More than 66% of the 200,000 newly diagnosed annual breast cancers in the US occurs in women over 55 years. Treatment advances result in excellent survival, yet older breast cancer survivors with co-morbidity may live longer, but not better after cancer. Decline in physical function, increased social isolation, and diminished economic resources increase vulnerability among older women. Rural women represent an underserved population. The purpose is to examine associations between comorbidity and predictors of health status among older rural breast cancer survivors.Baseline data of 331 BCS age 55–90 years enrolled in the Rural Breast Cancer Survivors Study. Four surveys were used for data collection. Self-reported prescription medications were used as proxy for co-morbidity. Bivariate tests of association and multivariable recursive partitioning techniques were used for analysis.Mean number of prescription medication categories reported was 3.68 . Common prescription categories were: anti-hormonal, anti-hypertensive, and cholesterol- reducing agents. 69% was overweight or obese. BMI >31 was significantly associated with both poorer physical and mental health. Multivariate analyses indicated physical health status was predicted by BMI, comorbid conditions, social support, and adverse changes in economic lifestyle. The same variables, with the exception of BMI, were predictors of mental health status.Assessing co-morbid conditions, mental health status, social support, and economic burden after breast cancer treatment may better inform cancer survivorship care and comprehensive geriatric assessment. Breast cancer is the most common female cancer with more than 200,000 new cases diagnosed each year in the United States with about 66.4% occurring in women over the age of 55 years  examine associations between co-morbid conditions, and physical and mental health status among older rural breast cancer survivors; (2) identify predictors of physical and mental health status of older rural breast cancer survivors; and (3) explore challenges to improve cancer survivorship care and comprehensive geriatric assessment.Data were drawn from the parent study, the Rural Breast Cancer Survivors Study (RBCS), a population-based study conducted in the State of Florida evaluating the dissemination and implementation of cancer survivorship interventions among rural breast cancer survivors. The RBCS was approved by Institutional Review Boards and the State of Florida Department of Health (DOH). Participants were identified through Florida cancer registry. Eligibility criteria included: at least 21 years of age, Florida rural residence, telephone access, and diagnosis of Stage 0-III breast cancer in the previous three years. Survivors receiving anti-hormonal therapy were eligible. Survivors with metastatic disease, men with breast cancer, and those lacking reliable telephone access were not eligible.Rural eligibility was established using one of two criteria: (1) residence in one of 33 Florida rural counties designated by Florida statute; or (2) residence in a rural area of an urban county having an Index of Research Access (IRA) score equal to or greater than 4  health status, (2) co-morbid conditions, (3) sociodemographic and treatment characteristics, and (4) social support.The Medical Outcomes Study Short Form v1 (SF-36) was used to assess self-reported health status  questionnaire assessed social support  was imputed using the Multivariate Imputation by Chained Equations (MICE) procedure, with CART (Classification And Regression Trees) as underlying modeling technique  was divided into four categories: underweight, normal weight, overweight and obese, based on CDC definitions  included employment status, BMI, social support, family income, and changes in economic lifestyle. Characteristics significantly associated with MCS scores , reported more than two prescription categories in combination with low levels of social support. In contrast, the 57 participants with the highest average PCS of 52.5  reported no more than two prescription categories, and no adverse changes in economic lifestyle since end of cancer treatment. Ninety-three participants with high BMI (over 31.88) reported low average PCS of 38.5 , or approximately one standard deviation below the U.S. adult average.The non-linear multivariable tree model for PCS scores Figure  showed tMI over 3.88 reporterminal node 8) had an average MCS of 50.4 which was almost a standard deviation higher than the average among 32 who reported more than three prescription categories estimated at 41.5 . The 57 participants with less than midrange social support scores  had the lowest average MCS at 40.2. In contrast, 154 participants who reported no adverse changes in economic lifestyle and levels of social support of at least 79% of the maximum scores had the highest average MCS of 54.2, or 40% of a standard deviation above the general U.S. adult average MCS score.The non-linear multivariable tree model for MCS scores Figure  showed tSignificant associations between co-morbidity and health status were noted. The majority was overweight or obese which was significantly associated with both poor physical health and poor mental health. Implications of this finding are exacerbated by the reality that increased BMI is a risk factor for many diseases including cardiovascular disease, selected cancers, diabetes, and other ailments , the list of co-morbid conditions was not comprehensive, and therefore certain health conditions may not have been detected. For example, some participants described having joint or musculoskeletal pain. This type of pain is a known side effect of aromatase inhibitor therapy for which they may have been taking pain medication. Yet, a specific prescription category for joint or musculoskeletal pain and arthritis was not contained in the study instrument. Third, BMI was calculated by self-report of weight and height, which may have resulted in inaccurate estimates of actual BMI, particularly at the very low or very high end of weight (McCaskill-Stevens & Abrams Finally, the possible critically important role of diabetes in this population is recognized. Yet, we do not know if the present sample had a lower incidence of diabetes or if they had a higher incidence of undiagnosed diabetes. If the latter is true, this would place older rural breast cancer survivors at an even greater risk. Thus, it is an important issue to address in future research.The intersect among three factors: aging, cancer, and co-morbid conditions represent characteristics of a growing population of cancer survivors having unique survivorship needs that may place them at a higher risk of vulnerability, economic changes, and decline in social support after treatment ends. The implications and need for future research into the quality of life of older breast cancer survivors are broad as the population continues to age and people live longer after diagnosis. The complexity of needs experienced by aging breast cancer survivors need to be addressed. Because of the multifaceted nature of health in cancer survivors, follow-up and survivorship care for older breast cancer survivors would ideally include comorbid disease, social support, and adverse changes in economic lifestyle.While all breast cancer survivors may be at risk for not receiving services that may make a difference in their post-treatment quality of life, rural dwelling women may be at particular risk. Understanding the exact nature of similarities and differences in ruaral versus urban dwelling women may help ameliorate some of these risks and provide guidance as to precise nature of services that are warranted.


It remains unclear whether the increased risk of colorectal cancer (CRC) associated with obesity differs by gender, distribution of fat, tumour location and clinical (TNM) stage. The primary aim of this study was to examine these associations in 584 incident colorectal cancer cases from a Swedish prospective population-based cohort including 28098 men and women.Seven anthropometric factors; height, weight, bodyfat percentage, hip circumference, waist circumference, BMI and waist-hip ratio (WHR) were categorized into quartiles of baseline anthropometric measurements. Relative risks of CRC, total risk as well as risk of different TNM stages, and risk of tumours located to the colon or rectum, were calculated for all cases, women and men, respectively, using multivariate Cox regression models.Obesity, as defined by all anthropometric variables, was significantly associated with an overall increased risk of CRC in both women and men. While none of the anthropometric measures was significantly associated with risk of tumour (T)-stage 1 and 2 tumours, all anthropometric variables were significantly associated with an increased risk of T-stage 3 and 4, in particular in men. In men, increasing quartiles of weight, hip, waist, BMI and WHR were significantly associated with an increased risk of lymph node positive (N1 and N2) disease, and risk of both non-metastatic (M0) and metastatic (M1) disease. In women, there were no or weak associations between obesity and risk of node-positive disease, but statistically significant associations between increased weight, bodyfat percentage, hip, BMI and M0 disease. Interestingly, there was an increased risk of colon but not rectal cancer in men, and rectal but not colon cancer in women, by increased measures of weight, hip-, waist circumference and bodyfat percentage.This study is the first to show a relationship between obesity, measured as several different anthropometric factors, and an increased risk of colorectal cancer of more advanced clinical stage, in particular in men. These findings suggest that risk of CRC differs according to the method of characterising obesity, and also according to gender, location, and tumour stage. Colorectal cancer (CRC) is the third most common malignancy in developed countries with approximately 1 million new cases every year , includiNumerous epidemiological studies and meta-analyses have examined the relationship between body weight and body mass index (BMI) and CRC, mainly risk of colon cancer, and most studies have shown a positive relationship between a high BMI and risk of colon cancer in men, whereas weak or no associations were reported in women -16. The A small number of studies have examined associations of other anthropometric factors than BMI and CRC risk according to tumour location; i.e. colon or rectum ,6,14,22.To our knowledge, only two previous studies ,18 have The Malmö Diet and Cancer Study (MDCS) is a population-based prospective cohort study, forming part of the European Prospective Investigation into Cancer and Nutrition (EPIC) that enrThe main purpose of the MDCS was to further investigate the associations between a Western diet rich in fat and low in fruit and vegetables and certain forms of cancer. Participants in the MDCS and EPIC cohort include 11063 men (39.4%) and 17035 women (60.6%) between 44 and 74 years of age. Data on lifestyle, health and socio-demographic characteristics were collected via standardized self-administered questionnaires. Ethical permission for the MDCS (LU 90-51) and the present study (LU 530-2008) was obtained from the Ethics Committee at Lund University.2. Waist circumference was measured at the midpoint between the lower ribs and the iliac crest, and for hip circumference the level of greatest lateral extension was used. These measurements were estimated to the nearest 0.01 m. The waist and hip circumferences of each participant were used to calculate waist-hip ratio  as an additional measure of fat distribution. Body composition was estimated using a single frequency bio-impedance methodology  with tetra polar electrode placement and subjects