safety concerns that were attributed in the past to menopausal hormone therapy (MHT) need to be re-considered and to be put in their right perspective. It is not necessary to present again the main features of the CEE + MPA and the CEE-alone randomized studies.

The main issues discussed by the WHI investigators included the following:

• The present report is based on mortality follow-up through December 2014 and includes 7489 deaths (1088 occurred during the intervention phase and 6401 occurred post-intervention; 4083 additional deaths had occurred since the last report). For the CEE + MPA trial, the median post-intervention follow-up was 12.5 years and the cumulative follow-up was 18 years; for the CEE-alone trial, the median post-intervention follow-up was 10.8 years and the cumulative follow-up was 18 years.
• During the intervention phase, all-cause mortality in the pooled cohort was 4.0% with hormone therapy vs. 4.0% with placebo. Compared with placebo, women randomized to receive CEE + MPA had a hazard ratio (HR) of 0.97 (95% confidence interval (CI) 0.82–1.16) and women randomized to receive CEE alone had a HR of 1.04 (95% CI 0.89–1.22). During the post-intervention period, the HR for all-cause mortality was 1.04 (95% CI 0.97–1.10) for CEE + MPA and 0.92 (95% CI 0.85–0.99) for CEE alone.
• The HRs for all-cause mortality tended to differ by age during the intervention and cumulative follow-up phases. Comparison of women aged 50–59 years with those aged 70–79 years showed that the risk was significantly lower for the younger age group, as ratios of nominal HRs for all-cause mortality in the pooled cohort were 0.61 (95% CI 0.43–0.87) during the intervention phase and 0.87 (95% CI 0.76–1.00) during cumulative 18-year follow-up, without significant heterogeneity between trials. Although younger women tended to have lower HRs than older women for mortality due to cardiovascular disease (CVD), cancer, and other (non-CVD, non-cancer) causes during the intervention phases of the two trials, only the latter outcome in the CEE-alone trial showed a statistically significant trend with age (p for trend by age = 0.002). During cumulative follow-up, trends in cause-specific mortality across age groups were not statistically significantly different.

In the Discussion section, the investigators had several important comments as well. They claimed that no other randomized clinical trial of hormone therapy has been large enough to assess a potentially modifying effect of age on all-cause mortality. They noted that observational studies, which primarily include women who initiate hormone therapy in early menopause, have generally demonstrated lower mortality among women using hormone therapy compared with non-users. HRs in most large cohort studies have ranged from 0.40 to 0.80. Regarding cause-specific mortality, the most marked risk reductions reported in observational studies have been for coronary or CVD deaths. Total cancer mortality did not differ significantly between intervention and placebo groups in either trial despite the increased incidence of breast cancer with CEE + MPA. However, a significant reduction in breast cancer was seen with CEE. Divergent findings for CEE alone and CEE + MPA for breast cancer point to an adverse effect of progestin on the breast epithelium, but progestins have been linked to favorable effects on the endometrium, and a decreased risk of endometrial cancer became apparent with long-term follow-up of the CEE + MPA trial. Last, but not least, it was mentioned that only one dose, formulation and route of administration in each trial were assessed; thus, results cannot necessarily be generalized to other hormone preparations.

18 September 2017: 

Several recent publications have raised again the complex association between menopause, glucose handling and insulin status, type 2 diabetes and hormone replacement (HRT/MHT). Interestingly, a cohort of 3639 postmenopausal women from Rotterdam, followed for 9.2 years, revealed a clear statistical correlation between the age at natural menopause and the future risk of becoming diabetic [1]. Hazard ratios (HRs) for type 2 diabetes were 3.7 (95% CI 1.8–7.5), 2.4 (1.3–4.3) and 1.60 (1.0–2.8) for women with premature (< 40 years), early (40–44 years) and normal menopause (45–55 years), respectively, relative to those with later menopause (p_trend < 0.001). The HR for type 2 diabetes per 1 year older at menopause was 0.96 (0.94–0.98). The investigators concluded that early onset of natural menopause is an independent marker for type 2 diabetes in postmenopausal women. These findings certainly raise again the discussion over the relevance of the hormonal changes around the menopause vis-a-vis the metabolic pathways involved in glucose metabolism and the development of insulin resistance and type 2 diabetes. It also puts forward the potential consequences of HRT in this respect.

