At present, women with ductal carcinoma in situ are counseled that they have a pre-malignant condition which carries the possibility of progression to a fully malignant breast cancer. However, in most cases, the treatment of DCIS resembles that of a small invasive breast cancer and this is a source of confusion to many. In order to properly evaluate the benefit of radiotherapy, mastectomy and contralateral mastectomy, it is necessary to consider the risks of ipsilateral invasive cancer and of contralateral breast cancer in women with DCIS and with small invasive breast cancer. Several registry-based studies indicate that the risks of ipsilateral and contralateral cancer are similar in the two conditions and therefore a similar approach to treatment is rational. In a recent large survey of 2432 women who were diagnosed with DCIS in the United States, many of the respondents reported confusion—specifically, about their chances of developing an invasive breast cancer, or metastatic cancer, and the options that were available to them to avoid these unwanted outcomes . The womWe think that much of the confusion is unnecessary and is generated by the current paradigm that separates DCIS and invasive cancer into two distinct conditions. No doubt this position is taken by doctors to reassure patients, relay success (“we got it early”) and reduce anxiety. The position is based on the low mortality rate of DCIS and the belief that stromal invasion is a prerequisite to metastases. After reviewing the clinical literature, we conclude that DCIS is better described as a small breast cancer . Small, We base this interpretation on the observation that the mortality of DCIS is 3% over 20 years and that prevention of local invasive recurrence post-DCIS does not reduce breast cancer mortality . If invaConsider the goals of treatment of DCIS. The primary goal is to prevent invasive cancer. Secondary goals are to prevent contralateral cancer, distant recurrence and death from breast cancer. We also want to minimize morbidity and maintain quality of life. Are the goals any different than for women with a small invasive breast cancer? For example, for those women who have a cancer that is less than one centimeter and is node-negative?The risk of an invasive in-breast recurrence following DCIS is the same as the risk of an invasive in-breast recurrence following invasive breast cancer.Consider the following four points:In the Banting database, the 15-year risk of invasive local recurrence following DCIS was 15.6%, following stage I breast cancer this was 15.3%, and following stage II breast cancer it was 15.9% ;2.The benefit of radiotherapy on reducing ipsilateral invasive breast cancer is the same for patients with DCIS and stage I/II breast cancer.In the Banting database, the 15-year risk of ipsilateral invasive recurrence was 14% for DCIS patients who received radiotherapy and 29% for DCIS patients who did not receive radiotherapy—a difference of 15% . In the 3.The risk of contralateral invasive breast cancer is the same following DCIS and following invasive breast cancer.In our SEER-based analysis of 812,851 women with breast cancer, the 25-year actuarial risk of contralateral invasive breast cancer was 10.1% for patients with DCIS and 9.9% for patients with invasive breast cancer . Based o4.Preventing invasive in-breast recurrence after DCIS does not prevent death from breast cancer.In our SEER based study of DCIS patients, the risk of invasive in-breast recurrence cancer was much higher for women who were treated with lumpectomy than those who were treated with mastectomy (1.3% versus 3.3% at ten years), but the risk of dying of breast cancer was similar . Similar5.Chemotherapy is given based on the risk of distant recurrence.We give women chemotherapy to prevent distant recurrence, not local recurrence. The choice of giving chemotherapy to a woman is dependent on her calculated risk of distant recurrence or death. All agree that the risk of death following DCIS is too low (3%) to warrant chemotherapy—but this does not mean it is not cancer. The risk of dying of cancer for post-menopausal women with small low-grade node-negative breast cancer may also be too low to warrant chemotherapy—but this does not mean that these are not cancers. If we had a chemotherapy regime that was completely non-toxic and without side effects, we would give it to DCIS patients. The decision to give chemotherapy is based on factors other than the presence of cancer cells in the breast stroma. This is one consideration; others include the patient’s age, nodal status, ER status, MammaPrint scores, co-morbidity, etc. It is interesting that among young Black women, the risk of dying of DCIS approaches 10%, and it is possible that some of these women might benefit from chemotherapy . There aDCIS, like invasive breast cancer, is heterogeneous; the risks of the various outcomes vary according to host factors, clinical stage and biological subtypes. In order to decide upon treatment for any given patient, the risks of the local and distant recurrence must be considered against the side-effect profile and the morbidity of the treatment under consideration. In the context of DCIS, the protective effect of adjuvant radiotherapy on ipsilateral invasive recurrence is less evident in very young women (diagnosed before age 40) compared to older women , whereasThe risk of invasive ipsilateral