When measured using the computer-assisted method CUMULUS, mammographic density adjusted for age and body mass index predicts breast cancer risk. We asked if new mammographic density measures defined by higher brightness thresholds gave better risk predictions.Cumulus), and in effect at two increasingly higher thresholds, which we call Altocumulus and Cirrocumulus, respectively. All measures were Box-Cox transformed and adjusted for age, body mass index, menopausal status and machine. We used conditional logistic regression to estimate the change in Odds PER standard deviation of transformed and Adjusted density measures (OPERA). The area under the receiver operating characteristic curve (AUC) was estimated.The Korean Breast Cancer Study included 213 women diagnosed with invasive breast cancer and 630 controls matched for age at full-field digital mammogram and menopausal status. Mammographic density was measured using CUMULUS at the conventional threshold . Altocumulus and Cirrocumulus measures were on average 25 % and 80 % less, respectively, than the Cumulus measure. For dense area, the OPERA was 1.18  for Cumulus; 1.36  for Altocumulus; and 1.23  for Cirrocumulus. After fitting the Altocumulus measure, the Cumulus measure was no longer associated with risk. After fitting the Cumulus measure, the Altocumulus measure was still associated with risk (P = 0.001). The AUCs for dense area was 0.59 for the Altocumulus measure, greater than 0.55 and 0.57 for the Cumulus and Cirrocumulus measures, respectively (P = 0.001). Similar results were found for percentage dense area measures.Corresponding Altocumulus measures perform better than Cumulus measures in predicting breast cancer risk, and Cumulus measures are confounded by Altocumulus measures. The mammographically bright regions might be more aetiologically important for breast cancer, with implications for biological, molecular, genetic and epidemiological research and clinical translation. Historically, the incidence and prevalence of breast cancer has been lower in Asian countries than Western countries , 2. HoweMammographic density is one of strongest risk factors for breast cancer , 6. ConvIn establishing the evidence for mammographic density as a predictor of disease , 10, conMultiple studies of Western women, and a few of Asian women, have shown that, after adjusting for age and body mass index (BMI), the standard measure of mammographic density above predicts breast cancer risk –16. It iWe used a Korean case-control study to assess if using in effect a higher than conventional pixel threshold to define density better discriminates cases from controls, i.e. better predicts risk of breast cancer. We assessed the relative discrimination by fitting the density measures based on different degrees of brightness both independently, and together.unadjusted risk factor, as has been conventional practice, but of the standard deviation of that factor after adjusting for all other factors taken into consideration, either by design or analysis, in the case-control comparison 0.5, j,k = 1,2, when Yj is fitted with Yk we multiplied the log(OR) estimate from fitting Yj by SDj|k and then exponentiated to obtain the appropriate OPERA  using the DeLong test, and use of the likelihood ratio criterion to test the relative goodness-of-fit of nested models, were performed using the STATA software package . NominalTable Altocumulus measures for dense and percentage dense area were 20–25 % less than the corresponding Cumulus measures ; see Table 2 (3.7 %) between Cumulus and Altocumulus measures, and 13.1 cm2 (13.4 %) between Cumulus and Cirrocumulus measures, respectively. The correlations were 0.84 and 0.79 for Cumulus and Altocumulus, 0.63 and 0.56 for Cumulus and Cirrocumulus, and 0.59 and 0.54 for Altocumulus and Cirrocumulus, respectively.For both cases and controls, the Cumulus, Altocumulus and Cirrocumulus, the mean of the dense and percentage dense areas differed between cases and controls . The statistical significance was greater for the Altocumulus measures .Table P < 0.05). The OPERA estimates and the AUCs were highest for Altocumulus: 1.36 : 1.15–1.62, P < 0.001) for dense area and 1.41  for percentage dense area, respectively. The corresponding OPERA estimates for Cumulus were 1.18  for dense area and 1.23  for percentage dense area, respectively. For Cirrocumulus they were 1.23  for dense area and 1.21  for percentage dense area, respectively.Table Altocumulus, Cirrocumulus and Cumulus measures together. From the OPERA estimates and standard errors, and from examining the change in log likelihood (LL) and AUCs, it was apparent that after fitting the Altocumulus measure the addition of the Cumulus or Altocumulus measures did not improve the fit (P > 0.05). On the other hand, from Tables Altocumulus measure gave a better fit than the Cumulus or Altocumulus measures alone (P = 0.001).Table Cumulus, Altocumulus and Cirrocumulus measures, respectively. The AUCs for the Altocumulus measures were highly significantly greater than for the corresponding Cumulus measures (P = 0.001). For dense area, the change in AUC from 0.55 for the Cumulus measure to 0.59 for the Altocumulus measure is 80 % when compared with the baseline AUC of 0.5 corresponding to no association, and this is reflected in a similar change in the log (OPERA) estimates. Similar AUCs applied to the percentage dense area measurements.Figure Altocumulus and Cirrocumulus , based on defining the mammographically ‘dense’ regions by being successively brighter, and therefore in effect at higher pixel brightness thresholds, than has been convention, which we call Cumulus. All density measures discriminated between cases and controls. The risk gradients and AUCs for the dense area and percentage dense area measurements were the same as well as their AUC.We have introduced two new measures of mammographic density, Altocumulus measure performed better than the Cumulus and Cirrocumulus measures. Moreover, when measures were fitted together, the risk gradient for the Altocumulus measure remained statistically significant, while the risk gradient for the Cumulus and Cirrocumulus measures were reduced and no longer statistically significant. This implies that the apparent risk relationship from traditional Cumulus measures has been confounded by the true causes being in breast tissue seen at higher thresholds of pixel intensity, so that the white but not bright areas on a mammogram do not appear to be associated with risk.Even though these density measures were correlated, the Altocumulus measures of dense area appear to be better predictors of risk, the Cumulus measures of percent dense area might be better predictors of masking.Therefore, measuring density at a higher pixel threshold appears to capture more risk-predicting information than measuring at the usual threshold. This is important for several reasons. First, in terms of clinical relevance, we studied digital images, so our findings are relevant to mammography as it is now and will be conducted across most of the world. Digital mammography makes possible automated measures that can be used to provide information in real time. While different measures of ‘breast density’ from digital mammograms are being developed and applied (e.g. ), at theSecond, these findings suggest that the mammographically denser regions might be more aetiologically important for breast cancer. The relevant tissues and biological processes involved in explaining why ‘mammographic density’ is a risk factor for breast cancer are more likely to be in the higher density areas of the breast. If confirmed, this is a critical observation for molecular, genetic and other studies trying to determine the underlying biological processes behind this phenomenon . It is aAltocumulus is one of the strongest yet known risk factors for breast cancer when viewed on a population, as distinct from individual, perspective. OPERA is an omnibus measure for discrimination between cases and controls similar to the area under the receiver operator curve, but has the advantage of explicitly taking into account other risk factors. The OPERA we estimated here of 1.4–1.5 for Altocumulus is comparable to that for a risk score based on the current common genetic markers (SNPs) recently found to be associated with risk [BRCA1 and BRCA2, combined, is only about 1.2, while the OPERA for number of live births is close to 1.1 in a Western population [Third, ith risk . In comppulation .Altocumulus, as we have measured it, is necessarily the optimal measure, we have shown that the current threshold is not optimal. More research is needed to clarify the situation, especially if automated measures can be developed that allow for changing the threshold. We are currently measuring mammographic density across different thresholds in different populations, and using multiple observers, to try to obtain better mammographic predictors of risk. We encourage others to try varying thresholds to help clarify this important issue.Obviously there must be an optimal threshold, at least for a given population measured on a given machine by the same observer. This study suggests that it is at a higher pixel level than has been convention, at least for digital mammograms and Korean women. While we are not claiming that Altocumulus and Cirrocumulus using twin and family studies, we have done for Cumulus [Altocumulus and Cirrocumulus measures, and compare these findings to those for Cumulus measures .Cumulus, Altocumulus and Cirrocumulus measures depend on the observers. However, given that measurements are performed blind to case-control status, the main issue is repeatability, and all were highly repeatable, the most for Cumulus measures. Also, the concepts of “bright” and brightest” regions is somewhat subjective, and can vary across observers. But we have tried to see if and how risk prediction depends on the threshold, so the key issue was to have measurements in effect at different thresholds (and of course conducted blind to case-control status) and then use OPERA, log likelihoods and AUC to assess the relative goodness of fits.There are several limitations to this study. The Altocumulus, performed better than the conventional measure, Cumulus, in predicting breast cancer risk from digital mammography images. This suggests that the mammographically denser (bright) regions might be more aetiologically important for breast cancer, with implications for biological, molecular, genetic and epidemiological research and clinical translation. More research is required to work out which threshold is optimal and we encourage other researchers to work on this question.This case-control study found that better discrimination between women with and without breast cancer can be achieved by defining mammographic density at a higher pixel brightness threshold than conventional, at least for Asian women. A new measure,