in a supine position. Lean body mass and fat mass were determined and served to calculate body fat percentage. The BIA method has previously been validated in Swedish middle-aged and elderly adults [At baseline examination, weight (multiples of 0.1 kg) and height (to the nearest 0.005 m) was measured by a trained nurse, and body mass index (BMI) was calculated as kg/my adults .Incident cases of invasive colorectal cancer in the MDCS were identified through the Swedish Cancer Registry and vital status was determined by record linkage with the Swedish Cause-of -Death Registry. End of follow-up was 31 December 2009. Information on vital status and cause of death was obtained from the Swedish Cause of Death Registry until 31 December 2009. Time on study was defined as time from baseline to diagnosis, death or end of follow-up 31 December 2009. Median time from baseline until diagnosis was 8.6 (SD = 4.3) years and the median follow-up time in the entire cohort was 13.7 (SD = 3.2) years.Among the 28098 men and women in the cohort, there was a total number of 584 cases of incident colorectal cancer. Eight tumours were re-classified as tumour in situ (TIS), and these were not included as cases. A total number of 181 cases were diagnosed with CRC before baseline examination, i.e prevalent colorectal cancers, and therefore excluded from the study. Cases with other prevalent cancers were not excluded from the study.Patient and tumour characteristics in the cohort have been described in detail previously -30. The Distribution of established and potential risk factors for CRC was compared between CRC cases and the rest of the study cohort. Anthropometric measurements were divided into quartiles. Separate quartiles were calculated for men and women for this analysis , and for those who did not (rest of cohort) is presented in Table As shown in Table As shown in Table Separate analysis of risk of colon and rectal cancer demonstrated an overall increased risk of colon cancer for all anthropometric factors except for bodyfat percentage Tables  and 7. WAmong women, all anthropometric factors except height and WHR were significantly associated with risk of a more advanced T-stage in rectal but not colon cancer, while there were no associations with risk of more advanced N-stage, neither in colon nor rectal cancer (data not shown). In addition, there was a significant association between height and M1 disease in colon but not rectal cancer in women (data not shown). In men, there were no associations between anthropometric factors and risk of more advanced T-stage in rectal cancer, but in colon cancer, only height was associated with a statistically significant increased risk of T-stage 3 & 4 disease (data not shown). Moreover, among men, there was a statistically significant increased risk of developing N1-2 tumours related to height, weight, waist and hip in colon and to hip, BMI and WHR in rectal cancer, and a statistically significant association between BMI and M1 disease in colon but not rectum (data not shown).The results from this large prospective cohort study indicate that the association between obesity and risk of CRC varies by gender, cancer site and tumour aggressiveness. All anthropometric factors except bodyfat percentage were significantly associated with an increased risk of CRC in general, which corresponds well to previous findings ,18,19,32To our knowledge, only two previous studies ,18 have We have thus been able to demonstrate an increased risk of more advanced tumours with increased anthropometric measures, particularly in men, among whom several anthropometric variables were significantly associated with risk of a more advanced T-stage, N2 disease, and both M0 and M1-tumours. In women, several anthropometric variables were associated with an increased risk of more advanced T-stage, but not node-positive disease. Furthermore, increased anthropometric measures were only associated with non-metastatic (M0) disease in women. Taken together, these findings suggest that overweight persons have an increased risk of developing more advanced colorectal cancer forms, but that this risk may differ according to gender.Moreover, our findings provide further evidence of gender-related differences in tumour susceptibility of cancer in the colon and rectum, respectively, as we found a positive association between obesity and risk of developing colon cancer in men and rectal cancer in women. This has to our knowledge not been shown previously, since only a few studies have examined risk of colon and rectal cancer separately. However, two previous studies ,14 have Body weight or BMI have been the most commonly used anthropometric measurements to examine the associations of obesity and colorectal cancer risk in previous studies, the majority of which have shown a positive relationship between BMI and risk of CRC in men, but week or no associations in women -16. HoweThe exact biologic mechanisms underlying the association between obesity and increased risk of CRC are not fully understood. Some authors have suggested components of the metabolic syndrome, in particular insulin-resistance and subsequent hyperinsulinemia, to be the underlying link, which may reflect the growth-promoting effects of insulin ,34. ThesSeveral epidemiological studies have shown that elevated levels of estrogen and progesterone is associated with lower risk of developing CRC -49. ReceIn agreement with most previous reports, we found a stronger association between body size and risk of colon compared to rectal cancer in general, in particular in men . In lineA limitation to the present study is the relatively small number of cases in some subgroups, i.e. it is possible that some of the non-significant findings in relation to gender or tumour stages may have been caused by a potential type II error. Therefore, these data need to be validated in larger patient cohorts. It should also be pointed out that since mean age at diagnosis was >70 years for women , interprCertain methodological aspects need further attention. The validity of the anthropometric measurements is one aspect as there may be a potential inter-observer variation. Recommendations for the nurses performing baseline examinations described how participants should be dressed, in which position the participants should be examined, and location for the estimation of waist- and hip measurements. We therefore consider the risk of misclassification of anthropometric measurements to be low. In contrast, most previous studies have used self-reported anthropometric measures.It is also possible that participation in the MDCS was associated with body constitution, which may have lead to potential selection bias. In a previous paper, Manjer et al  comparedAnother aspect is the validity of collected data. As anthropometric data was assessed only at baseline, it is possible that some individuals have gained and some have lost weight. Such a misclassification is likely to lead to an attenuation of risks and, if anything, observed risks may be underestimated.In addition, it might be difficult to apply incidence rates from the MDCS to the background population as participants may to some degree have been selected in terms of socio-economic factors and risk of CRC. Nevertheless, we consider it possible to make internal comparisons comparing subjects with high versus low levels of the study measurements in order to obtain relative risks.This study is the first to show a relationship between obesity, measured as several different anthropometric factors, and an increased risk of colorectal cancer of more advanced clinical stage, in particular in men. These findings need to be confirmed in future studies, as they may be of importance in the development of novel strategies for prevention of the disease, such as tailored screening programmes taking sex and anthropometric factors into account.CRC: Colorectal cancer; MDCS: Malmö diet and cancer study; BMI: Body mass index; WHR: Waist-hip ratio; T-stage: Tumour stage; N-stage: Nodal stage; M-stage: Metastatic stage; HRT: Hormone replacement therapy.The authors declare that no competing interests exist.JB performed the statistical analyses and drafted the manuscript. SW, BN and AG collected clinical data. JM assisted with the statistical analyses and helped draft the manuscript KJ conceived of the study, carried out the histopathological re-evaluation, and helped draft the manuscript. All authors read and approved the final manuscript.Distribution of quartiles of anthropometric measurements.Click here for file


BRCA1 or BRCA2 face a unique set of challenges related to managing cancer risk during a demographically-dense stage of life. They may struggle with decision-making in the absence of clear age-specific guidelines for medical management and because they have not yet fully developed the capacity to make life-altering decisions confidently. This study sought a patient-centered perspective on the dilemmas faced by 18–24 year olds who completed BRCA1/2 gene mutation testing prior to their 25th birthdays.Young women who have been identified as carrying a deleterious mutation in BRCA1/2-positive women recruited through cancer risk clinics, hospital-based research centers, and online organizations. All 32 participants were women aged 21–25 who tested positive for a BRCA1/2 gene mutation between 2 and 60 months prior to data collection. Investigators used techniques of grounded theory and interpretive description to conduct both within and cross-study analysis.This study integrated qualitative data from three independent investigations of Participants expressed needs for (1) greater clarity in recommendations for screening and prevention before age 25, especially with consideration of early and regular exposure to radiation associated with mammography or to hormones used in birth control, and (2) ongoing contact with providers to discuss risk management protocols as they become available.Health care needs during the young adult years evolve with the cognitive capacity to address abrupt and pressing change. Specific needs of women in this population include a desire to balance autonomous decision-making with supportive guidance, a need for clear, accurate and consistent medical recommendations. Optimally, these women are best cared for by a team of genetically-oriented providers as part of a sustained program of ongoing support, rather than seen in an episodic, crisis-driven fashion. A discussion of insurance issues and provider-patient cultural differences is presented. BRCA1 or BRCA2 genes increase a woman's lifetime risk of breast and ovarian cancer. By age 70, approximately 60–70% and 45–55% of BRCA1 and BRCA2 mutation carriers will develop breast cancer, respectively; 40% and 20% of BRCA1 and BRCA2 mutation carriers will develop ovarian cancer relative terms , they may be viewed quite differently if presented in absolute terms .Deleterious mutations in the BRCA1/2 mutation testing may be offered once a woman reaches age 18 BRCA1/2 mutation testing may receive highly personal and emotionally-charged cancer risk information before they are able to confidently manage this risk. The typical primary care provider is often not equipped to bring a balanced, authoritative perspective to the extraordinary concerns faced by these women. Consequently, young carriers experience distress that is both quantitatively and qualitatively different from that of older mutation-positive women BRCA1/2-related risk aggregates participants across the lifespan in recruitment and data analysis, obscuring development of evidence-based risk management tailored to the unique developmental needs of the youngest consumers. We sought a patient-centered perspective on the dilemmas faced by 18- to 24-year-olds as they considered BRCA1/2 