invasive in-breast recurrence is the same for both groups of patients , but we The use of radiotherapy has the same impact on reducing the risk of ipsilateral invasive for patients with DCIS and stage I/II breast cancer ,18 but w❖Following pure DCIS 1.4% ;❖Following DCIS with micro-invasion 2.8% ;❖Following a local invasive recurrence after DCIS 10% ;❖Following a local invasive recurrence after a stage I invasive cancer 25% ;❖Following a local invasive recurrence after a stage II invasive cancer 47% .There is an important point where the statistics on DCIS and invasive cancer diverge. Consider the ten-year risk of distant recurrence or death within 10 years of diagnosis, by patient group:The key point here is that the mortality rate of a woman who experiences a local invasive recurrence is highly dependent on her initial diagnosis and treatment. Death is much less likely if a DCIS patient experiences a local recurrence than if a stage II breast cancer patient experiences a local recurrence. However, lumpectomy is considered as standard of care for both. Now comes the paradox. We consider a local recurrence after an invasive cancer to be a marker of tumor aggressivity, but not a source of metastases (this was the conclusion of the Fisher NSABP studies and provides the basis for breast-conserving surgery). The invasive recurrence was not the cause of death. Conversely, conventional wisdom says that an invasive recurrence following DCIS is a source of metastases and is the cause of death for the unfortunate few patients who die. So, if we accept conventional wisdom, then there is greater justification to perform a mastectomy for a DCIS patient than for a patient with invasive cancer. No wonder the patients are confused. Aren’t you? Consider if you had two skin lesions and one was more likely to turn malignant, which one would you remove?In the paper by Rosenberg et al., the patients expressed a great deal of confusion about the risks for local and distant recurrence . Much ofWe hope that this analysis reduces confusion; however, it is unlikely to decrease anxiety. This is a separate problem. In a recent study from Princess Margaret Hospital, we showed that the level of anxiety and distress experienced by a woman with a new diagnosis of breast cancer was similar across all stages—despite large differences in prognosis .Based on the risks and patterns of the relevant outcomes described here, we propose that we should counsel women with DCIS as if they have a small breast cancer. We already treat them as such. Ultimately, to optimize the treatment of DCIS and early invasive breast cancer we must differentiate between the cancer processes in the breast and in the systemic niche. Preventing local recurrences will not have the hoped-for downstream effect of preventing deaths; therefore, the de-escalation of local treatment is rational. To prevent death, we must identify and target the subgroup of patients at the highest risk with effective systemic treatments.The other option is to change the definition of cancer. The NCI defines cancer as “a disease in which abnormal cells divide without control and can invade nearby tissues. Cancer cells can also spread to other parts of the body through the blood and lymph systems.” If we look closely at DCIS (and early-stage lesions), we realize that not all have the capacity to invade and metastasize —some do


Women in the UK have a 15% lifetime risk of developing breast cancer. Like other high‐income countries, women in the UK are having children later in life which increases their risk. The risk of breast cancer is reduced by 4.3% for every 12 months of breastfeeding, this is in addition to the 7.0% decrease in risk observed for each birth. Breastfeeding reduces the risk of Triple‐Negative Breast Cancer (20%) and in carriers of BRCA1 mutations (22–55%). The mechanisms of reduced risk as a result of pregnancy are related to changes in RNA processing and cellular differentiation. The UK has a low rate of breastfeeding (81%) and this is contrasted to countries with higher  and lower rates (Ireland). The low UK rate is in part due to a lack of experience in the population, todays grandmothers have less experience with breastfeeding (62%) than their daughters. An estimated 4.7% of breast cancer cases in the UK are caused by not breastfeeding. The UK only has 43% of maternity services with full Baby‐Friendly accreditation which promotes compliance with the WHO ‘Ten Steps to Successful Breast Feeding’. Legislation in the UK and Europe is far short of the WHO Guidance on restricting the advertising of formula milk. Expansion of the Baby‐Friendly Hospital Initiative, stricter laws on the advertising of formula milk and legislation to support nursing mothers in the workplace have the potential to increase breastfeeding in the UK. Women with a family history of breast cancer should particularly be supported to breastfeed as a way of reducing their risk. Babies who are breastfed have a reduced risk of death from infectious diseases,2The average age for a woman's first birth is similar across the UK, 28.8 ,3Defining the rate of breastfeeding is complex. It is straightforward to understand exclusive breastfeeding or no breastfeeding but there are many versions of combination feeding in between these two extremes. The category of ‘ever breastfed’ is used to allow comparisons globally.In the UK women have low rates