Breast cancer is the most common female cancer worldwide including India, where advanced stages at diagnosis, and rising incidence and mortality rates, make it essential to understand cancer literacy in women. We conducted a literature review to evaluate the awareness levels of risk factors for breast cancer among Indian women and health professionals.A structured literature search using combined keywords was undertaken on bibliographic databases including MEDLINE, Cochrane Database of Systematic Reviews, Cumulative Index to Nursing and Allied Health (CINAHL) and SCOPUS. Searches were restricted to research published in English language peer-reviewed journals through December, 2014 in India.A total of 7066 women aged 15–70 years showed varied levels of awareness on risk factors such as family history (13–58%), reproductive history (1–88%) and obesity (11–51%). Literacy levels on risk factors did not improve over the 8-year period (2005–2013). On average, nurses reported higher, though still varied, awareness levels for risk factors such as family history (40.8–98%), reproductive history (21–90%) and obesity (34–6%). Awareness levels were not consistently higher for the stronger determinants of risk.Our review revealed low cancer literacy of breast cancer risk factors among Indian women, irrespective of their socio-economic and educational background. There is an urgent need for nation- and state-wide awareness programmes, engaging multiple stakeholders of society and the health system, to help improve cancer literacy in India. We also searched for qualitative studies on breast cancer using the above mentioned search terms. No qualitative study was found on breast cancer awareness among women in India. The initial search yielded 120 studies on the basis of terms in the titles and abstracts (where available) identified from the search strategy. Studies that focused on awareness of screening, or treatment modalities alone for breast cancer were excluded as we focused exclusively on the literacy levels of risk factors and causes of breast cancer. After applying the inclusion criteria, full-text articles were retrieved for 20 studies, of which 13 fulfilled the eligibility.Index terms (MeSH terms) used for the search were,  AND (awareness OR knowledge OR attitude OR educationWe considered risk factors  summaris3n = 10) included adult women with a mean age ranging from 25 to 48 years. While the majority of studies were conducted in urban cities such as Ahmedabad, Mumbai, Jaipur and Chandigarh; and states such as Haryana and New Delhi The literature search yielded 120 articles, of which 13 studies met the inclusion criteria for this study. These studies included information on 7066 women aged 15–70 years n = 3), included adult women with a mean age ranging from 28 to 40 years. All three studies were conducted in urban settings , with educated women, either studying or practicing nursing  and n = 28 prospective observational studies; n = 29/40 on breast cancer) from high income countries did not show a significant change in literacy level after educational interventions on risk perception from baseline There is an urgent need to explore the drivers of awareness deficits and stigma surrounding breast cancer, both in the general population and among health care professionals, as incidence and mortality rates continue to rise This review has certain limitations. These findings may not be generalised across the country as they are derived from 9 locations in northern, western, and southern geographical regions of the country. India’s heterogeneous populations with different socio-economic, cultural and social factors may yield wider variations than observed, though it is unlikely that literacy levels would be higher as this review includes major metropolitan cities such as Mumbai. The number of studies and time span are too narrow for an evaluation of significant changes in cancer literacy over time. While we emphasise the importance of literacy in this review, higher awareness levels in Indian women may not always translate to better outcomes. Some evidence suggests a noncompliant attitude of women after breast cancer screening in terms of diagnostic follow up for abnormal findings, irrespective of their socio-economic status, suggesting other factors related to fear, stigma, discrimination, denial, and distrust in the health system 5Indian women need to be aware of both modifiable and non-modifiable risk factors for breast cancer to adopt appropriate practices for prevention. There is an urgent call for more effective nation- and state-wide cancer literacy programmes, as well as engagements with community-level organisations and the health system Not required.Not involved in data collection, analysis and interpretation of findings.Wellcome Trust Strategic Award; South Asia Network for Chronic Disease (WT 084674).None declared.


Ovarian cancer is a disease laden with paradigms, and it is a serious health problem. It is important to know its natural history, as it is multifactorial in origin, and also to understand its behaviour given its risk factors which can lead to death from metastasis in patients. It continues to be a challenge for oncologists. An analytical literature review was performed to update the latest concepts of its origin, evolution, risk factors, pre-clinical horizon, and its clinical manifestations; until the death of the patient. Ovarian cancer is the sixth most common tumour in women. More than 200,000 new cases are diagnosed each year worldwide. Each year, it constitutes 4% of all cancers diagnosed in women, and there are 6.6 new cases per 100,000 women per year . The pooIt is the most common malignancy after breast cancer in women over 40 years of age, particularly in developed countries, and in Mexico it stands in fourth place among the deaths caused by gynaecological tumours . EpithelMost women with ovarian cancer are diagnosed with locally advanced and metastatic disease according to the International Federation of Gynaecology and Obstetrics (FIGO) clinical stages III or IV .The tumour involves one or both ovaries, with positive peritoneal implants outside the pelvis, or retroperitoneal, or inguinal positive nodes. There is superficial liver metastasis. The tumour is limited to the true pelvis area, but with a histologically verified malignant extension to the small intestine or omentum.The tumour invades one or both ovaries with distant metastasis. There is pleural effusion fluid, positive by histology, and liver parenchymal disease.Its origin has not really been clarified, and there are multiple causes, which has led to a number of medical publications in indexed and non-indexed journals. Ovarian cancer is a disease that belongs to the group of chronic and degenerative diseases with extensive natural history. After ten years of control, it can re-occur, with fatal relapses in a short amount of time. Perhaps the critical period to establish a good survival prognosis and a long disease-free period is the first two years of diagnosis, in locally advanced stages. Unlike breast cancer, it appears in two periods of life, the first one being in youth, and the second one postmenopausal.Epithelial ovarian cancer, the most frequent, occupies third place in the list of gynaecological malignancies worldwide. In 2008, half of new cases were presented in highly developed countries . In our Alterations for ovarian cancer are transmitted through mitosis from one cell to another, but are not transmitted from parents to children. There must be a predisposition or susceptibility to germline mutation or an inherited susceptibility for that to happen. The cause and mechanism of hereditary cancer are the fathers’ sperm. Once a person has inherited cancer, the individual becomes a carrier and will transmit it to their offspring according to Mendelian laws, depending on the dominant or recessive nature of the altered gene causing the cancer. Usually, it is dominant if it is an oncogene and recessive if it is a mutated tumour suppressor gene. The best known hereditary cancer is breast cancer. It has this characteristic in 5–10% of the cases. Its main cause is the mutation of the BRCA1 tumour suppressor genes from chromosome 17 or BRCA2 from 13. The first of these genes manifests itself in breast and ovarian cancer, because it is a tumour suppressor gene. In general hereditary transmission is because of mutant allele, which will only manifest itself in daughters, developing into a tumour. The abnormal presence of BRCA1 is associated in women with a 50% to 80% probability of developing breast cancer and a predisposition to ovarian cancer .BRCA 1 and BRCA 2 mutations: Risk for ovarian cancer from 27–44%, compared to 1% of the general population.Breast-ovary syndrome: Risk of 10–44%.Li-Fraumeni syndrome.Lynch syndrome: Risk of 9–12%.Ashkenazi Jewish population: Risk of 16–60%.Family history of ovarian cancer.Medium-high socioeconomic status, especially in industrialised countries.Nulliparity, infertility, and use of ovulation-stimulating drugs .White race.High-fat diet and obesity.Polycystic ovaries  .Personal history of breast, colon, or endometrial cancer (hormone-dependent tumours).Exposure to asbestos, talc, or radiation.Migration from adjacent cells see  19]..19].Low concentration of selenium bound to proteins.The risk factors of epithelial ovarian cancer are typical of perimenopausal and postmenopausal women , 16. ItsOf the latter, the expression of protein-bound selenium in the ovary, there is an overexpression of the epithelial cells of the gonad, compared with overexpression of the neoplastic cells of the ovary. It was less than in normal epithelial cells .Polycystic ovary syndrome (PCOS) is a heterogeneous genetic disorder, involving metabolic and endocrine problems. It occurs most frequently in women of reproductive potential and is characterised by an increased concentration of androgens circulating in the blood. It has a markedly negative effect on the metabolism of normal bodily functions. PCOS can evolve into metabolic syndrome, affecting the body’s energy utilisation. This takes the form of a markedly high rate of insulin synthesis in the blood, abdominal obesity, increased blood pressure, dyslipidemia, insulin resistance, type 2 diabetes mellitus, cardiovascular disease, and endometrial hyperplasia. Changes can also take place in the regulation of gonadotropin release, and this interferes with the ovarian steroid inhibition-feedback loop. This results in increased secretion of luteinising hormone in the woman’s body. The secretion of follicle-stimulating hormone (FSH) also increases; the stromal cells and ovarian theca cells are hyperactive, and because of this hyperactivity, the secretion of androgens increases; all this allows abnormalities to appear in the biochemistry of the body’s metabolism after menopause. There are various types of pharmacological treatment for PCOS, including lifestyle changes such as reduced dietary intake, physical exercise, controlling nitrosodimethylamine production, its increased metabolism in the ovary, and its reaction with the proteins there. Nitrosodimethylamine is metabolised in the ovaries by the mitochondria and the microsomal enzyme system. The microsomes and mitochondria cause the nitrosodimethylamine in the ovary to degrade and be converted to reactive toxic metabolites and formaldehyde. These become attached to the ovarian proteins with covalent bonds. Most of this degradation takes place in the microsomes. When the DNA of the normal epithelium of the ovary has been separated and analysed by immunohistochemistry tests, it shows changed sequences of the deoxyribonucleic acid bases. These changes result from the toxic effects