genetic testing and risk management.Most extant literature regarding psychosocial aspects of BRCA1/2 mutation-carriers during their reproductive years. Beginning in 2003 and 2009, Werner-Lin BRCA1/2-positive women aged 18–35 from the University of Chicago Cancer Risk Clinic and the National Cancer Institute, respectively, plus through national online organizations. All data for those studies was collected either via in-person interviews conducted in the Chicago metro area (Werner-Lin) or via telephone interview based in Bethesda, but targeting women from across the US (Hoskins) Investigators performed these investigations after approval by appropriate local Human Investigations Committees in accord with an assurance filed with and approved by the Department of Health and Human Services, where appropriate. Investigators obtained written informed consent from each participant.Data were drawn from three separate qualitative studies; each used a developmental frame to investigate the experiences of BRCA1/2 mutation testing prior to their 25th birthday were eligible for participation. Six unaffected women aged 21–25 consented to participate.Data from participants aged 18–27 who were ≤25 when they completed genetic testing were eligible for this secondary analysis. We chose to limit analysis to only women aged 25 or younger at the time of testing in order to understand the unique needs of these very young consumers of genetic testing services; due to the absence of clear age-specific guidelines for medical management and the complex and dense demographic shifts that occur during young adulthood , we hypothesized that the needs of women in this age range would be qualitatively different from those of women in their later twenties and thirties. Alphanumeric identifiers were assigned to 26 eligible individuals see  All undeInvestigators independently collected in-depth, semi-structured interview data from 2004–2009. Investigators' interview guide elicited data-rich reports of: family experiences with cancer and genetic testing; impact on family, peer and romantic relationships; beliefs about how cancer risk influences individual development; family formation; and attitudes towards risk-reduction. Investigators jointly developed a focus group guide based on findings from their earlier studies to address perspectives on: learning about cancer risk before age 25; cancer risk-management; the impact of genetic testing on identity, sexuality, family and social life; and family formation. After consenting, each participant selected a pseudonym to identify herself and within eight weeks of the 90-minute focus group, all participants completed a family history phone interview.verbatim. Using the constant comparative method, investigators independently examined a subset of transcripts from each study to generate provisional codes. Once a working list of codes was established, all transcripts were reread and coded. Grounded theory techniques were used to facilitate agreement on a set of codes that best represented each dataset. Investigators approached the separate codebooks as three waves of data collection to capture changes to standard care protocols, public policy addressing insurance and discrimination concerns, and the social perceptions of genetic susceptibility during each time frame All data were audio-recorded and professionally transcribed BRCA1 (n = 19) or BRCA2 (n = 13) mutation carriers. At the time of initial data collection, 13 women were single, 15 were in relationships, and 4 were engaged/married. Two had children, 24 planned to have children, and six did not want children or were undecided. None had developed breast or ovarian cancer. None were pregnant, and none reported pursuing genetic testing to inform family planning. The majority had made active lifestyle choices to support healthy living since learning their mutation status. Five had completed risk-reducing bilateral mastectomy (RRBM) or had the procedure scheduled in the coming months; none had scheduled or completed risk-reducing salpingo-oophorectomy (RRSO).Data from 32 women aged 21–27 (mean age = 23.2) were included in the current analysis. All were confirmed Reza (25) shared:Overall, participants expressed satisfaction with the care they received from the variety of providers with whom they had contact during the process of genetic testing and initiation of risk management. Participants valued providers who acknowledged their priorities, fears, and obligations. Numbers after each participant pseudonym indicate age at the time of data collection. A doctor [said], “Right now there's really no reason to (have a mastectomy) In the next few years there's probably going to be advances. I'm not telling you to wait fifteen years…” Because in my head it was, why should I wait until after I get cancer? But he was, like, “Wait till you're thirty.” And I was, like, “Okay, that makes sense to me.”Pam's mother was diagnosed with breast cancer at age 32, so Pam (22) initiated screening at 21 “They said the breasts have to go by 25. And between 30 and 35 the ovaries would need to go. I went to the surgeon and talked to her about it, and I gave her my reasons for not wanting to wait, she agreed with me. Which was nice.”BRCA1/2 mutation in their family prior to their own genetic testing. Yet, many found it difficult to have their requests for screening adequately addressed. Monique (25) remembered, “…everybody was like, ‘oh, you're too young to know what you want.’… the primary response was never, ‘no, you shouldn't do it because medically it's not necessary.”Nineteen participants knew of the Linda (23) completed genetic testing at her gynecologist's suggestion. She recalled receiving her test results:Incompletely developed genetic and health literacy led several participants to misunderstand their risk of inheriting a mutation, cancer risk estimates associated with being a mutation carrier, or the residual risk of cancer post surgical risk-reduction. I got a phone call from my gynecologist saying, “I was afraid of this but you tested positive.” And I was like, “test positive for what? I have no idea what you're talking about.” And she was like, “for the genetic mutation.” Had I been smart I would have seen the genetics counselor first.Hannah (19) provided an example of a common misunderstanding of statistics at they relate to genetic risk. She reported:A lack of clear expectations about genetic testing and the implications of one's carrier status complicated participants' interpretation of test results. (T)he way the genetic counselor explained it to us … there's only like a 25% chance of us both having it. [Since I have it], it's less likely [my sister] has it.Hannah did not understand that one sister's mutation status was unrelated to the other's individual probability of being a mutation carrier Melissa (27) stated, “some of the research is conflicting concerning different things, and it sort of perturbed me that it wasn't presented to me that way. It was presented to me as ‘never take birth control.’” Melissa wanted her providers to directly address the uncertainty regarding birth control pills. Yet, participants also valued autonomy in making choices; they wanted to weigh differing perspectives to come to a decision that best fit their own needs, rather than having their providers make choices for them.Participants acknowledged that incomplete health literacy increased their need for expert guidance. Hannah reported, “I never took birth control because, in the beginning, they thought those hormones could actually be really negative for me. Now I hear, ‘We were wrong. You should have been taking birth control all these years.’” In the early years of managing women with BRCA1/2 mutations, one major concern related to the possibility that exogenous hormones might further increase the risk of breast cancer – the most frequent syndrome-related malignancy. Newer data suggest that there is little evidence of increased breast cancer risk among mutation carriers using oral contraceptive formulations prescribed since 1975, while a 50% reduction in the risk of BRCA-related ovarian cancer is now widely accepted as an important benefit related to OC exposure Participants expressed frustration at receiving inconsistent, inaccurate, ambiguous or incomplete recommendations from providers regarding their cancer risk management. During the initial phase of their mutation-positive experiences, participants reported receiving information from genetic counselors, oncologists, obstetrician/gynecologists, breast surgeons, and general practitioners, each with her/his own discipline-specific perspective and knowledge base. BRCA-related male breast cancer penetrance is so much lower than that for females, providers and consumers often mistakenly believe hereditary risk of breast/ovarian cancer is passed only through the maternal bloodline. Ruth recalled a physician telling her that since cancer was present on the paternal side of her family, she “[didn't] have anything to worry about, or maybe we'll start giving you a mammogram a little bit earlier than normal.”Isabelle (22), whose mother developed breast cancer at age 25, was frustrated by her inability to access screening; despite a letter signed by a doctor confirming her need for MRI, another provider refused to start screening before she turned 25. Given her family history, she perceived this to be too late.Since Alysha (26), who sought out a great deal of information online, shared “(I was) very frustrated with the conflicting information that doctors were telling me, particularly about screening – when and how often and the consequences of various tests.” Participation in the annual meeting of a consumer advocacy group validated her desire to gather information to feel well-informed. After attending the conference, she reported “I feel much better informed about what I should be doing and what those types of screenings actually do and possible side effects and accuracy.”Lynn (23) carried a mutation, yet she received the message from her physician that “you don't need a mammogram at this age.” This led her to feel out of place in the healthcare system and frustrated at her inability to access screening. Feeling “paralyzed” by this roadblock, she completed bilateral mastectomy at age 22, believing it to be the only way to effectively manage her cancer risk Genetic testing at age 18 confirmed Tracy (26) recalled,Like older mutation-positive women in the two original study cohorts I was talking to my genetic counselor, saying “I'm finally ready to get my breasts removed, who should I contact?” She found me the best surgeon in the state, who's wonderful. And she said “If you're still not interested in having kids, they've discovered tubal ligation can reduce your [ovarian cancer] risk. This might be a good option for you.”Ashley (24) recalled that her physician told her “…to start thinking about having kids before I'm 30 because if you breastfeed before you're 30, it reduces your risk of breast cancer” and she reported thinking, “oh jeez, I gotta get moving here.”Charlotte (25) recalled that physicians she saw in the context of a research study told her to “start having kids at any time, get that done with..,” contributing to her feeling of urgency to complete childbearing so that RRSO could be pursued. Although Ashley experienced this recommendation as informative and supportive, Charlotte was distressed by her perceived need to act quickly.Reza's mother was in active chemotherapy treatment following her second ovarian cancer recurrence in three years. Reza (25) wanted to undergo RRSO, but her providers advised against it. She shared, “Nobody would give me a reason that seemed real besides ‘you're too young, you'll want to have kids someday.”Sara (22) also met with