The 2017 position statement on the menopause that was issued by the American Association of Clinical Endocrinologists and the American College of Endocrinology includes a section on type 2 diabetes [2]. The main points were:

(1) Women without diabetes at baseline: spontaneous menopause has not been associated with an increased risk of diabetes; evidence from observational trials suggested a neutral or slightly beneficial effect of estrogen on glucose metabolism; in randomized controlled clinical trials, including HERS (women with known cardiovascular disease), blood glucose levels did not rise over time in estrogen-treated women, and fewer women with impaired fasting glucose at study onset progressed to overt diabetes. In younger, non-diabetic women in the shorter KEEPS trial, no effect of conjugated estrogen was seen, while transdermal estrogen-treated subjects showed a modest reduction in blood sugar. In the WHI, there was a 21% reduction in diabetes incidence over time in women treated with estrogen/progesterone therapy, but this effect was limited to the age group 50–69 years old; in the estrogen-only arm of the WHI, the incidence of diabetes in treated women was 12% less than in controls at all age groups.

(2) Women with diabetes at baseline: in observational studies, treatment with HRT has resulted in either neutral or beneficial effects on glucose levels in patients with pre-existent type 2 diabetes.

11 September 2017: 

The word 'LASER' is an acronym for 'Light Amplification by Stimulated Emission of Radiation'. Laser light energy has been widely used for different medical and surgical indications. Different light sources are available for the laser practitioner. In the last years, a number of publications have appeared and vaginal laser has gained interest as a treatment for genitourinary syndrome of menopause (GSM) and as an option for stress urinary incontinence (SUI) [1-10].

The carbon dioxide (CO2) laser is the first-generation laser for GSM treatment. In 2011, Gaspar and colleagues [1] first demonstrated that vaginal fractional CO2 laser treatment induced a significant improvement in clinical and histological signs of vaginal atrophy. Subsequently, in a pivotal paper, Salvatore and colleagues [2] reported a 12-week study where symptoms were analyzed before and after three sessions (one per month) of fractionated CO2 laser, using a specific, registered technology. This paper opened a new era for non-hormonal treatment of GSM. Other studies confirmed these data, showing morphological changes in vaginal tissues, and the alleviation of the symptoms of dryness and dyspareunia [3], with an improvement in sexual gratification.

In the same years, there were studies of the thermal effects of a non-ablative 2940 nm Erbium:YAG laser, using precisely controlled, sequentially packaged bursts of long pulses (SMOOTH® mode vaginal erbium laser, VEL). The SMOOTH mode is registered and allows the use of full beam and patterned handpieces to deliver Er:YAG laser energy with different fluences to the vaginal tissue. VEL increases the tissue temperature up to the optimal range, but does not exceed the threshold for ablation or tissue damage, leading to significant improvement in GSM [4-7].

Both the microablative fractional CO2 laser and the non-ablative VEL have been repeatedly reported in observational studies to be effective for GSM treatment: vaginal dryness improves in 80–90% of women and dyspareunia in all (100.0%) sexually active women, with clinical changes similar to those induced by local estrogen administration. In addition, VEL treatment induces a deep collagen remodelling and synthesis [3], leading to a reinforcement to correct mild to moderate SUI [8-10]. VEL was reported to improve SUI as well as vaginal prolapse, by assessing the impact on the Incontinence Questionnaire-Urinary Incontinence Short Form (ICIQ-UI SF), the PAD test, the post-void residual urine volume and Q-tip angulation [8-10]. After VEL treatment, a reduction of four to six points in the ICIQ-UI score has been reported, with a success in 70–80% of patients [8-10].