of the reactive metabolites of the nitrosodimethylamine in the DNA of the normal ovarian epithelial cells. This path can occur in any woman exposed to tobacco or alcohol consumption .Age: >45 years.Early menarche: relative risk (RR) 1.0 .Late menopause: RR 2.5 (95% CI 1.1–5.8).Nulliparity: Pregnancy reduces the risk of ovarian cancer .Medical history of breast cancer.Infertility treatment with no full-term pregnancy: The use of clomiphene citrate is associated with a RR of 2.3 (95% CI 0.5–11.4) compared with infertile women who do not use it.Obesity: RR 2.05 in women with a high BMI >30, aged over 18 years.Use of hormone replacement therapy for more than five years: RR 1.5 (95% CI 0.9–2.6).Smoking: Odds ratio (OR) 1.0.Use of talc and exposure to asbestos: Daily use of talc RR 1.3 (95% CI 0.8–1.9).Two immediate family members with breast or ovarian cancer, including one <50 years at the time of diagnosis: OR 2.90 (95% CI 1.92–4.36).One family member with unilateral breast cancer <40 years; bilateral <30 years: OR 1.35 (95% CI 1.03–1.78).More than one pregnancy carried to term.Use of oral contraceptives and breast-feeding, the latter being related to continuous ovulation.Tubal ligation not clearly demonstrated.Clearly established protective factors include:Lynch II syndrome includes non-polypoid colorectal carcinoma, endometrial cancer, upper gastrointestinal tract cancer, urothelial cell carcinoma of the renal pelvis, ureteral cancer, and ovarian cancer . Publishsine qua non” investigation for a suspected adnexal tumour: pelvic ultrasound, preferably using colour Doppler, and better still, by the vaginal route in the early stages. The above has not had a statistically significant impact on the prognosis for survival of women with ovarian cancer. Women with high-risk factors who have completed their family must undergo a prophylactic salpingo-oophorectomy before the age of 35 years, though this does not eliminate the possibility of future peritoneal carcinomatosis, similar to advanced ovarian cancer. Depriving menopausal women of hormone replacement therapy has not improved the statistics for survival of ovarian cancer patients, and its absence has even favoured cardiovascular ischaemia and loss of bone mass.To date, there is no suitable programme for detection; diagnostic methods are expensive and do not detect malignant tumours in the early stages of disease. In most cases, women are diagnosed at stages of local progression or in metastatic disease with a poor prognosis for survival. However, in women with hereditary risk factors or those identified during a directed history, it is acceptable to do immunohistochemical tests with tumour markers. We should not forget the “Age and menopause status.Tumour size.Tumour stage.Characteristics of the tumour by imaging .Presence or absence of symptoms.Tumour marker values .Unilateral, compared with bilateral.In general, ovarian cancer is revealed by increased abdominal volume, but the symptoms are vague and frequently an adnexal tumour is overlooked because the discomfort is not intense and is often confused, by the patient and even by the doctor, with gastrointestinal conditions and conditions misleadingly appearing to originate in the urinary tract. When the malignant ovarian tumour does become apparent, 79% of cases are diagnosed at advanced stages, and symptoms will depend on the organ affected and invaded. At this time the woman experiences intense gastrointestinal symptoms, with lower abdominal or pelvic pain, and periodic constipation and diarrhoea; vaginal bleeding also occurs. The patients are usually treated as if the condition originated from ulcers, colitis, and not infrequently liver disease, mainly disease of the gallbladder. The volume and diameter of the abdomen increases suddenly, through ascites, and this leads to the gradual onset of dyspnoea, in line with the amount in litres that is pressing upwards on the diaphragm and impeding respiratory movement. Unlike with other tumours, the patients’ body weight increases because of the malignant-free fluid in the abdominal cavity. When an ovarian tumour is diagnosed by accident at the early stages, the usual diagnosis is of a benign adnexal tumour, which generally works for most fertile women. This generally regresses at the next menstrual period or the painful symptoms improve. The diagnosis of malignant ovarian tumour can also be made accidentally or incidentally during a gynaecological investigation and sometimes because of twisting of the ovarian pedicle, which requires an investigative laparotomy for acute abdomen, mostly with no indication for oncological surgery. Once the ovarian tumour has been diagnosed as malignant, the prognosis for survival will be related to the following factors:The doctor should never neglect to take a history directed to adnexal tumour, and carry out a physical examination including digital rectal and vaginal examination, which is essential to increase the possibilities for initial surgery . The initial assessment of patients with suspected ovarian cancer, following the initial history-taking, physical examination, laboratory results, and tests for tumour marker cancer-125, must focus on investigating the contents of the abdominal cavity. Therefore, imaging studies must be conducted, such as ultrasound CT, MRI, and special techniques of radioactive isotope scanning; none of these give details of the correct staging of the tumour, and at the end of the study an abdominal CT, chest x-ray, and bone scan must be carried out. Where technically possible the recommended first-line ultrasound procedure for a suspected single adnexal tumour is by the vaginal route, using colour Doppler. This has a sensitivity of over 93.5% and specificity of 91.5%. If this is not possible, MRI is the most appropriate for adnexal investigation, particularly if there is suspected tumour activity outside the pelvis. It has a sensitivity of 91.1% and specificity of 84%. CT has shown 87.2% sensitivity and 84% specificity , 27, 28.The strains from ovarian cancer originate from the epithelial, the germ cells, and the gonadal stroma. From the former derive the serous, mucinous, endometrioid, undifferentiated, clear cell, small cell, and Brenner tumour adenocarcinomas. This group makes up about 45 % of the malignant neoplasms. Five percent (5%) of the endometrioid tumours are generated in endometriosis. It is reported that 25% to 33% of the cases are associated to endometrial cancer. The clear cell ones have the worst survival rate. The epithelial strains are characterised for rising the non-specific tumour markers, significantly the cancer-125 in nonmucinous tumours. In mucinous tumours, the cancer-19.9 increases with higher frequency in a formidable response to both schemes with chemotherapy that includes the platinum derivatives.The non-epithelial strains, mainly the germ ones show more presence in young menstruating people. The tumour markers are mainly increased by: carcinoembryonic antigen, alpha-fetoprotein, and the chorionic gonadotropin beta fraction; the tumours in ovarian germ cells represent 20% of the neoplasms where only 3% is associated with malignancy. Tumours are a group of heterogeneous and complex neoplasms, and up until now there are no etiological factors that have been defined that may be associated to its presentation, despite the many descriptions of diverse chromosomal alterations  and processes regarding DNA repair (short-arm of chromosome 12) that contribute to its development. Gonadal dysgenesis is associated to the growth of dysgerminomas in at least 50% of reported cases and some patients have shown that there is an overexpression of p53 gene . The mosImmature teratomas show clinically as solid tumours having isolated areas with fatty deposits and calcifications. Yolk sac tumours normally show as tumours with mixed solid and cystic areas. The capsular rupture or bright punctate comes about as a result of an increase in vascularity and because of the creation of small vascular aneurysms. The embryonal carcinoma and the polyembryoma rarely show in their pure form. Instead, they become a part of the mixed tumours of germ cells see  30]..30].Low-grade: Mild-to-moderate pleomorphism<12 mitosis x 10 fields of 400x.High-grade: Significant pleomorphism with more than 12 mitosis x 10 fields of 400x.The papillary serous carcinoma are better classified as high-grade and low-grade . The metCurrently, there are no molecular markers that identify groups associated with the forecasted results. Among the related factors, these are some of them: tumour heterogeneity, size of the studied population, and the different sample processing techniques .Ovarian cancer will keep on being a high-risk threat to women, given that its diagnosis in initial stages yields a very low percentage. Therefore, the majority of patients will die in spite of today’s treatments. Nowadays there is no low-cost effective method to perform the appropriate screening. I believe it is necessary for every woman after menarche to undergo a pelvic US as a research study. Those with hereditary risk factors of ovarian tumours must have screening tests with immunohistochemical proofs, such as the commonly used tumour markers panel, to aid their diagnosis. It is imperative to remember that ovarian cancer can only be cured in stage I , providesine qua non image and immunohistochemistry studies. The natural history of ovarian cancer indicates that it will remain as the tumour that takes the life of women in reproductive age for several decades to come.Ovarian cancer does not present with an effective research method. Good tools for early diagnosis of high-risk tumours are the ultrasound as a