resistance about her decision to undergo RRSO, despite her certainty that she did not wish to have biological children. She lamented, “I've gone to the doctor and expressed my fear of cancer. There's never been the acknowledgement of, ‘okay I hear you, you don't wanna have kids; if you wanna do surgery now, that's great.’”and risk management. The Affordable Care Act of 2010, which requires group health plans to provide coverage for dependent children of policy-holders until their 26th birthday, may levy additional pressure to decide early about risk-reducing surgery Barriers to effective utilization of the healthcare system to reduce mutation-related cancer risk lead young women to feel uncertain about risk-management, concerned about reproductive decisions, and pressured to make quick choices. Participants valued providers who addressed their priorities and obligations. They desperately wanted evidence-based guidance to inform their decisions, yet they reported receiving incomplete and inconsistent recommendations from providers with limited expertise in hereditary cancer risk assessment and management. Participants experienced being treated as too young both to know what they wanted and to make major healthcare decisions independently. Incomplete health literacy led many participants to overestimate their cancer risk, focusing on lifetime rather than shorter-term, and relative rather than absolute risk, indicating the need for providers with quantitative expertise in hereditary cancer genetics to facilitate ongoing education. The combination of inflated short-term risk perceptions, limited proven age-specific risk management strategies, and well-intentioned but inaccurate provider recommendations all created pressure to rush childbearing, so that surgical risk-reduction could be implemented. Utilization of services from genetically-oriented providers may support patients' acquisition of developmentally and medically sound knowledge of cancer risk Inaccurate cancer risk perceptions may increase distress in young women, cause them to delay genetic testing (if risk is inaccurately perceived as low), or to initiate risk-reducing surgery precipitously (if short-term risk is inaccurately perceived as very high) Rapid uptake of risk-reducing surgery following genetic testing, as seen in our sample, is driven by the perception that cancer risk is imminent. The need to accurately convey short-to-intermediate cancer risk (over 5–10 years) represents a major challenge.Our data suggest discrepancies may exist between patient and provider responses to inherited cancer risk, further indicating the need for providers with expertise in both cancer genetics and the developmental needs of adolescents transitioning to adulthood. Providers may have difficulty believing that a 20-year-old faces similar risks to those observed in older mutation carriers. Trust in provider recommendations seemed to erode as differences between provider and consumer expectations grew. Providers may suggest women in their 20s postpone risk-reducing surgery until after childbearing to reinforce that imminent cancer risk is quite low, or because they assume young patients prioritize having children. Yet, recommendations linking risk management and family formation may signal to patients that physicians perceive short-term risk of cancer to be very high. When young adults are not ready to commit to life-long partnerships or to become parents, these well-intentioned recommendations are interpreted as a failure to be taken seriously. Striking generational and gender socialization differences may exist between patients and providers, leaving young women struggling to feel understood by those helping them make decisions about their care. Optimally, providers can convey the caring expected from an expert, while maintaining the neutrality necessary to guide patients confidently to individually-tailored and thoughtful decisions.Ideally, young women would learn all the facets of risk management early in their experience as mutation carriers, allowing them to manage risk confidently. However, our data suggest that rapid developmental changes common during the transition to adulthood may necessitate a prolonged period of care for young women, whose needs are distinct from older mutation carriers for whom standard practice guidelines and clinical trials were designed. In the context of limited evidence, young women need to work methodically with providers who are knowledgeable and non-judgmental, to avoid rushing into decisions inconsistent with their life goals. Provider recommendations may be carefully tailored to attend to developmental readiness while still providing an integrated approach to care. Such a model may enable ongoing connection with patients as shifting life circumstances precipitate interest in more aggressive risk-reduction strategies.BRCA-related cancer risk evolved. We maintained separate codebooks for each study to ensure temporal differences in standards of care and public policy were accounted for during analysis. All three studies recruited women who completed genetic testing before age 25. However, none recruited individuals aged 18–20 at the time of data collection. None enrolled racial or ethnic minority women, subpopulations which are under-represented in high-risk clinics. Uptake of genetic testing remains particularly low for women of African descent Participants received care over a thirteen-year period during which the treatment of BRCA1/2 mutation carriers comprise a unique subset of high-risk women who require particularly thoughtful individualized expert care to meet their complex needs. Insuring accurate understanding of absolute short-term cancer risk is essential to informed decision-making.Young


The UK Parliamentary Enquiry and USA Institute of Medicine state that lesbians may be at a higher risk of breast cancer but there is insufficient information. Lesbians and bisexual (LB) women have behavioural risk-factors at higher rates compared to heterosexuals such as increased alcohol intake and higher stress levels. Conversely, breast cancer rates are higher in more affluent women yet income levels in LB women are relatively low. This systematic review investigated all evidence on whether there is, or likely to be, higher rates of breast cancer in LB women.Cochrane library , MEDLINE, EMBASE, PsychINFO, CAB abstracts, Web of Science , SIGLE and Social Care Online databases were searched to October 2013. Unpublished research and specific lesbian, gay and bisexual websites were checked, as were citation lists of relevant papers. Included were studies in LB populations reporting breast cancer incidence or prevalence rates, risk model results or risk-factor estimates. Inclusions, data-extraction and quality assessment were by two reviewers with disagreements resolved by discussion.Searches found 198 references. No incidence rates were found. Nine studies gave prevalence estimates - two showed higher, four showed no differences, one showed mixed results depending on definitions, one had no comparison group and one gave no sample size. All studies were small with poor methodological and/or reporting quality. One incidence modelling study suggested a higher rate.Four risk modelling studies were found, one Rosner-Colditz and three Gail models. Three suggested higher and one lower rate in LB compared to heterosexual women. Six risk-factor estimates suggested higher risk and one no difference between LB and heterosexual women.The only realistic way to establish rates in LB women would be to collect sexual orientation within routine statistics, including cancer registry data, or from large cohort studies. Recent US and UK Government policy documents have stated that there may be higher rates of breast cancer in lesbians and bisexual women (LB women), but the evidence that this is based on is unclear. For example, in 2009 the Report by the UK All Party Parliamentary Group on Cancer’s Inquiry into Inequalities in Cancer stated t“While the relative risk of breast cancer for lesbians and heterosexual women is the topic of much discussion, a definitive answer is still unavailable. It is believed that lesbians may be at higher risk for breast cancer because there is some evidence that they have a higher prevalence of certain risk factors, including nulliparity, alcohol consumption, smoking, and obesity.”.It has long been thought within the LB women’s community that there is a higher rate of breast cancer. As the However, sexual orientation has not yet become part of demographic data collection for cancer intelligence agencies in the UK or USA nor have any cohort studies measuring incidence of breast cancer collected data on sexual orientation. So healThere are several reasons as to why there might be an increased risk of breast cancer in lesbians and bisexual (LB) women. For example, there are several known behavioural risk factors at higher rates in LB compared to heterosexual women such as increased alcohol intake and higher stress levels. Also prConsiderable work has been undertaken to try to quantify the amount of increased risk in factors associated with an increased risk in breast cancer. For exaThis systematic review investigates all evidence on whether there is, or likely to be higher rates of breast cancer in LB women. It includes relevant incidence and prevalence studies and all studies where risk factor models or estimates have been applied to any LB population.A protocol was developed and a scoping search was undertaken in November 2009. The following databases were searched: Cochrane library , MEDLINE, EMBASE, PsychINFO, CAB abstracts, Web of Science , SIGLE, Social Care Online to February 2010, updated in October 2013. Unpublished research and material only available on lesbian, gay and bisexual (LGB) specific websites was checked. Contact with experts was made, including the Boston Lesbian Health Project (USA). Citation lists of included and excluded studies and reviews were checked. The following search terms were used: lesbian, gay women, queer/bisexual/sexual preference/sexual orientation + female, breast cancer, breast carcinoma, breast neoplasm.Included were studies in any LB populations measuring and presenting breast cancer incidence or prevalence rates, risk factor estimates or risk model results. All identified citations (titles ± abstracts) were screened by two reviewers. Data extraction and quality assessment were by two reviewers with disagreements resolved through discussion. Quality assessment assessed selection, performance, attrition and detection biases where possible, appropriate to study designs. There are no specific quality assessment checklists for prediction modelling studies but there is a list of criteria recently published by Altman. This wa•Study design – prospective cohort better.•Patient sample - participants followed up from a common event.•Sample size – power depends on number of events so if a general population sample needs large numbers or long follow up or both. Suggested needing ten times the number of events to the number of variables studied.•Incomplete data, missing or lost to follow up are difficult problems that reduce power and probably bias. Completeness of data should be reported.•Use of continuous variables better than categorisation into low and high risk groups.•Not useful to have participants split into multiple risk groups, up to three better .