of breastfeeding, 81% of babies are ever‐breastfed.In England, 72.7% of babies born at term had breastmilk as their first feed.4Women in the UK born after 1960 have a 15% lifetime risk of developing breast cancer.However, the protective effects of pregnancy is dependent on the age a woman's first birth occurred. Young age of first full‐term pregnancy (<25) reduces the risk of breast cancer in postmenopausal women by 35% compared to nulliparous women.While this increased breast‐cancer risk for older mothers is concerning, what we are actually seeing is a reversal of the protective effects of pregnancy for young women. Women who have one child between the ages of 30 and 34 have the same risk nulliparous women.Pregnancy is protective against breast cancer in the long‐term, but in the short‐term both the incidence of breast cancer and the aggressiveness of cancers that do occur increases.Given the reduction in breast cancer risk when a woman's first pregnancy occurs at less than 30 years it would be prudent to include information on breast cancer risk with fertility education in schools.5A large meta‐analysis of 47 studies from 30 countries examined the impact of breastfeeding on breast‐cancer risk.Breastfeeding has been shown to not alter the protective effect of multiple pregnancies in women who had their first full‐term pregnancy before 25 years.6The protective effects of an early full‐term pregnancy and breastfeeding have been consistently seen in multiple countries and ethnic groups, suggesting that the protection results from biological changes in the breast rather than environmental or socioeconomic factors.The human breast goes through remarkable changes during a woman's lifetime. During puberty increased levels of oestrogen and progesterone causes the breasts to enlarge. This is due to the development of the mammary glands and increased fatty tissue.6.1Studies have sought to understand the difference in gene‐expression in breast tissue from women who have had children compared to those that have not.6.2Terminal ductal lobuloalveolar units are regarded as the site of origin for the majority of human breast cancers and they contain mammary stem and progenitor cells.7Breast cancer is categorised into three major subtypes based on the presence or absence of oestrogen receptor or progesterone receptor known as hormone receptors (HR) and human epidermal growth factor 2 (HER2).7.1Hormone‐receptor positive and HER2 negative is the most common type of breast cancer representing 70% of cases.7.2HER2 positive breast cancers account for 15–20% of cases, about half of these cases are also hormone‐receptor positive. When detected early and treated with a combination of chemotherapy and HER2 inhibitors as well as endocrine therapy for those who are hormone‐receptor positive; 94% of women survive 5 or more years.7.3Breast cancers that do not have hormone receptors or HER2. The cause of these cancers can be unknown but tumours from BRCA mutation carriers are typically within this subtype.88.1Young age of first full‐term pregnancy (<25) was found to reduce the risk of HR+ breast cancer by 18–40% compared to women without children.8.2The literature on the risk of HER2+ breast cancer and pregnancy does not have a clear consensus. Some studies show an increased risk with one or more birth,8.3One or more full‐term pregnancy was found to reduce the risk of triple‐negative breast cancer by 30% in women aged 20–44 compared to women without children.8.4Pregnancy is associated with a reduced risk of breast cancer in BRCA1/2 carriers, the greater number of pregnancies the larger the reduction in risk was observed.99.1A 2015 meta‐analysis found no reduction in the risk for hormone‐receptor positive breast cancer associated with breastfeeding.9.2The studies that found an increased risk of HER2+ breast cancer with pregnancy, had a lower risk in women who breastfed.9.3A 2015 meta‐analysis found a 20% reduction in the risk for triple‐negative breast cancer associated with breastfeeding.9.4Women with BRCA1 mutations who breastfed for more than one year were found to have a 22–50% reduced risk of breast cancer than those who never breastfed.Women with a family history of breast cancer should particularly be supported to breastfeed as a way of reducing their cancer risk. Many women are unaware of having a BRCA mutation and their increased cancer risk.10Breastfeeding is a highly‐emotive subject because so many women have not breastfed, or have experienced the pain of trying very hard to breastfeed and not succeeding.10.1Public Health England recently studied mothers perceived barriers to breastfeeding.10.2Problems can be caused by common conditions such as tongue‐tie in the infant10.3First‐time mothers, have little experience of seeing breastfeeding in their community and need additional support in positioning and attachment of the baby.The “Ten Steps to Healthy Breastfeeding” are the basis of the WHO/UNICEF Baby‐Friendly Hospital InitiativeBOX 1Every facility providing maternity services and care for new‐born infants should:1. Have a written breastfeeding policy that is routinely communicated to all health care staff.2. Train all health care staff in skills necessary to implement this policy.3. Inform all pregnant women about the benefits and management of breastfeeding.4. Help mothers initiate breastfeeding within a half‐hour of birth.5. Show mothers how to