Evidence indicating an association between cigarette smoke exposure and an increase in breast cancer risk highlights the need for health messages that aim to prevent smoking initiation and reduce secondhand smoke (SHS) exposure among adolescent girls.This study aimed to evaluate the efficacy of targeted gender-sensitive, breast cancer-specific, Web-based messages about the increased risk of breast cancer associated with cigarette smoke exposure. Outcomes assessed 6 months postmessage delivery included nonsmoking adolescent girls’ knowledge of the link between cigarette smoke exposure and breast cancer, perceptions of breast cancer risk associated with cigarette smoke, smoking behavior and intentions, and stage of change related to avoidance of secondhand smoke.A prospective randomized controlled trial was used to compare standard (control) messages with targeted gender- and Aboriginal status-sensitive, breast cancer-specific (intervention) messages. Messages were delivered online to 618 nonsmoking girls, aged 13 to 15 years, clustered in 74 Canadian secondary schools.Compared with the control group, girls in the intervention group were significantly more likely to report that breast cancer is an illness caused by cigarette smoke  and to agree that exposure to SHS increases their risk of breast cancer . No significant effects were observed for a change in smoking status, intention to try smoking, or stage of change related to avoidance of SHS.Compared with standard messages, targeted gender-sensitive, breast cancer-specific messages had a stronger influence on girls’ knowledge and perceived risk of cigarette smoke exposure as a risk factor for breast cancer. Brief information-based interventions delivered over the Internet have the potential to provide effective health promotion that could be broadly disseminated and lead to long-term effects on girls’ knowledge and risk perceptions about cigarette exposure and breast cancer. Recent evidence indicates that cigarette smoking and secondhand smoke (SHS) exposure are associated with an increase in premenopausal breast cancer risk -7. In 20The increased risk of premenopausal breast cancer associated with smoking and SHS, especially exposure between menarche and first childbirth, has direct implications for breast cancer prevention strategies. In a recent Canadian survey, 10% of youth in grades 10-12 self-identified as current smokers . AlthougFrom a cancer prevention perspective, targeting interventions toward adolescent girls is particularly important because it is during periods of breast development that cigarette smoke exposure appears to increase the risk of breast cancer. The potential effectiveness of targeting tobacco control messages that highlight the benefits of reducing breast cancer risk toward adolescent girls is also supported by health behavior theory. The pubertal period is marked by heightened awareness of physical  and psychological  changes, and can therefore be exploited as a teachable moment for breast cancer prevention . As suchSeveral meta-analyses and systematic reviews indicate that targeted messages are more persuasive than generic messages, and lead to greater improvements in outcomes including behavioral intentions, behavior change, and attitudes -22. The The rapid expansion in adolescents’ use of the Internet has led to the characterization of the Internet as an ideal channel for risk factor screening  that can be coupled with the delivery of targeted health promotion interventions to reduce cigarette smoke exposure . DigitalAlthough Web-based interventions for adolescents have great potential, recent investigations of Web-based smoking cessation interventions for adolescents have not yet demonstrated substantial gains in efficacy ,28-30. HThe aim of this study was to investigate the efficacy of targeted gender- and Aboriginal status-sensitive, breast cancer-specific, Web-based messages focused on the increased risk of breast cancer associated with cigarette smoke exposure. The outcomes included nonsmoking adolescent girls’ (1) knowledge of the causal link between cigarette smoke exposure and breast cancer, (2) perceptions of breast cancer risk associated with exposure to cigarette smoke, (3) smoking initiation, (4) intentions to smoke in the future, and (5) stage of change related to avoidance of SHS at follow-up (6 months following the message delivery). We hypothesized that compared with a control group that received a standard message describing the carcinogenic effects of tobacco smoke, a greater proportion of girls exposed to the targeted, disease-specific intervention would identify exposure to cigarette smoke as a cause of, and risk factor for, breast cancer. We also hypothesized that compared with girls who received a standard message, a smaller proportion of girls who received the targeted, disease-specific intervention would try smoking, report intentions to try smoking in the future, and report doing nothing to avoid SHS exposure.The study described in this article, entitled Supporting Tailored Approaches to Reducing Tobacco (START): Decreasing Breast Cancer Incidence, was a cluster randomized controlled trial nested within an ongoing Web-based prospective cohort study, the British Columbia Adolescent Substance Use Survey (BASUS). The BASUS study began enrolling students from 48 participating secondary schools in the fall of 2009 and surveyed participants every 6 months until the fall of 2012. All BASUS participants were 13 years of age or older, able to read and complete a Web-based survey in English, and provided informed consent, as well as written parental consent in schools where required. Although the majority of students completed their surveys online outside of school time, others completed the survey in school computer labs during scheduled class time. Students received reminders to complete each wave of the BASUS survey via school-based posters and announcements, as well as via personal email if requested by the participant. Students could retrieve their passwords via email using a lost password button on the BASUS website. All participants received a $25 gift card as an honorarium for each wave of the survey completed, and the response rates for individual schools ranged from 2% to 100%, with a 20% average. In the spring of 2011, schools were stratified into groups containing a similar number of study participants and randomly assigned to have their students receive either the targeted, breast cancer-specific intervention or the control message. The follow-up assessment was completed approximately 6 months later as part of the next wave of the BASUS study. For a complete description of the design of the randomized controlled trial and CONSORT statement, please refer to Richardson et al . EthicalA tailored intervention message was designed to be sensitive to gender and Aboriginal status . The resFollowing receipt of the intervention message at baseline, adolescent girls answered the following yes/no question: “Would you be interested in receiving information about the connection between cigarette smoke and breast cancer?” If a participant responded “Yes,” she received additional information about the risk of cigarette smoke exposure and breast cancer upon completion of the survey (available on request).Students in the control group were presented with a standard message that cigarette smoke contains carcinogenic agents. The message was sourced from Health Canada’s online library of health labels and warnings for cigarette tobacco . This meWarning, you’re not the only one smoking this cigarette. The smoke from a cigarette is not just inhaled by the smoker. It becomes secondhand smoke, which contains more than 50 cancer-causing agentsFollowing receipt of the standard message at baseline, adolescent girls answered the following yes/no question: “Would you be interested in receiving information about the connection between cigarette smoke and cancer?” If a participant responded “Yes,” she received additional general information about the risk of cigarette smoke exposure and cancer upon completion of the survey questions (available on request).Participants included in the current analysis were nonsmoking adolescent girls, aged 13 to 15 years, who participated in the BASUS study. For baseline characteristics postrandomization, please refer to Richardson et al .The baseline data collection for the current study occurred between April and June 2011; the follow-up data were collected between October and December 2011. The baseline survey questions determined the participants’ demographic and SHS exposure characteristics, including age, ethnicity, family income , and family history of breast cancer (yes or no). In addition, smoking behavior (ever tried smoking), intentions to smoke in the future, SHS exposure , and interest in receiving more information were assessed at baseline.Approximately 6 months after the baseline dissemination of the intervention and control messages, the subsequent wave of the BASUS survey was administered. The following question was used to assess the girls’ knowledge of the connection between cigarette smoke exposure and breast cancer: “Which of the following illnesses have been shown to be caused by exposure to cigarette smoke?”, with the following response options: AIDS, arthritis, asthma, bladder cancer, breast cancer, common cold, diabetes, heart disease, lung cancer, measles, schizophrenia, stomach cancer, or none of the above. Risk perceptions regarding cigarette smoke exposure and breast cancer were assessed by asking participants to respond to the following statement: “Being exposed to secondhand cigarette smoke increases my risk of getting breast cancer”, with the following response options: strongly agree, agree, disagree, or strongly disagree. Intentions to smoke were measured with the following question: “Do you think you might try smoking cigarettes in the future?”, with the following response options: probably yes, probably not, or definitely not. The following brief measure developed by our group was used to assess the girls’ stages of change  related to avoidance of SHS: “When you are exposed to secondhand cigarette smoke, do you consistently do things to reduce your exposure to the smoke?”, with the following response options: yes, I have been for more than 6 months; yes, I have been, but for less than 6 months; no, but I intend to in the next 30 days; no, but I intend to in the next 6 months; or no, and I do not intend to in the next 6 months .P<.10) between the treatment and control groups were included as covariates in subsequent multivariate models. Bivariate analyses of the categorical data were conducted with Fisher’s exact tests. Follow-up time (measured in months) was included in the multivariate models. A generalized estimating equation (GEE) was used for all multivariate regression models to adjust the standard errors of the parameter estimates for the correlated responses of students clustered within the same school [The primary aim of the analysis was to determine whether differences in the outcomes were associated with exposure to the intervention versus control messages. To account for possible confounding not controlled by random allocation, potential confounders were identified with bivariate tests—any variables found to differ . Therefore, 618 nonsmoking girls from 74 schools (some students reported moving to a new school which increased the number of schools from 48 to 74), aged 13 to 15 years (mean age of 14 years), were included in the analyses. Of these girls, 242 received the intervention message and 376 received the standard control message. Among girls in the intervention group, 55 out of 242 (22.7%) requested more information about the relationship between cigarette smoke and breast cancer, and 64 girls out of 376 (17.0%) in the control group requested more information about the relationship between cigarette smoke and cancer—these proportions did not significantly differ (P=.52) by group. On average, 6 months elapsed between the baseline presentation of the messages and the follow-up assessment. P<.10) between intervention and control groups.A total of 745 nonsmoking adolescent girls completed the baseline survey, and 618 completed both the baseline and follow-up surveys, providing a retention rate of 83.0%. Among the 127 girls lost to follow-up, 59 (46.5%) and 68 (53.5%) were in the control and intervention groups, respectively—results from a one-sample binomial test (hypothesized proportions of 50% in intervention and control groups) indicated that the difference in proportions lost to follow-up was not statistically significant  see .As shown in P=.003). Among girls who did not request more information (n=499), a significantly greater proportion of girls in the intervention group  compared with the control group  agreed with the statement that being exposed to SHS increases their risk of breast cancer (P=.03). All