•Needs to have validation study in an independent sample.Study characteristics and results were tabulated and assessed qualitatively. Results were interpreted in light of methodological strengths and weaknesses identified in quality assessment. No meta-analysis was appropriate because of heterogeneity of study populations and study designs.From the database searches 198 references were found of which 24 were duplicates. Additional internet and citation searches yielded three more references. Flow of review information is shown in Figure There was no published information on incidence of breast cancer in LB women in any country found.Nine studies were found giving information on prevalence. One was an unpublished cross-sectional survey from the UK (Prescription for Change). The othBrandenburg et al. (2007) gave a prevalence of 2% lesbian and 3% heterosexual women who had reported ever being diagnosed with breast cancer, but it was not possible to determine the size of the sample these percentages came from and the numbers in the paper did not add up correctly so these results should be treated with caution.Cochran et al. 2001) reported the results of seven large studies on lesbian and bisexual women conducted in various parts of the USA between 1987 and 1996. The sam reportedFrisch et al. (2003) is a cohort study with linIt is unclear how representative of the lesbian population this sample was. There is no information on social class or education levels. As 1989 was the year that Denmark passed its law permitting homosexual partnerships (the first in the world), the sample was among the first partnerships to be recognised and many may have been in long-term relationships beforehand. Also, the sample size is relatively small so the 95% confidence intervals for the relative risk estimate are quite wide, and the follow up period is short.Kavanaugh-Lynch (2002) did not ask sexual orientation directly but used three different demographic indicators to suggest lesbian sexual orientation. These wRankow and Tessaro (1998) reported the results of a survey conducted in North Carolina among the LB community between June and November 1995. ApproxiRoberts et al. (2004) reported the results of a retrospective medical chart audit of patients attending a specialist women’s health services clinic providing healthcare to young, low-income women in urban San-Francisco and had significant outreach to the lesbian community. IncludeIt was noticeable in the abstract and conclusions that mention was made of the differences in risk factors for breast cancer between lesbians and heterosexual women but not the similarity in breast cancer rates. However, it is likely that the sample was too small to demonstrate a difference in breast cancer diagnosis between the two groups and the 95% confidence intervals were wide. Also the study participants were relatively young.Valanis et al. 2000) reported the results the Women’s Health Initiative Study on 93,311 heterosexual and non-heterosexual post-menopausal women[00 reportThe percentages of non-heterosexual women seem rather low. There were an additional 2697 women who preferred not to indicate their sexual orientation. The split between lifetime and adult lesbian seems rather arbitrary and the categorisation was based on recent sexual behaviour rather than sexual orientation.Zaritsky and Dibble (2010) reports This interesting paper is limited in population because it could only include lesbians who had a heterosexual sister. Therefore, a relatively large number of lesbians who have no siblings, only lesbian sisters or only brothers would be excluded. Also, women whose sisters had already died (possibly from breast cancer) would also not have been eligible to take part in the study. The study was also relatively small. Also, the prevalence of breast cancer found was remarkably high. Although the recruitment strategy is not clear, it seems likely that participants were recruited on the basis of being lesbians with breast cancer, or with an interest in breast cancer. Therefore, since the snowball recruitment was via the lesbian community, it is more likely that the lesbians would have had a higher rate than their heterosexual sisters.The Prescription For Change Survey was a survey conducted on behalf of the Stonewall charity by Ruth Hunt and Dr Julie Fish, with assistance from Sigma Research , associated with the University of Portsmouth. It was funded by Lloyds TSB Foundation. The report is avail“one in twelve lesbian and bisexual women aged between 50 and 79 have been diagnosed with breast cancer, compared with one in twenty women in general”.The “one in twenty” statistic is not referenced so it is unclear where this has come from. The age distribution of the sample is not known, other than the range of 14–84. If a roughly normal distribution is assumed, the sample size will be approximately 2954 women. However, it is likely that the distribution will be skewed towards the younger age groups so the sample size will be less than this.There were eleven relevant papers, which have been split into three parts – risk models, incidence model and risk factor estimates. Table Bryn Austin (2012) used the Rosner-Colditz model and the Brandenburg et al., had a reIn Bryn Austin 2012) prospect prospecIn Dibble (2004) the sampIn McTiernan (2001) all partBoehmer et al., tested t•Twelve registries from the Surveillance, Epidemiology and End Results (SEER) database for years 1996–2004.•Census 2000 results for two questions  which were linked to find same sex female partner households.•Public Use Microdata Sample of the Census 2000 to estimate age and socioeconomic status of the sample.Because they were unable to link individuals they assessed density of female same sex partnered households at a county level, and then compared the breast cancer rates. The highest density was in San Francisco and the lowest in Iowa. The results showed that a 1% increase in same sex partnered households was associated with a 13% increase in breast cancer, after adjusting for age, ethnicity and socio-economic status. However, this is an ecological study so may have ecological bias; specifically that it is unknown whether the women in the same sex partnered households are the same as the women who are getting the breast cancer.All of the six studies described in Table The six studies were heterogeneous in a variety of different ways. The lesbian participants were recruited mostly via self-administered questionnaires in cross-sectional surveys but one was an audit of medical records. The comparators were mostly drawn from large US national surveys such as NHANES III and NHIS and the numbers in these national surveys actually used for comparison purposes in the studies was not stated in two of the studies. It is likely that there will have been some lesbians in the comparator group in Cochran 2001,,18,26 buTherefore, of the six studies, it is likely that Valanis 2000 may have more believable results than the others. However, all of the studies are from the USA and it is unclear how generalisable these results are to LB women in other countries because of differences in modifiable risk factors such as obesity rates and use of alcohol in different countries.This systematic review found no incidence estimates for breast cancer in individual LB women. There were twenty included studies using a variety of study designs to estimate prevalence, risk and local population incidence rates. This is a considerable body of research and suggests that there much interest in the question as to whether there is a higher incidence of breast cancer in lesbians and bisexual women than heterosexual women.Of the prevalence estimates, all of the studies found were relatively small and had a variety of poor quality issues associated with study design or reporting. The one unpublished estimate was high at 8%, relativFour risk modelling studies, one population incidence model and six risk factor estimates came from the USA. In two of the modelling studies, the populations may have been either high risk of breast cancer because of family history or at higher risk because of sampling biases. Three of the risk modelling studies suggested a higher rate of breast cancer in LB women compared to heterosexual women and one gave the opposite. The local population incidence rate model suggested a higher incidence of breast cancer in regions where more same sex partnered households live. Of the six risk factor estimate studies in LB women, five of the six studies concluded that there was a higher risk of breast cancer based on the factors they had assessed and one concluded that it was unlikely that there would be any difference in risk.A strength of this project is the comprehensiveness of the systematic review, which includes unpublished as well as published evidence in order to minimise publication bias. It has been conducted by very experienced systematic reviewers. The searches were updated to very close to the publication date to ensure no studies were missed.There are limitations from the conduct of the review and the weakness of the included studies. Coding of prevalence studies and the other types of studies included in this systematic review in medical databases is poor so there is a greater risk of missing relevant studies that could have been included, compared to systematic reviews of, for example, randomised controlled trials. Systematic reviews of prediction studies are rare and therRisk would need to be assessed prospectively in order to ensure that the risk factor occurred before the development of disease and did not start after diagnosis. This is more important for some potential risk factors such as alcohol use. There is an assumption that if a certain risk factor is present, then acting on that risk factor, such as drinking less alcohol, will substantially alter the risk of breast cancer. For some of these risk factors, it is unclear whether the factor itself is linked with incidence, or whether the factor is correlated with another causative factor. However, losing weight after the menopause is associated with less risk because of the oestrogenic effects of adipose tissue.Given the available evidence, it remains uncertain as to whether there is a higher incidence of breast cancer in LB women or not, but the balance of evidence is starting to suggest a higher incidence. The only realistic way to establish rates in LB women compared to heterosexual women would be to collect sexual orientation within routine statistics, including Cancer Registry data or from large cohort studies. Recently the UK National Cancer Data Set was reviewed but it iBMI: Body mass index; BRFSS: Behavioural risk factor surveillance system; CAB Abstracts: Commonwealth agricultural bureau abstracts database; CDSR: Cochrane database of systematic reviews; CENTRAL: Cochrane database of trials; CI: Confidence interval; DARE: Database of reviews of effects; EMBASE: Biomedical answers database; HRT: Hormone replacement therapy; HTA: Health technology assessment database; ISBN: International standard book number; LB: Lesbian and bisexual; LGB: Lesbian, gay and bisexual; MEDLINE: Medical database; NHANES: National health and nutrition examination survey; NHIS: National health interview survey; NHSEED: National health service economic evaluation database; PsychINFO: Psychological information database; SCI: Science citation index; SD: Standard deviation; SIGLE: System for intervention on grey literature in Europe; SSCI: Social science citation index; TSB: Trustee Savings Bank; UK: United Kingdom; USA: United States of America.The authors declare that they have no competing interests.CM devised, conducted and wrote the original systematic review as her Master’s Degree in Public Health Dissertation. This dissertation was awarded the Thomas McKeown prize for the best MPH project. DM was second and senior reviewer for the subsequent publication. Both authors read and approved the final manuscript.CM degrees - MBChB, MSc, PhD, MPH, FHEA.DM degrees - BSc, PhD.CM - Reader in Health Technology Assessment, Health Economics Research Group, Brunel University, Middlesex,DM – Senior Lecturer, Unit of Public Health, Epidemiology and Biostatistics, University of Birmingham.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/13/1127/prepub