breastfeed, and how to maintain lactation even if they should be separated from their infants.6. Give new‐born infants no food or drink other than breastmilk, unless medically indicated.7. Practice rooming‐in ‐ allow mothers and infants to remain together −24 hours a day.8. Encourage breastfeeding on demand.9. Give no artificial teats or pacifiers  to breastfeeding infants.10. Foster the establishment of breastfeeding support groups and refer mothers to them on discharge from the hospital or clinic.10.4Women do not breastfeed in isolation and rely on the advice and support of their family. A woman's partner is the most helpful or influential on feeding practices.Sweden has historically high rates of breastfeeding initiation, which was 97% in 1990.10.5Despite breastfeeding being protected by UK law10.6The longer the duration of a mother's maternity leave the longer the duration of breastfeeding.Breastfeeding in the workplace is not adequately protected in UK law. The law requires an employer to provide a space to rest including the ability to lie down.10.7Formula milk is an essential product for children with complex medical needs and for those women who cannot breastfeed.11Breastfeeding reduces the risk of breast cancer by 4.3% for every 12 months of breastfeeding, which is in addition to the 7.0% decrease in risk observed for each birth. Breastfeeding has been shown to primarily reduce the risk of Triple‐Negative Breast Cancer (20%) as well as in carriers of BRCA1 mutations (22–50%). Women with a family history of breast cancer should particularly be supported to breastfeed as a way of reducing their cancer risk.The molecular mechanisms of reduced breast‐cancer risk as a result of pregnancy appear to be related to RNA processing and cellular differentiation and may be associated with an alteration in maintenance or differentiation of breast cancer stem cells.The UK has a low rate of breastfeeding in part due to a lack of experience in the population. An estimated 4.7% of breast cancer cases in the UK are caused by not breastfeeding. Expansion of the Baby‐Friendly Hospital Initiative, stricter laws on the advertising of formula milk and legislation to support nursing mothers in the workplace have the potential to increase breastfeeding rates in the UK.Britta Stordal: Funding acquisition (lead); investigation (lead); methodology (lead); writing – original draft (lead); writing – review and editing (lead).The author has no financial or non‐financial interests related to the work submitted for publication. The author states that there is no conflict of interest.This study was approved by the Natural Science Research Ethics Committee at Middlesex University. This study did not involve human participants or patient material, so no written informed consent was required.Appendix S1Click here for additional data file.


Guidelines recommend shared decision making (SDM) for mammography screening for women ≥ 75 and not screening women with < 10-year life expectancy. High-quality SDM requires consideration of women’s breast cancer (BC) risk, life expectancy, and values but is hard to implement because no models simultaneously estimate older women’s individualized BC risk and life expectancy.n = 55,533) a model to predict 10-year non-breast cancer (BC) death. We considered 60 mortality risk factors and used best-subsets regression, the Akaike information criterion, and c-index, to identify the best-fitting model. We examined model performance in the remaining 1/3 of the NHS cohort  and among 17,380 Black Women’s Health Study (BWHS) participants, ≥ 55 years, who completed the 2009 questionnaire. We then included the identified mortality predictors in a previously developed competing risk BC prediction model and examined model performance for predicting BC risk.Using competing risk regression and data from 83,330 women > 55 years who completed the 2004 Nurses’ Health Study (NHS) questionnaire, we developed ; over 10 years, 3.1% developed BC, 0.3% died of BC, and 20.1% died of other causes; NHS validation cohort participants were similar. BWHS participants were younger (mean age 63.7 years [± 6.7]); over 10-years 3.1% developed BC, 0.4% died of BC, and 11.1% died of other causes. The final non-BC death prediction model included 21 variables . The final BC prediction model included age, BMI, alcohol and hormone use, family history, age at menopause, age at first birth/parity, and breast biopsy history. When risk factor regression coefficients were applied in the validation cohorts, the c-index for predicting 10-year non-BC death was 0.790 (0.784–0.796) in NHS and 0.768 (0.757–0.780) in BWHS; for predicting 5-year BC risk, the c-index was 0.612 (0.538–0.641) in NHS and 0.573 (0.536–0.611) in BWHS.We developed and validated a novel competing-risk model that predicts 10-year non-BC death and 5-year BC risk. Model risk estimates may help inform SDM around mammography screening.The online version contains supplementary material available at 10.1186/s13058-023-01605-8. Breast cancer is the most common non-skin cancer diagnosed in women and incidence increases with age , 2. Mammand life expectancy to support shared decision making around mammography screening.In addition, none of the mammography screening trials included women ≥ 75 years old. Most guidelines recommend engaging women ≥ 75 in shared decision making , 11, 12.The Breast Cancer Risk Assessment Tool  is