other outcomes of interest did not significantly differ in these stratified analyses.After stratifying groups by whether or not the girls requested more information about the relationship between cigarette smoke and (breast) cancer, we examined all outcomes analyzed in the prior multivariate models  using univariate analyses (Pearson Chi-square tests). Among girls who requested more information (n=119), a significantly greater proportion of girls in the intervention group  compared with the control group  identified breast cancer as an illness caused by exposure to cigarette smoke  knowledge of the causal link between cigarette smoke exposure and breast cancer, (2) perceptions of breast cancer risk associated with exposure to cigarette smoke, (3) smoking initiation, (4) intentions to smoke, and (5) stage of change related to avoidance of SHS at follow-up . The results indicate that the intervention message had positive effects on awareness of cigarette smoke exposure as a causal agent of, and risk factor for, breast cancer among nonsmoking girls approximately 6 months following message dissemination. Compared with the girls who received the standard control message, the girls who received the intervention message were 33% more likely to identify breast cancer as an illness caused by exposure to cigarette smoke and 10% more likely to agree with the statement that being exposed to SHS increases their risk of breast cancer. Furthermore, a similar pattern of results was found in groups stratified by whether or not the girls requested more information about the relationship between cigarette smoke and (breast) cancer.This is the first intervention we are aware of specifically designed to evaluate the effect of a brief Web-based intervention on awareness of the relationship between SHS and breast cancer. Furthermore, this study considered both changes in perceived risk regarding the link between exposure to SHS and breast cancer, as well as smoking intentions and behavior at follow-up. Two teams of researchers have tested online interventions to reduce cigarette use and intentions to smoke among adolescents ,28. TheyFindings from our study, which indicate that brief, targeted, breast cancer-specific messages can raise girls’ awareness of the link between breast cancer and cigarette smoke exposure, add to the small but growing body of literature about the benefits of using the Internet to deliver messages to raise awareness and ultimately effect health behavior change. For example, in a recent study 25% of 497 adolescents reported changing their behavior  based on findings in online searches for health information . Indeed,This study is not without limitations. The purpose was to compare a generic control message with targeted gender- and Aboriginal status-sensitive, breast cancer-specific (intervention) messages. Given that the control message did not contain breast cancer-specific information it is not possible to disentangle the influence of the breast cancer-specific information from the other aspects of the gender tailoring of the intervention message. The positive outcomes of the intervention were increases in girls’ knowledge and risk perceptions related to cigarette smoke exposure and breast cancer, not with actual behavior change . However, the latter, nonsignificant findings could have resulted from the small number (22/613) of girls who reported having tried smoking at the time of follow-up. Future studies could address this limitation by employing a much larger sample. These studies could add to the results of the current investigation by examining behavioral change among an oversampling of girls’ who have already tried smoking. Additionally, if a second no-information control group had been included as a reference , larger intervention effects may have been found. The generalizability of these findings is limited—they may not be relevant to other age groups and ethnicities.The study findings suggest that a brief, targeted, disease-specific and gender-sensitive, Web-based message influenced girls’ knowledge of cigarette smoke exposure as a risk factor for, and causal agent of, breast cancer, thereby supporting the use of this type of intervention in future trials. Brief informational interventions delivered via the Internet appear to be effective, far-reaching forms of health promotion that have the potential for long-term effects on adolescents’ knowledge and risk perceptions with regard to cigarette exposure and breast cancer. Future investigations of Web-based interventions could employ repeated exposure of the targeted message, or they could implement a multistep design and incorporate short message service (SMS) text messaging or interactive voice responses to understand how to increase the effectiveness of these types of interventions.


The aim of this present study was to examine duration of breastfeeding in relation to the risk of different subgroups of breast cancer. A prospective cohort, The Malmö Diet and Cancer study, including 14092 parous women, were followed during a mean of 10.2 years and a total of 424 incident breast cancers were diagnosed.Tumours were classified regarding invasiveness, tumour size, axillary lymph node status, Nottingham grade, tumour proliferation (Ki67), HER2, cyclin D1 and p27, WHO histological type and hormone receptor status. Duration of breastfeeding was measured using total time of breastfeeding, categorized in quartiles using the lowest as the reference group . Average duration of breastfeeding per child and breastfeeding duration of the first child were also used as exposures in separate analyses. Relative risks, with 95% confidence intervals, were obtained using a Cox’s proportional hazards analysis adjusted for potential confounders.Overall risk for breast cancer was similar in all quartiles of breastfeeding. No strong results regarding breastfeeding duration and breast cancer subgroups were seen. A few results indicated an association between a relatively long duration of breastfeeding and tumours with high proliferation (Ki67) and grade III histological grade.Breastfeeding duration was not associated with breast cancer risk and no strong results were seen with regard to breast cancer subgroups. Several early studies and a recently a large meta-analysis including data from thirty countries, have shown a negative association between increasing time of breastfeeding and the risk of breast cancer. HoweverIn all, 17 035 women participated in a prospective population-based cohort in Malmö, Sweden: The Malmö Diet and Cancer Study (MDCS). The MDCS collected information on breastfeeding, as well as other reproductive and environmental factors. During follow-up, 622 women were diagnosed with breast cancer. Tumour tissue samples were available for about 90% of these women, which allowed tumour reclassification and further tumour biological examinations. Tumours were evaluated with regard to invasiveness, size, axillary lymph node status, Nottingham grade, tumour proliferation (Ki67), Human epidermal growth factor receptor 2 (HER2) status, and expression of cell cycle regulators such as cyclin D1 and p27. Tumours were further examined for WHO histological type  and hormone receptor status; estrogen receptor alpha (ERα), estrogen receptor beta (ERβ) and progesterone receptor (PgR).The aim of the present study was to examine breastfeeding in relation to the risk of breast tumours with different biological characteristics.All women born between 1923 and 1950 in Malmö were invited to a prospective cohort study, the MDCS. Between the years 1991 and 1996, 17 035 women participated[Information on breastfeeding, education, occupation, marital status, age at menarche, parity, year of each child’s birth, age at menopause, exposure to oral contraceptives (OC) (ever/never), current use of hormonal replacement therapy (HRT), alcohol consumption and smoking habits were collected using a questionnaire at baseline.Menopausal status was assessed using both medical records and the questionnaire. A women was considered postmenopausal: (1) if she had undergone bilateral oophorectomy; or (2) if she had undergone hysterectomy but not bilateral oophorectomy, and if she was ≥55 years of age; or (3) if the above criteria were absent and she affirmed that her menstruations had ceased at least during the calendar year two years prior to baseline examination; or (4) if it was unknown whether or not she had undergone a previous oophorectomy or hysterectomy and information on menstrual status was missing, and she was ≥55 years of age. In all 11388 women were postmenopausal at baseline. A woman was classified as pre-/perimenopausal if she affirmed that she was still menstruating, or if her menstruations had ceased less than two years prior to baseline examinations, or if information on menstrual status was missing and the women was <55 years of age at baseline.2.Height and weight was measured at baseline by a trained nurse at the study centre, and Body Mass Index (BMI) was calculated as kg/mThe MDCS and the present analyses were approved by the Ethical Committee at Lund University (LU 51–90 and Dnr 652/2005).Time of breastfeeding was assessed with the help of a questionnaire. All participants were asked to fill in the number of children they had given birth to. Information on birth years of the children and duration of breastfeeding was retrieved for the first seven children. No information on twin pregnancies was available. Parity was defined as the total number of children that a women answered she had given birth to.Mean duration of breastfeeding per child was calculated as the sum of the months of breastfeeding divided by the number of children with information on breastfeeding.Total time of breastfeeding was calculated as mean time of breastfeeding multiplied with parity. This calculation was made since time of breastfeeding was limited to seven children and a small amount of women had eight or more children (n = 13). Breastfeeding of the first child was investigated in an additional analysis, as it is likely that changes during the first pregnancy and following lactation period may be particularly important with regard to the differentiation of the breast tissue. Women tAll women were followed until 31 December 2004 with tumour end-points retrieved by record linkage with The Swedish Cancer Registry (until 31 December 2003). Due to a delay in central registration, linkage to its regional branch, The Southern Swedish Regional Tumour Registry, provided tumour-endpoints for the year 2004. Vital status was obtained from The Swedish Cause-of-Death Registry until 31 December 2004. A total of 622 incident breast cancer cases (including invasive and cancer in situ) were registered during follow-up.Out of 17 035 women, 576 had been diagnosed with breast cancer prior to inclusion in the study, and they were categorized as prevalent breast cancer cases and were subsequently excluded from the analyses. A total of 2089 women were nulliparous and hence excluded from the study population. Yet another 278 had no information on parity and were also excluded. This gave us a study population of 14 092 women with 522 incident breast cancer cases. A total of 57, were cancer in situ (CIS) and only provided person-years until event, but did not provide invasive end-points in the