It is unclear whether estrogen receptor (ER)-status of first primary breast cancer is associated with risk of metachronous (non-simultaneous) contralateral breast cancer (CBC), and to what extent endocrine therapy affects this association.We studied the effect of ER-status of the first cancer on the risk of CBC overall, and for different ER-subtypes of CBC, using a large, population-based cohort. The cohort consisted of all women diagnosed with breast cancer in the Stockholm region 1976–2005; 25715 patients, of whom 940 suffered CBC. The relative risk was analyzed mainly using standardized incidence ratios (SIR).Women with breast cancer had a doubled risk of CBC compared to the risk of breast cancer in the general female population (SIR: 2.22 [2.08–2.36]), for women with a previous ER-positive cancer: SIR = 2.30 (95% CI:2.11–2.50) and for women with a previous ER-negative cancer: SIR = 2.17 (95% CI:1.82–2.55). The relative risk of ER-positive and ER-negative CBC was very similar for women with ER-positive first cancer (SIR = 2.02 [95%CI: 1.80–2.27] and SIR = 1.89 [95%CI: 1.46–2.41] respectively) while for patients with ER-negative first cancer the relative risk was significantly different (SIR = 1.27 [95% CI:0.94–1.68] for ER-positive CBC and SIR = 4.96 [95%CI:3.67–6.56] for ER-negative CBC). Patients with ER-positive first cancer who received hormone therapy still had a significantly higher risk of CBC than the risk of breast cancer for the general female population (SIR = 1.74 [95% CI:1.47–2.03]).The risk of CBC for a breast cancer patient is increased to about two-fold, compared to the risk of breast cancer in the general female population. This excess risk decreases, but does not disappear, with adjuvant endocrine therapy. Patients with ER-positive first cancers have an increased risk for CBC of both ER subtypes, while patients with ER-negative first cancer have a specifically increased risk of ER-negative CBC. Of all women with breast cancer, each year 0.6–0.7% will develop contralateral breast cancer (CBC) Estrogen receptor (ER) status acts both as a prognosticator, independent of treatment, but also as a predictor of endocrine therapy response This study was approved by the ethical committee at the Karolinska Institutet, Stockholm, Sweden. As the study was purely register based, no contact was made with the study persons and the data were analyzed anonymously informed consent was not obtained. The exception from informed consent was confirmed by the ethical committee.The Stockholm Breast Cancer Register is a population-based register to which all breast cancer patients in the Stockholm-Gotland health-care region of Sweden are reported. The register is complete from 1976 and contains, among other clinical variables, date of birth, date of diagnosis, ER-status and information on subsequent cancers, distant metastasis and date of death. Adjuvant therapy is included in the register from 1990. In this study we included all women who were recorded in the Stockholm Breast Cancer Register during 1976–2005 as having invasive breast cancer occurring as the patient's first malignancy and not diagnosed in TNM-stage 4 (N = 25 715). We investigated the risk of CBC, defined as invasive contralateral breast cancer occurring as the patient's second malignancy and not diagnosed in TNM-stage 4. By these restrictions we tried to ensure that the breast cancers were primary malignancies, and not misclassified metastatic events.Further, women with CBC that occurred less than 3 months after the first breast cancer could not be part of the study population, since we regard their two cancers as simultaneous. The cutoff of 3 months for simultaneous CBC has been used previously by our group and others The measurement of ER-status during the study period is naturally of crucial importance for this study. Prior to 1988 isoelectric focusing For the analysis of endocrine therapy we restricted our cohort to patients with their first cancer diagnosed after 1990 (approximately 60% of the cohort), since treatment information was not included in the register until then. Endocrine treatment was recorded as yes/no, and for one third of the patients the type of endocrine therapy was also specified. (Tamoxifen for 75% of the patients and aromatase inhibitors for 22%.)Incidence of CBC was estimated as the number of cases divided by total person time (person-years) at risk, from first diagnosis of breast cancer until date of CBC or censoring . The cumulative incidence of CBC was estimated by the Nelson-Aalen estimator We used the standardized incidence ratio (SIR) to investigate the risk of CBC among breast cancer patients, compared to the risk of unilateral breast cancer in the general (breast-cancer free) female population. We calculated the ratio of observed to expected number of CBC-cases, in 5-year age intervals and 5-year calendar-period intervals. The background rate used for calculating the expected number of CBCs was the 5-year-age- and 5-year-period-specific rate of breast cancer in Stockholm during the study period (1976–2005), which we calculated from population counts of the general population of women and number of unilateral breast cancer patients in the Stockholm Breast Cancer Register. We calculated the rates separately for all breast cancer, for ER-positive cancer and for ER-negative cancer, thereby enabling us to compare the rate of e.g. ER-negative CBC to the rate of ER-negative unilateral breast cancer. We used 95% confidence intervals (CI) based on the Poisson distribution for the SIR to determine statistical significance As a sensitivity analysis we also calculated the SIRs restricted to patients with known ER-status , with the aim of investigating the potential effect of missingness of ER-status. Further, we investigated whether the risk of CBC, as compared to the risk of breast cancer in the general population, differed depending on how long time had passed since the first breast cancer. In effect, the observed over expected ratio of CBC during the first five years from diagnosis of primary cancer was calculated, by counting the accumulated person time  and observed number of CBCs, during these first five years. Then, the number of observed CBCs occurring more than 5 years after the first breast cancer and the person time accumulated from the time point five years after first primary diagnosis and until the end of follow up was calculated, giving rise to an observed over expected ratio in this group. These two ratios could then be compared and whether they differ will answer the question of whether the risk of CBC, as compared to the risk of breast cancer in the general population, differ by time since the first breast cancer.All data preparation and analyses were done using SAS Statistical Package 9.2.The final cohort consisted of 25 715 breast cancer patients, of which 18 853 (73%) had known ER-status; 14 720 had ER-positive breast cancer and 4 133 had ER-negative cancer . Among tThe cumulative incidence of CBC given the ER-status of the first cancer is shown by Nelson-Aalen plots in The risk for breast cancer patients to develop CBC was 2.22 times higher (95% CI: 2.08–2.36) than the risk of the general female population to develop unilateral breast cancer . FurtherAs a sensitivity analysis we restricted our cohort to only the patients for which ER-status  was known (N = 18 615), the purpose was to investigate the effect of missingness of ER-status on our estimates. We calculated the risk for breast cancer patients to develop CBC compared to the risk of the general female population to develop unilateral breast cancer; SIR = 2.02 . The relative risk among women with ER-positive first cancer was 2.02  and among women with ER-negative first cancer 2.03 . These findings are thus in concordance with the risk estimates for the full cohort . In addiWhen investigating the relative risk of ER-positive and ER-negative CBC separately  we foundWe evaluated the effect of endocrine therapy for the first cancer for women with ER-positive breast cancer by calculating the SIRs for the patients for whom we had information on endocrine therapy (patients diagnosed from 1990). The overall relative risk of CBC, as well as the risk of ER-positive CBC, was lower for the endocrine-therapy treated women , compared to non-endocrine treated , while no corresponding risk reduction was found for ER-negative CBC .We found the risk of CBC for breast cancer patients to be about twice as high compared to the risk of breast cancer in the general (breast-cancer free) female population, independently of ER-status of the first cancer. However, while ER-positive breast cancer seems to predict an increased risk for CBC in general, an ER-negative first cancer seems to specifically increase the risk for ER-negative CBC, and not for ER-positive CBC. The risk of CBC is highly increased for all women with first breast cancer diagnosed before the age of 50, and we now show that this increase is more pronounced for ER-negative CBC. Endocrine therapy for the first cancer decreases the risk of CBC, compared to when no endocrine therapy is given, this decrease was mediated through the risk of ER-positive CBC; no effect is seen for the risk of ER-negative CBC.Strengths of this study include that it was conducted in a country with a unified healthcare system and a population-based cancer register, which enabled close to complete case identification. We reduced the risk of misclassification of CBC through exclusion of women diagnosed with a previous cancer other than breast cancer, women diagnosed with an initial TNM stage IV breast cancer and women diagnosed with distant metastasis prior to the second cancer, this strict definition is a potential explanation for the somewhat lower incidence (454 cases per 100 000 person years) shown in this study, compared to other studies We found breast cancer patients to have approximately doubled risk of CBC, compared to the risk of breast cancer in the general female population, and found no significant difference in relative risk of CBC by ER-status of the first cancer . ER-statThe findings in The two previous studies that have investigated the SIR of CBC using unilateral breast cancer as the background population have conflicting results. Bouchardy et al. As previously shown We found the incidence of CBC overall to decrease over calendar period, as both our group and others have shown previously In conclusion; the increased risk of CBC for breast cancer patients compared to the risk of breast cancer for the general female population is not dependent on ER-status of the first cancer, which can thus not be used for risk prediction. However, it seems that ER-positive breast cancer predicts an increased risk for CBC in general while an ER-negative first cancer specifically increases the risk for ER-negative CBC. This, in combination with our finding that the increased risk compared to the general population is further enhanced for young women and in particular for ER-negative CBC, might imply effects of host factors that are yet unknown. Finally, the protective effect of adjuvant endocrine therapy for the first breast cancer is exclusively seen for the risk of ER-positive CBC, however also these treated women have a significantly higher risk of CBC than the risk of breast cancer for general female population.Table S1SIR sensitivity analysis latency time. Standardized incidence ratio (SIR) comparing the incidence of CBC to the incidence of unilateral breast cancer, overall and according to ER-status of the first and second breast cancer, including only CBCs with one year or more between the two cancers.(DOCX)Click here for additional data file.