28 August 2017: 

There has been ongoing uncertainty as to what level of circulating 25-hydroxy-vitamin D (25OHVitD) indicates vitamin D insufficiency. Vitamin D deficiency has been designated as a 25OHVitD level less than 30 nmol/l and insufficiency as less than 75 nmol/l [1, 2]. Please note that many laboratories give their results in ng/ml, and thus 30 nmol/l is equivalent to 12 ng/ml, and 75 nmol/l is equivalent to 30 ng/ml.

This would lead one to the expectation that treatment of a person with vitamin D insufficiency would be associated with adverse biochemical and morphological bone effects. Two recent publications should make us question the proposed 25OHVitD cut-off for vitamin D insufficiency [3, 4]. Shah and colleagues studied 11,855 people being assessed for 25OHVitD levels at a commercial laboratory and 150 people attending the Austin Hospital Melbourne [4]. Through a series of statistical analyses, they identified a ‘breakpoint’ of 30 nmol/l of vitamin D below which serum calcium was significantly lower, and parathyroid hormone (PTH) and alkaline phosphatase levels significantly higher. Although 34% of those with a 25OHVitD below 30 nmol/l had secondary hyperparathyroidism, the majority of people with a 25OHVitD below this level were biochemically normal. There was no signal of any biochemical abnormality amongst those with a 25OHVitD level between 30 and 75 nmol/l that justified a person being classified as vitamin D-insufficient. They also found no association between 25OHVitD and bone remodelling markers, bone mineral density (BMD) or matrix mineralization density in the subset of 150 people in which these parameters were measured. However, few people in this group had a 25OHVitD level below 30 nmol/l and this substudy may have been underpowered.

Reid and colleagues have concurrently reported the findings of a study in which 452 adults (mean age 69 years and two-thirds male) were randomly allocated to 100,000 IU of vitamin D3/month or placebo for 2 years [3]. No significant treatment effect was seen for BMD in the lumbar spine, which was the primary outcome. Although hip BMD declined in both groups, this was attenuated by 0.5% in the treated group. A treatment effect at the lumbar spine and hip was seen for the subset of 46 people who had a 25OHVitD level of 30 nmol/l or less at baseline.

The use of vitamin D supplementation is widespread across the developed world. However, contrary to prevailing practice, these studies indicate no bone health benefits of such supplementation for otherwise healthy adults when the serum 25OHVitD level is above 30 nmol/l. These recent findings should cause us strongly to question the validity of untargeted vitamin D supplementation for community-dwelling adults.

Susan R. Davis

Chair of Women’s Health, Monash University, Melbourne, Australia

21 August 2017: 

The Bible says that 'wine makes people happy'. Alcohol seems an inbred constituent of human nutrition, and so many studies have pin-pointed its various health benefits and risks. Usually, the bottom-line recommendation favors alcohol consumption, but limiting it to 'drink in moderation', in order to avoid the potential serious adverse outcomes of heavy and lasting drinking. A new report from the World Cancer Research Fund and the American Institute for Cancer Research addresses 'diet, nutrition, physical activity and breast cancer' [1]. The report states that there is strong evidence that consuming alcohol increases the risk for premenopausal and postmenopausal breast cancer. 

Comment

This has been known, of course, but interestingly, while reviewing the literature, it seems that no threshold has been detected. Dose-response meta-analysis showed that each 10 g of ethanol per day increase the risk of breast cancer by 5% in premenopausal women, and by 9% in postmenopausal women. To note, in the premenopause, only North American studies have demonstrated a statistically significant result, whereas European or Asian studies were in the same direction, but still non-significant. The bottom line of these data means that even just one drink per day, equivalent to 10 g of alcohol, already carries a higher risk for breast cancer. The recommendation was thus clear – 'it is best to avoid alcohol, but if alcohol is consumed, the amount should be limited'.

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.