analyses for “all breast cancers”. CIS cases were neither included in the analyses of specific subgroups, e.g. histology and receptor status. Ten women with bilateral breast cancer were excluded as tumour end-points in the analyses due to difficulties in determining the relevant side to be used in the analyses of tumour size, axillary lymph nodes, histopathology and receptor status. A further 31 did not have sufficient tissue for further analyses. Bilateral cases and cases with no tumour material did however provide person-years up until the event. In all 424 tumours were included in the subgroup analyses . All tumours were re-evaluated concerning invasiveness and tumour type was described according to the WHO classification. The tumours were graded according to Elston and Ellis, including tubular formation, nuclear atypia and mitotic index. FurtherInformation on tumour laterality, size and lymph node metastasis were retrieved from medical records and histopathological reports by one registered nurse.The main analyses used total duration of breastfeeding as measurements. Additional analyses used mean duration of breastfeeding and breastfeeding duration of the first child. Breastfeeding duration was divided into quartiles. Quartile cut-offs for breastfeeding were based on the distribution of all women in the study cohort. Different quartiles of breastfeeding were compared regarding the distribution of established and potential risk factors for breast cancer. Each subject was followed until the event of breast cancer, death or end of follow- up, 31 December 2004. The incidence of breast cancer was calculated per 100,000 person-years in different breastfeeding quartiles. Corresponding relative risks of breast cancer were analyzed using a Cox’s proportional hazards analysis yielding relative risks (RR) with 95% confidence intervals (CI). These analyses were subsequently adjusted for potential confounders; age at baseline, education, socioeconomic status, marital status, age at menarche, age at first birth, parity, oophorectomy, age at menopause, oral contraceptive use, hormone replacement therapy use, bmi, alcohol consumption, smoking and height  was similar in all breastfeeding groups as compared to the lower quartile Table . There wWomen in the lowest quartile of average duration of breastfeeding were younger at baseline and were more often pre-/perimenopausal at breast cancer diagnosis as compared to all other groups . In order to get access to the data, an application to the committee is needed. Please contact Prof. Jonas Manjer: jonas.manjer@med.lu.se.The authors declare that they have no conflict of interests.SB participated in designing the study, carried out all the statistical analyses, participated in interpreting the results, reviewed the literature and drafted the manuscript. SiB participated in the study design, analyzing the tumours, interpreting the results and critically revised the manuscript. LA participated in the tumour analyses and critically revised the manuscript. GL participated in the study design, critically revised the results and the manuscript. JM designed the study, supervised and participated in analyzing all statistical analyses and critically revised the manuscript. All authors have read and given approval of the final manuscript.Table S2. Risk of breast cancer subgroups defined by clinico-pathological markers in relation to average duration of breastfeeding. Table S3. Risk of breast cancer subgroups defined by immunohistochemical markers in relation to average duration of breastfeeding. Table S4. Risk of breast cancer subgroups defined by type and receptor status in relation to average duration of breastfeeding. Table S5. Distribution of risk factors in different quartiles of breastfeeding duration of first child. Table S6. Risk of breast cancer subgroups defined by clinico-pathological markers in relation to breastfeeding duration of first child. Table S7. Risk of breast cancer subgroups defined by immunohistochemical markers in relation to breastfeeding duration of first child. Table S8. Risk of breast cancer subgroups defined by type and receptor status in relation to breastfeeding duration of first child.Distribution of risk factors in different quartiles of average duration of breastfeeding. Click here for file


Menopausal hormone therapy (MHT) increases breast cancer risk; however, most cohort studies omit MHT use after enrolment and many infer menopausal age.We used information from serial questionnaires from the UK Generations Study cohort to estimate hazard ratios (HRs) for breast cancer among post-menopausal women with known menopausal age, and examined biases induced when not updating data on MHT use and including women with inferred menopausal age.Among women recruited in 2003–2009, at 6 years of follow-up, 58 148 had reached menopause and 96% had completed a follow-up questionnaire. Among 39 183 women with known menopausal age, 775 developed breast cancer, and the HR in relation to current oestrogen plus progestogen MHT use (based on 52 current oestrogen plus progestogen MHT users in breast cancer cases) relative to those with no previous MHT use was 2.74 : 2.05–3.65) for a median duration of 5.4 years of current use, reaching 3.27 (95% CI: 1.53–6.99) at 15+ years of use. The excess HR was underestimated by 53% if oestrogen plus progestogen MHT use was not updated after recruitment, 13% if women with uncertain menopausal age were included, and 59% if both applied. The HR for oestrogen-only MHT was not increased .Lack of updating MHT status through follow-up and inclusion of women with inferred menopausal age is likely to result in substantial underestimation of the excess relative risks for oestrogen plus progestogen MHT use in studies with long follow-up, limited updating of exposures, and changing or short durations of use. Menopausal hormone therapy (MHT) provides effective relief from climacteric symptoms but some are associated with increased risk of stroke, venous thromboembolism, and breast, ovarian, and endometrial cancers , but nevAccurate information about the risks (and benefits) of MHT is essential to allow women to make informed decisions about their health, and evidence from observational studies is important because it is no longer justifiable to conduct long-term trials of MHT safety , which has ascertained MHT use and menopausal status at entry and during prospective follow-up, to estimate the relative risk of breast cancer in relation to MHT use among women whose age at menopause was known. We also assessed the likely extent of the biases that occur when only baseline questionnaire information is available and if women with simple hysterectomy are included in analyses.The BGS is a cohort study of 113 693 women from the United Kingdom, aged ⩾16 years, from whom questionnaire information and informed consent was gained at recruitment during 2003–2015. The first follow-up questionnaire was completed at 2.5 years after recruitment, a second at ∼6 years, and a third at 9.5 years. The study was approved by the South East Multi-Centre Research Ethics Committee.Breast and other cancers occurring in the cohort were identified from recruitment and follow-up questionnaires and spontaneous reports to the study centre. Confirmation of diagnosis was obtained from the cancer registries in the United Kingdom, ‘flagging' at the National Health Service Central Registers , pathology reports, and correspondence with patients' general practitioners.Information on MHT was obtained at recruitment and from the second follow-up questionnaire, and was used to assess MHT exposure from menopause to date of breast cancer incidence or end of follow-up. Women were asked the ages or years they started and stopped episodes of MHT use, whether they were still using MHT, and the name of each drug used. We also asked participants at recruitment and in the second follow-up questionnaire how old they were when their periods stopped completely . Women who could not report age at natural menopause, because of hysterectomy without bilateral oophorectomy or because they were taking MHT or oral contraceptives around the time of menopause , were excluded from the main analyses because it was not possible to determine the age at which their ovarian function ceased. Information was also collected on other breast cancer risk factors  menopausal age.The current analytic cohort is based on all women who were recruited to the study during June 2003 to December 2009 inclusive without previous breast cancer. The recruitment cutoff at December 2009 was selected because at the time of analysis the follow-up for the second questionnaire was practically complete for this group of recruits. Women with known age at menopause entered risk at their date of recruitment or menopause, whichever was later, and were censored at the earliest date of: first invasive or gression  using atThe MHT was analysed as a time-varying exposure lagged by 1 year . Heterogeneity in HRs for subtypes of breast cancer by behaviour, oestrogen receptor status, and morphology was assessed using a data augmentation method , of whom 58 148 were established as post-menopausal before the censoring date for analysis. The first follow-up questionnaire at 2.5 years after recruitment was completed by 57 592 of these women (99.0%) and the second follow-up questionnaire at ∼6 years after recruitment was completed by 55 923 (96.2%) of these post-menopausal women (3.7% completed an abridged version by telephone). Of the remainder at second follow-up, 1.2% had died by this time, 1.7% were alive but had not completed the questionnaire although their vital and cancer status was available from ‘flagging' at the National Health Service Central Registers, and 0.9% were lost to follow-up at an earlier date  or no follow-up was available. The follow-up rate  was 99.5%.