Mammographic density (MD) is a strong, independent risk factor for breast cancer, but measuring MD is time consuming and reader dependent. Objective MD measurement in a high-throughput fashion would enable its wider use as a biomarker for breast cancer. We use a public domain image-processing software for the fully automated analysis of MD and penalized regression to construct a measure that mimics a well-established semiautomated measure (Cumulus). We also describe measures that incorporate additional features of mammographic images for improving the risk associations of MD and breast cancer risk.r) was used to compare the MD measurements by Cumulus and our automated measure, which mimics Cumulus. The likelihood ratio test was used to validate the performance of logistic regression models for breast cancer risk, which included our measure capturing additional information in mammographic images.We randomly partitioned our dataset into a training set for model building  and a test set for model assessment . The Pearson product-moment correlation coefficient  in an external test set. Adding a variable, which includes extra information to percentage density, significantly improved the fit of the logistic regression model of breast cancer risk (P = 0.0002).We observed a high correlation between the Cumulus measure and our measure mimicking Cumulus (Our results demonstrate the potential to facilitate the integration of mammographic density measurements into large-scale research studies and subsequently into clinical practice. Extensive mammographic density (MD) is a strong risk factor for breast cancer. MD refers to the different radiologic patterns of dense and nondense tissue in the breast. Radiologically dense tissue  appears light on a mammogram . NondensComputer-assisted methods are also used to assess MD. The interactive thresholding technique introduced by Byng et al. [MD can be evaluated and reported by radiologists on the basis of visual analysis of mammograms. Examples of quantitative and qualitative classification methods based on the visual characterization of mammographic parenchymal patterns include BIRADS, Wolfe , and Tabg et al. , CumulusMD is not yet an integral part of predicting the risk of breast cancer at screening and has limited influence in the clinical decision-making process for breast cancer-preventive interventions. A key challenge in the incorporation of MD data in research studies or clinical practice is that the assessment of MD by using the described methods, when performed on a large scale, is heavily restricted because of time and cost. The second challenge is that these methods are to some extent dependent on a subjective interpretation by the reader, some more so than others. A robust automatic method that measures MD, developed to work in a high-throughput setting, would thus be of great benefit to both single assessments of MD and longitudinal studies assessing risk of breast cancer with respect to MD change in large-scale screening programs.We present a fully automated method of assessing MD quantitatively from digitized analogous film mammograms by using ImageJ , a publiThis study is an extension of a breast cancer case-control study carried out among Swedish residents born in Sweden and aged 50 to 74 years, between October 1, 1993, and March 31, 1995 ,11. InfoPostmenopausal women with incident primary invasive breast cancer were identified via the six Swedish Regional Cancer Registries. The 3,979 women with a diagnosis of invasive breast cancer were identified, and 84%  of these women participated in the study. The primary reasons for nonparticipation were patient's refusal or doctor's refusal because of the patient's poor health.Controls were frequency matched by the expected age distribution  among cases and identified through the Swedish National Population Register holding data on national registration number, name, address, and place of birth of all Swedish residents. The response rate among controls was 82% .et al. [We sought to retrieve all mammograms for the eligible women in the initial cohort of the main study population by using the Swedish national registration numbers . We couFilm mammograms of the mediolateral oblique (MLO) view were digitized by using an Array 2905HD Laser Film Digitizer, which covers a range of 0 to 4.7 optical densities. The density resolution was set at 12-bit dynamic range. For participants in this study with multiple mammograms, the most recent mammogram was used; for cases, this was the mammogram before diagnosis. The mammogram contralateral to the tumor was chosen for cases. If this image was missing, the examination before the most recent examination was selected. For controls, we randomized side and used the same procedure as for cases. Women with bilateral breast cancer were excluded.Cases lacking information on tumor side or lacking films of the contralateral breast were excluded, as were subjects with previous reduction mammoplasty, and subjects who only had mammograms of very poor quality. There were 3,593 participants with eligible film mammograms .2-squared of 0.95. In addition, LE regularly calibrated herself against a training set of mammograms measured by Professor Boyd, an expert on, and one of the developers of, Cumulus [Mammographic density was measured by using the Cumulus software, a computer-assisted technique developed at the University of Toronto, Ontario, Canada . For eac Cumulus .To process automatically the digitized film mammograms and to measure PD, we used ImageJ , a publiPatient-identification tags were first automatically removed (cropped) by ImageJ from the images. Further preprocessing of the images was required to extract the breast region from the rest of the image. Background of the image was subtracted by superimposing a "mask" derived by applying grayscale erosion and gaussian Blur filters, followed by implementing the Kittler and Illingworth Minimum Error thresholding , implemeHaving identified the breast region of the image, we further applied automated thresholding methods to separate the areas of "dense" breast tissue ("regions of interest") from the remaining area of the breast. In total, 15 thresholding methods, which vary according to the type of pixel-intensity information they exploit  were applied to the preprocessed image, and the same preprocessed image after subtracting background by using a rolling-ball algorithm and further filtering/de-noising of the image. Areas corresponding to "dense" tissues were subdivided into smaller objects by using the watershed algorithm. Figure The Analyze command in ImageJ was then used to count and measure objects in the thresholded images . A variety of measurements were obtained for the breast as a whole, as well as for the "objects" of dense tissue, under each thresholding method . Analysis was limited to 772 variables with less than 200 NaN ("not a number") values. All remaining NaN values in the 772 variables were converted to zero in subsequent analyses.t test was used to compare the means of continuous variables. Because of the nonnormal distributions of MD measures, we used the nonparametric Wilcoxon test to compare the distribution of percentage density and absolute dense area. Distributions of categoric variables were compared by using the χ2 test. All tests were two-sided.The two-sample Student To build and assess a PD estimation model, we randomly partitioned the dataset, consisting of information on 2,993 women, into two parts: a training set for model building , and a test set for model assessment (765 cases and 747 controls).Principal component analysis was used to carry out feature selection. Instead of directly using the 772 nonindependent "raw" (ImageJ) variables, for building a model of PD, we substituted, in their place, 123 principal components (PCs). The weights (of the raw variables) used by each PC were calculated from a principal component analysis (PCA) of the training set. These 123 PCs captured 90% of the total variance of the original 772 variables (in the training set). The Scree plot, showing the fraction of total variance, as explained or represented by each PC, is displayed in Additional file Our first aim was to select a model for Cumulus PD, as a function of the PCs. As other researchers have done , we workThe same procedure may be applied to get a trained estimate of other MD measures by ImageJ, such as total breast area, absolute dense area, or absolute nondense area.r) was estimated. The Bland-Altman plot was used to assess the agreement between the two methods of measurement.To test for an association between Cumulus PD and ImageJ PD, the Pearson product-moment correlation coefficient  was evaluated by calculating the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. The pROC package in R was used to calculate AUCs along with their standard errors and 95% confidence intervals. The DeLong test  was usedIn addition to using ImageJ to mimic the Cumulus measure of PD, we performed a systematic evaluation of the information in the ImageJ variables in terms of their ability to predict breast cancer risk. We fitted logistic regression models with the lasso penalty in the training set (consisting of 733 cases and 748 controls) by using a similar procedure to that described earlier for the linear model for PD. The same 123 PCs were included in our analysis, and repeated 10-fold cross validation was again used to obtain the optimal value of the tuning parameter. We "trained" three models:1. 123 PCs as covariates; all regression coefficients included in the penalty term.2. PD + 123 PCs as covariates; coefficients for the 123 PCs included in the penalty term, but not the coefficient for PD.3. PD + 123 PCs as covariates; all coefficients (123 PCs + PD) included in the penalty.Based on these three models, we formed three "scores" for each image, derived by summing the products of the nonzero regression coefficients of the PCs with the corresponding PC values of that image. We refer to these scores as score 1, score 2, and score 3 (according to these three models). The test set was then used for "external" assessment of the predictive ability of the "trained" ImageJ scores; we fitted logistic regression models with breast cancer status as outcome variable, with different combinations of the scores and Cumulus or ImageJ PD as covariates.R (version 2.13.0)  was usedP < 0.001), absolute dense area (P < 0.001), age at diagnosis or reference date (P < 0.001), age at mammogram (P < 0.001), age at menopause (P = 0.001), alcohol consumption (P = 0.008), parity/age at first birth (P < 0.001), hormone-replacement therapy (P < 0.001), family history of breast cancer (P < 0.001), and benign breast disease (P < 0.001). A near-significant association was observed for age at menarche (P = 0.084). Body mass index (BMI) (P = 0.801) was not significantly associated with breast cancer case status in this subset of the main population case-control study.A summary of descriptive statistics of breast cancer risk factors for the subjects included in this study, presented by breast cancer case status, is shown in Table Descriptive statistics for the study population according to training and test sets are given in Additional file r = 0.884; 95% CI, 0.872 to 0.894; Figure r = 0.902; 95% CI, 0.892 to 0.911). From fitting a linear regression model (test set), we found that a 1% increase in the value of ImageJ PD was associated with a 1.029% increase in the value of Cumulus PD. The range of square-root transformed PD values for ImageJ (0 to 9.10) was similar to that of Cumulus (0 to 8.96). Bland-Altman analysis for Cumulus PD and ImageJ PD, based on the 1,512 samples in the test set, showed good agreement  were similar for both Cumulus PD and ImageJ PD . Not including PD as a penalized covariate during the process of forming score 2, meant that score 2 was "forced" to be independent of PD, whereas score 3 was constructed based on a model that penalized PD along with the PCs. Additional file P = 0.0002 for both Cumulus and ImageJ) significant, indicating that information is contained in mammographic images, not captured by PD, that is important for discriminating between cases and controls. The extra information captured by ImageJ is independent of PD in predicting risk. We also note that the fully automated ImageJ PD + score 3 model has a lower Akaike information criterion (AIC) [Having assessed the ability of our ImageJ PD measure to mimic Cumulus PD, we next turned to whether ImageJ might hold extra information (not captured by Cumulus) for discriminating cases and controls. We selected three models based on the training set. Three scores were constructed as linear combinations of 28, 3, and 37 PCs from fitting penalized regression models , respectively. As expected, score 3 included considerably more PCs than score 2 and was more strongly associated with PD (on (AIC)  than theWe developed an automated thresholding method for obtaining quantitative measurements of MD that compares favorably with the established semiautomatic computer-assisted Cumulus method in predicting risk of breast cancer. The algorithm is based on an established Java-based image-analyses program, ImageJ. Furthermore, we showed evidence that additional features in a mammogram captured by ImageJ, summed into a collective score, represent a significant and independent marker of breast cancer risk.et al. [et al. [r = 0.875; 0.863 to 0.887), which was similar to that of Kallenberg et al. [r = 0.895), and substantially higher than that of Heine et al. [r = 0.70). In our study, the odds ratios associated with breast cancer risk were also similar between PD measured by Cumulus and ImageJ, suggesting that PD measured by ImageJ is as good as PD measured by Cumulus in indicating the likely development of breast cancers. Kallenberg et al. [Other researchers have developed automated approaches to measure MD. For example, Heine et al.  describe [et al.  describeg et al.   compared with what has been reported before, for example, for the parenchymal pattern-based BIRADS density measure (AUC = 0.658) . HoweverP = 0.0002). ImageJ might be capturing information not related to PD, for example, features related to mammographic texture, in the mammograms. PCs with nonzero coefficients in each score  that is freely available. ImageJ can automatically open, process, and analyze a digitized mammogram in less than 12 seconds, offering a huge advantage over time-consuming measurements using Cumulus, which typically takes a reader between 2 and 5 minutes to achieve the same result. The software runs on Java and is thus not based on any specific platform and is inexpensive in terms of expertise needed to run the macros for processing mammograms. Its open-source design makes ImageJ more easily evolvable and correctable than many proprietary packages, allowing the fine-tuning of parameters for nonstandard mammograms or potentially, with further development, non-film mammograms. As the PD estimates are derived from a machine-learning-based method, the data can be easily retrained to output other measures, such as absolute dense and nondense areas. An additional strength includes our large population-based breast cancer case-control study, which allows us to apply and validate ImageJ PD alongside Cumulus PD in the estimation of breast cancer risk.A robust, automated thresholding method would shorten the time and cost needed to acquire MD data via parallel processing of the images. Large archives of film mammograms could then be rapidly revisited and read to answer epidemiologic research questions. Images from current and future studies may also be read at the same time as they are acquired, and the resultant readings, which could encompass both PD and additional mammographic features, could perhaps be used to estimate breast cancer risk better for each individual when incorporated into current breast cancer prediction tools, such as the Gail or the Claus models.We acknowledge the weakness of using a largely postmenopausal study population, which, on average, has lower mammographic density than do premenopausal women. Caution is needed when evaluating mammograms with very high density values with the new method. In addition, the generalizability of the new automatic mammographic density thresholding method is currently limited to the MLO images (taken from an oblique or angled view) analyzed in this study. In many countries, the MLO view is preferred over lateral, perpendicular projections during routine screening mammography, as more of the breast tissue is visible in the upper outer quadrant of the breast and the axilla. Further work is required to extend the application of the method to other projections . The high-throughput capacity of an automated method makes it feasible to base future assessments of MD on more than one view.The generalizability of our new MD measurement method is at present confined to digitized screen film mammograms. With the paradigm transition from analogue to digital mammography, it is of high clinical relevance to extend the use of the automated PD thresholding method to digital mammograms. In contrast with current applications used to determine MD from digital mammograms, which have to be present as the image is being acquired by the machine, ImageJ can be applied at any time after image acquisition, making it feasible to read digital images retrospectively. However, many concerns must be addressed before MD can be confidently measured from processed digital mammograms in general. A more detailed discussion of this topic is beyond the scope of this article. Nevertheless, the availability of phenomenal archives of unread film mammograms for historical cohorts with good follow-up data justifies the development of an automatic tool.Despite the remarkably strong influence of MD on breast cancer risk, it has had limited influence in clinical decision making and has not yet been included in any established risk-prediction tool. It is, however, likely that the purpose of future mammography screening programs will not be limited to the detection of early breast cancers, but also to stratify women according to their individual risk of breast cancer. Such stratification will make it possible to tailor screening intervals based on individual risk, add complementary diagnostic techniques , and select high-risk women for appropriate preventive interventions . A robust, fully automated thresholding technique that can assess density in an objective and high-throughput manner is the first step to achieving these goals, with the ultimate aim of reducing the incidence of and mortality from breast cancer.We describe a novel method for using a public domain software for the automated analysis of mammographic density, with the intent of duplicating the findings of an established method (Cumulus), and improving the risk associations of mammographic density and breast cancer risk. Further work is required to validate and extend the application to mammographic images of other views and those produced by a digital mammography system.P: P value; PC: principal component; PD: percentage density; r: Pearson product-moment correlation coefficient.AIC: Akaike information criterion; BMI: body mass index; CI: confidence interval; MD: mammographic density; MLO: mediolateral oblique; OR: odds ratio; The authors declare that they have no competing interests.PH, LS, KC, and KH conceived and designed the study. BH, AS, and LE collected and assembled data, and JL, KH, and LS were responsible for data analysis and interpretation. All authors contributed to manuscript writing and read and approved the final manuscript.Figure S1. An example of a digitized mammogram before and after thresholding and application of the watershed algorithm by using different global thresholding algorithms.Click here for fileFigure S2. Scree plot showing the proportion of variance explained for from principal component analysis of 772 ImageJ variables. PC, Principal component.Click here for fileTable S1. Weights of original variables. Each principal component (PC) is a linear combination of the original variables. Loading values represent relative contributions of the original variables to each PC. "Total" measurements are made on particles of at least 5 pixels. Particles1, -2, and -3 denote measurements on particle size ranges of 5 to 100, 101 to 1,000, and at least 1,001 pixels, respectively.Click here for fileTable S2. Descriptive characteristics of study population by training or test subgroups.Click here for fileNonzero coefficients of penalized regression models.Click here for file