−2. in situ breast cancers that were diagnosed during 204 390 person-years (median 6.0 years) of follow-up among 39 183 women with known age at menopause (and similar descriptive statistics for 18 965 women with unknown age at menopause).Menopausal age was known for 39 183 women and was uncertain  for 18 965 women. Of those with known menopausal age, 88.9% reported a natural menopause and 9.4% reported bilateral oophorectomy as the reason for menopause; the remaining 1.7% reported various other procedures or treatments. The median interval between menopause and subsequent recruitment for the 30 113 women known to be post-menopausal at recruitment was 7 years (interquartile range: 3 to 13 years). There were 9070 women pre-menopausal at recruitment who subsequently became post-menopausal during follow-up and at that point became eligible for analysis . The following results, unless otherwise stated, are based on the women with known menopausal age. The mean menopausal age was 50.2 (s.d.: 4.6) years and mean post-menopausal BMI was 25.7 (s.d.: 4.5) kg min situ breast cancer adjusted for menopausal and attained age was 1.95  for current users of all types of MHT relative to never users (P=0.027) and at 15+ years was 2.02 . There was little difference in HR and trend after adjusting for further potential confounding variables (results shown in vs 5+ years: Pheterogeneity=0.093).The HR for invasive and er users . The HR P=0.99) and there was a nonsignificant increase in HR per year of use . For combined oestrogen plus progestogen preparations (median duration of current use 5.4 years) there was a significantly increased risk with current use compared with never use , and HR increased by 5.6% (95% CI: 1.2–10.2% P=0.011) per year of use, reaching HR=3.27  at 15+ years of use. As can be seen by the non-overlapping CIs, there was a significant difference between the HRs for breast cancer risk in relation to current oestrogen-only MHT use vs never use compared with current oestrogen plus progestogen use vs never use (Pheterogeneity<0.001). There was no heterogeneity by time since recruitment for risk of breast cancer in relation to oestrogen-only MHT use (Pheterogeneity=0.35) or combined MHT use (Pheterogeneity=0.72). Without adjustment for menopausal age, the HR for breast cancer and combined oestrogen plus progestogen MHT use was 2.64 .Analysed by type of MHT preparation , for oesP<0.001) for invasive and 1.46  for in situ breast cancer, but the difference between these was not significant (Pheterogeneity=0.18) and in situ breast cancer only accounted for 14% of cases (P<0.001) and lobular  breast cancers were both increased but not significantly different to each other  and was not significantly different to that for oestrogen receptor-negative breast cancer  was not significantly different from that for continuous combined preparations  (Pheterogeneity=0.74). For other or unspecified types of MHT, of which tibolone use made up 49%, risk compared with never users was significantly increased with current use (P<0.001), but there was no significant trend with duration of use (P=0.78). The HR for breast cancer for current tibolone use was 2.32 . Among women with no family history of breast cancer, the HR for current tibolone use was 1.60  but this was based on only three cases of breast cancer, and among those with a positive family history of breast cancer the HR was 4.15 , but again was based on only three cases of breast cancer, and the difference between the HRs was not significant (P=0.25).When analysed by type of combined oestrogen plus progestogen MHT, the HR for breast cancer for serial combined preparations . We next examined the potential biases when these analytic procedures were not done . The numP<0.001) with greater BMI among women not using MHT and among past users (P=0.030). The risk of breast cancer was increased with current use of combined oestrogen plus progestogen MHT within each category of BMI but there was no significant trend with BMI (P=0.39). The relative increase in risk for combined oestrogen plus progestogen MHT was smaller with greater BMI, for example, for BMI at +30kg m−2, the HR was (3.40/1.64=) 2.07 , BMI at 25 to <30 kg m−2 the HR was (3.49/1.36=) 2.56 (95% CI: 1.53–4.27), and for BMI <25 kg m−2 it was 3.27 , although the CIs overlapped and the trend with BMI was not significantly different to the trend among never users of MHT (Pheterogeneity=0.79).The interrelation between MHT, BMI, and risk of breast cancer is shown in In our cohort, the risk of post-menopausal breast cancer was increased with current use of MHT, as in previous studies , and the−2) was similar to that in the Million Women Study  can be compared with the Women's Health Initiative trial and observational study results for women who began combined MHT use within 5 years of menopause  , Elleste Duet , and Climagest , and the most frequently used continuous regimens were Premique , Kilovance , and Kilofem .Previous studies have found greater risks for oestrogen receptor-positive than -negative breast cancer  that can seriously misclassify actual use   .Biases may also occur if analyses included women with simple hysterectomy before menopause  or who started MHT before cessation of menstrual bleeding , and furthermore study-specific characteristics  are also likely to affect the size of bias that might be seen in other studies. The misclassification of current use of MHT may be less important in older studies conducted before results were published from the Women's Health Initiative trial  as folloA number of cohort studies have reported relative risks for breast cancer of ∼2.0 to 2.5 for ⩾10 years of combined MHT use (In conclusion, our results show that risk of breast cancer increases with duration of use of combined MHT up to ⩾15 years, and relative risks in most of the published literature are likely to be substantially underestimated because of lack of updating MHT status through follow-up in cohort studies and inclusion of women with inferred menopausal age in cohort or case–control analyses. These results provide further information to allow women to make informed decisions about the potential risks and benefits of MHT use.


Earlier studies of breast cancer, screening mammography, and mortality reduction may have inflated lifetime and long-term risk estimates for invasive breast cancer due to limitations in their data collection methods and interpretation.To estimate the percentage of asymptomatic peri/postmenopausal women who will be diagnosed with a first invasive breast cancer over their next 25 years of life.A systematic review identified peer-reviewed published studies that: 1) enrolled no study participants with a history of invasive breast cancer; 2) specified the number of women enrolled; 3) reported the number of women diagnosed with a first invasive breast cancer; 4) did not overcount [count a woman multiple times]; and, 5) defined the length of follow-up. Data sources included PubMed, Cochrane Library, and an annotated library of 4,409 full-text menopause-related papers collected and reviewed by the first author from 1974 through 2008. Linear regression predicted incidence of first invasive breast cancer, based on follow-up duration in all studies that met the our inclusion criteria, and in a subset of these studies that included only women who were 1) at least 50 years old and 2) either at least 50 or less than 50 but surgically menopausal at enrollment.2 = 0.90). Over 25 years of follow-up, an estimated 94.55% of women will remain breast cancer-free . In the 12 studies  that enrolled only postmenopausal women, an estimated 0.23% of women will be diagnosed with a first invasive breast cancer each year .Nineteen studies met the inclusion criteria. They included a total of 2,305,427 peri/postmenopasual women. The mean cumulative incidence rate of first invasive breast cancer increased by 0.20% for each year of age  of screened asymptomatic peri/postmenopasual women will not be diagnosed with invasive breast cancer each year. Approximately 95% will not be diagnosed with invasive breast cancer during 25 years of follow-up. Women who receive clinical examinations, but do not have mammograms, will have higher cancer-free rates because innocuous positives (comprising 30-50% of mammography diagnoses) will remain undetected. Informed consent to asymptomatic women should include these results and consideration of the benefits of avoiding mammograms. The value of routine breast cancer screening for women, and the dangers of breast cancer overdiagnosis  lately hThe overdiagnosis of breast cancer increases women’s stress and fear, and also results in unnecessary and invasive surgical and medical treatments. Treatments can be painful, lead to adverse events, create financial burden, inhibit sexual relationships, and increase the risk of other diseases, including ischemic heart disease –7.Overdiagnosis also distorts mortality rate calculations because the mortality rate is defined as the number of women who died divided by the number diagnosed. Increasing the number of diagnosed women by 30–50% in the screened group lowers the apparent mortality rate . The belBreast cancer incidence figures were the subject of a major 2009 report sponsored by the U.S. Centers for Disease Control (CDC). It covered 92.1% of the US population over a six-year period (1999–2004) and identified 905,402 invasive and 233,833 in situ breast cancer cases from the National Program of Cancer Registries . While iIn 2013, the CDC posted on its consumer information website that “women have a 13% lifetime risk of developing breast cancer” . The CDCSecond, women who have had breast cancer are much more likely to be diagnosed with a new primary breast cancer than women who have never had cancer . Since tThird, census data estimates suffer from the now-documented problem of undercounted populations –17, whicThese limitations affect both the numerator of the incidence fraction that is increased as women are overcounted, and the denominator that is reduced when the population is undercounted. The effects may compound when long-term risk estimates are calculated from these numbers. The CDC consumer website states that a woman has a 13% lifetime risk of being diagnosed with breast cancer, generating widespread misperception that this applies to all groups of women. If estimates of both short and long-term breast cancer risk are not accurate, the decisions asymptomatic women and their doctors make about screening cannot be well informed. We seek to provide more reliable estimates across time by stage of life by using accessible published data that overcome these artifacts of overcounting numbers of women and undercounting estimated sample size.The goal of our study was to estimate the percentage of asymptomatic women with no cancer history who will be diagnosed with a first invasive breast cancer in their peri/postmenopausal years, and to determine the likelihood that these women will remain breast cancer-free. This systematic review included published incidence data from cohort studies, screening studies, and randomized trials that examined incidence of new invasive breast cancer. It included studies that both pre-cleared women for breast cancer history and tracked potential emergence of breast cancer diagnosis. Studies focusing on other outcomes were included if they met these criteria. For example, the Women's Health Initiative randomized controlled trials, which were designed to test cardiovascular health benefits of hormonal therapy, also provided a rich source of breast-screening information.Studies were excluded if they counted a woman multiple times or relied solely on population census estimates to predict the likelihood those women would be diagnosed with breast cancer. After the rigorous selection, linear regression analysis was used to model the cumulative incidence of a first invasive breast cancer based on the duration of follow-up among enrolled women.A multi-step, systematic search protocol identified all peer-reviewed published studies in which participants had been screened for a first invasive breast cancer and met five inclusion criteria: 1) Study participants were peri/postmenopausal women with no invasive breast cancer history at enrollment; 2) The study specified the number of women enrolled; 3) The study specified the number of women diagnosed with a first invasive breast cancer; 4) Study subjects were counted only once; and, 5) The duration of follow-up was clearly defined. Studies were excluded if they only estimated the number of women screened, followed, or diagnosed with breast cancer.We examined a unique index of published papers in the field of reproductive and behavioral endocrinology of aging women compiled by the first author, Winnifred Cutler (WC) from 1974–2008 for 7 textbooks she wrote . The indArticle identification continued (Step 1) with a PubMed search for references using the search terms "breast cancer and menopause or hormone therapy (or HRT)" for articles published from 2008 through June 2012 . Dr. BurAt least one coauthor and two independent readers  reviewed every study that reported findings on breast cancer incidence. WC assessed eligibility, based on the five inclusion criteria. DM and ES also reviewed the selections. Disagreements were resolved by consensus.Two searches of the Cochrane Library databases (Steps 2 and 3) subsequently identified all eligible screening trial articles. For the first search we used the phrase, “Breast cancer incidence during screening,” , and forNo language or study design restrictions were imposed on any of the searches. When multiple publications referenced the same study, we included the latest publication that reported on the complete enrolled sample of women. Three readers  reviewed potentially eligible studies and excluded those that did not meet the criteria.After determining potential eligibility, the three readers extracted information from eligible studies: number of women enrolled; number of women diagnosed with a first invasive breast cancer; length of follow-up; and, characteristics of trial participants and inclusion/exclusion criteria . For six studies, we contacted the original investigators to verify that their study met our inclusion criteria and the counts we extracted were accurate.The primary outcome of interest for review and subsequent data analysis was the total cumulative incidence of invasive breast cancer for population subgroups. To minimize potential sources of non-response and selective outcome bias, we included only studies where outcomes were reported for all enrolled women who were followed up for a similar, specific length of time.A least squares linear regression was used to model the cumulative incidence of a first invasive breast cancer, based on the duration of follow-up among enrolled women. We used this model to generate a summary estimate of the cumulative incidence rate of a first invasive breast cancer for a given follow-up period, with corresponding 95% confidence limits. The model allowed us to quantify the effect of longer follow-up duration on the cumulative total incidence of invasive breast cancer.Existence is met since, for any fixed follow-up duration, the cumulative incidence of invasive breast cancer will have a probability distribution with finite mean and variance. Independence requires that the cumulative incidence of first invasive breast cancer be independent for each study and was assessed via careful consideration of the women and studies included in the systematic review. Linearity requires that the relationship between follow-up duration and average cumulative incidence of first invasive breast cancer be linear. Homogeneity of variance requires that the variance in the cumulative incidence of first invasive breast cancer is the same for any duration of follow-up. We assessed linearity and homogeneity of variance by inspecting a Scatterplot that related cumulative incidence of first invasive breast cancer to duration of follow-up and corresponding residual plots. Normality requires that, for any fixed duration of follow-up, the cumulative incidence of first invasive breast cancer is normally distributed; this was verified by a normal probability plot of the residuals.The 5 assumptions required for a least squares linear regression model are 1) existence, 2) independence, 3) homogeneity of variance, 4) linearity, and 5) normality. Since all assumptions for least squares linear regression were met, this statistical approach gave us an advantage over meta-analysis since it did not require pooling information from heterogeneous studies. For detecting invasive breast cancer in women it is useful to avoid pooling, because among asymptomatic women, for every five-year age group between 45–70, a screened group’s incidence of breast cancer identified is much higher in a first mammogram screening than in subsequent rescreening examinations see  10]..10].Hence, linear regression offers a reasonable estimate of long-term freedom from a diagnosis of invasive breast cancer. It uses only readily available, published information, rather than requiring information that is impossible to obtain, such as number of rescreenings.After we conducted regression analysis for all studies, we conducted parallel analyses for two subgroups by fitting separate linear regression models to studies in which women were 1) at least 50 years old at enrollment, and 2) at least 50 years old at enrollment or younger than 50 and surgically menopausal.To minimize bias and ensure that no single study had an undue influence on the results of the regression analysis, we closely examined studies that reported substantially higher/lower incidence rates than the regression model predicted. A sensitivity analysis was performed by a parallel regression analysis after we eliminated the one study that followed women for 25 years (11 years longer than any other study).A total of 687,886 records of peer-reviewed published articles were searched for relevant studies. WC’s research database contained 4,409 potentially relevant articles, and the PubMed Search, combined with those of Drs. RB and JK, returned 69 more (Step 1). Of these, we screened 331 full-text articles and identified 18 potentially eligible candidates.  Our firsThe 19 studies we included collectively document 2,305,427 peri/postmenopausal women from 10 countries see . Of thes2 = 0.90). The percentage of women who remained disease free after 25 years of follow-up averaged 94.55% .On average, the cumulative incidence rate of a first case of invasive breast cancer increased by 0.20% per year . Interim results of the Sweden-Malmo study were consistent with those of shorter studies.The Sweden-Malmo study (Study 16)  was idenWhen we restricted our attention to the 1,686,123 women in the 8 studies in which women were at least 50 years old at enrollment we also saw a linear relationship between cumulative incidence of first invasive breast cancer and years of follow up . The resModel diagnostics indicate that a least squares linear regression model is an appropriate analytic approach to quantify the effect of follow-up duration on the cumulative incidence of a first invasive breast cancer. We assumed that the studies we considered were independent because the same women were not included in multiple studies, and the studies we analyzed were not directly related. 2 = 0.91). An average of 97.34% of the women in these studies remained disease free after 10 years of routine follow-up . . In this subgroup analysis, model diagnostics identified the French Cohort Study (Study 6)  as a pot2 = 0.88) among women who were either 50 years old or surgically menopausal when they enrolled in the study.The cumulative incidence rate of a first case of invasive breast cancer increased by an average of 0.23% per year   was lowein situ lesions, which might never cause harm, remain undetected. Incidence should be lowest for asymptomatic women whose health habits reduce risk [Based on the data analyzed from the 19 published studies of 2,305,427 asymptomatic peri/postmenopausal women, over the next 25 years of their lives, the cumulative incidence of a first invasive breast cancer is ~5%. Invasive breast cancer rates should be even lower for women who do not opt for mammograms because unscreened women are not overdiagnosed, and because uce risk .The major strength of this analysis is that it used data from published studies that screened for breast cancer in samples of known size and duration of follow up. Our selection criteria ensured that the data did not rely on estimated population sizes, and did not count a single woman multiple times. We avoided pooling data for disparate groups by using linear regression to analyze the data, instead of meta-analysis. Because the 19 studies were independently designed, results did not depend on preconceived notions. We could calculate the total cumulative incidence of first invasive breast cancer for 2,305,427 women by using prospectively gathered data.The CDC lifetime risk estimate of 13% is derived from data reported by the Surveillance, Epidemiology, and End Results (SEER) Program . SEER Cashowed no additional benefit of mammogram screening and no reduction in mortality with added mammography [Earlier studies suggested that widespread screening, and its promise of early treatment for breast cancer, reduced mortality for the screened group below that of groups who were not screened , but themography . Screenemography . In 2014mography .Potential harms of widespread screening need to be weighed against benefits, and need to be clearly explained to women so that they can grant informed consent . Harms ielevated our trend line, since we included 2 studies conducted in Sweden during this critical period (9 and 16) [Limitations to our study include participant representativeness and impact of potentially cancer-inducing catastrophes. For example, the 1986 Chernobyl accident doubled the rate of breast cancer after 10 years in nearby regions , 42 and  and 16) , 32. WomWeight gain, inadequate exercise, excess alcohol and inadequate solar radiation generating vitamin D deficiencies are the 4 major risks factors well documented to increase the risk of breast cancer. Hormonal changes as a consequence of menopause or certain hormonal therapy regimens are also associated with increased risk. These topics are reviewed further See  with greBy including qualified studies from 10 different countries, participants should theoretically be heterogeneous with respect to dietary habits, solar exposure, exercise, and alcohol habits. Since low risk patients were never specifically selected for any of the 19 studies, the potential presence of some of these risk factors among participants suggests that those women who manage their exposures to these recognized risks may have an even lower incidence than calculated.Conspicuously, a 25-year follow-up for many menopausal women amounts to the balance of their lives. Therefore, for many postmenopausal women, we find their remaining, lifetime likelihood of a diagnosis of breast cancer is under ~5%.Based on these studies of more than 2 million women, each year 99.75% of peri/postmenopausal woman without a known history of breast cancer are expected to remain free of invasive breast cancer diagnosis; 95% will not be diagnosed with an invasive breast cancer during 25 years of follow-up. Given the impact of overdiagnosis, together with the lack of evidence that mammography screening actually does reduce mortality rates, and the potential harms that may result from screening, we conclude that asymptomatic women with no breast cancer history and their physicians may reasonably decide against mammogram screening.S1 File(PDF)Click here for additional data file.S2 File(PDF)Click here for additional data file.S1 Table(DOC)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S1 Text(DOCX)Click here for additional data file.S2 Text(DOC)Click here for additional data file.S3 Text(DOCX)Click here for additional data file.S4 Text(DOCX)Click here for additional data file.