the most commonly used breast cancer prediction model in primary care , 19. It We previously used NHS data and Fine-Gray competing risk regression to develop a breast cancer prediction model for older women . That mon = 83,330 NHS, n = 17,380 BWHS; see Additional file We used NHS data to extend our previously developed competing risk breast cancer prediction model to also predict non-BC death . NHS is The oldest participants at the end of follow-up were aged 95. In both cohorts, cause of death was determined from state-issued death certificates, the National Death Index, family and friends, and the post-office. In NHS, death information was further supplemented with medical record review; > 98% of deaths are identified , 27. ForTo expand our model to predict non-BC death, we considered 60 potential mortality risk factors, including health behaviors (4), comorbidity (32), physical function 16), psychosocial factors (5), age, age at menopause, and parental longevity; information was obtained from the 2004 NHS questionnaire and/or prior years  for model development and 1/3  for internal validation. Survival time was measured from study entry until non-BC death; participants were censored at breast cancer death or 10 years from their 2004 questionnaire return date, whichever came first. We first examined the unadjusted effect of each mortality risk factor using proportional hazards regression (PHR). Variables significantly associated (p < 0.05) with non-BC death in univariate analyses and not collinear at > 0.4 (Spearman correlation) were considered in our multivariable model. When two variables were collinear, we removed the variable more difficult to self-report. We used best-subsets regression  [Analyses were completed using SAS 9.4 software. We randomly divided the NHS population into 2/3 (atistic) , the Akaatistic) –34. InveIn sensitivity analyses, we examined for “ghost-time” bias  by censoring participants at age 90 . We alsoWe examined the final model’s performance in predicting 10-year non-BC death and 5-year breast cancer risk because these thresholds have clinical significance. Guidelines for use of breast cancer prevention medications consider postmenopausal women with ≥ 3% 5-year risk to be at high risk , 37. Alsz-tests. While most risk factors were defined similarly by NHS and BWHS, BWHS did not assess participant mobility or ability to bath/dress oneself. We censored BWHS participants without complete 10-year follow-up on December 31, 2020, since death data after that date may have been incomplete.We used Royston and Altman’s methods for validating models using survival analyses and examined our model’s calibration (whether model predicted probabilities are accurate) and discrimination  in predicting non-BC death , 41. FirCalibration of the model in predicting non-BC death was assessed by estimating the ratio of the expected survival (1-CIF for non-BC death from our competing risk regression model) to the observed survival (1-the observed CIF computed using the nonparametric estimation of CIF) at 5 and 10 years within risk quintiles . To testTo demonstrate how our model may be useful, we calculated breast cancer and non-BC death risk estimates for four example women 75 years old for whom guidelines recommend shared decision making and to not screen women with < 10 year life expectancy , 11. We n = 55,553) were 96.2% non-Hispanic white, and their mean age was 70.1 (SD 7.0) years. Over 10 years, 3.1% developed breast cancer, 0.3% died of breast cancer, and 20.1% died of other causes. NHS validation cohort  participants were similar to development cohort participants  differed by race, were younger, more likely to have had a mammogram, a breast biopsy, have higher BMI, younger age at menopause, comorbidity, to be nulliparous and to walk briskly than NHS development cohort participants; BWHS participants were less likely to use alcohol, cigarettes, or MHT. The number of breast cancer diagnoses was similar between cohorts, but BWHS participants were slightly more likely to die of breast cancer; after standardizing by age the cohorts had similar rates of non-BC death. Additional file NHS development cohort participants  rather than self-reported diagnoses changed the model’s c-index. Adjusting model c-indices for age led to a small decrease in model performance  in the NHS validation cohort and 0.556 0.517–0.595) in the BWHS. We then removed factors that predicted mortality alone ; the model’s c-statistic improved to 0.611 0.582–0.640) in the NHS validation cohort and to 0.566 (0.528–0.604) in BWHS. We then examined model performance considering BMI and alcohol use as continuous rather than categorical variables; model performance improved when using continuous BMI. Finally, we added factors considered in our previous NHS model , but model performance did not improve. The c-index of our final breast cancer prediction model was 0.612 (0.583–0.641) in the NHS validation cohort and 0.573 (0.536–0.611) in BWHS, as shown in Table 0 in the 7–0.595 iTable We developed a novel model to simultaneously predict breast cancer incidence and non-BC death to inform older women’s breast cancer screening decisions. Our model performed well in predicting non-BC death across cohorts. The model slightly over-predicted death in the BWHS after 10 years follow-up in the highest risk group, possibly because data were not available in BWHS on participant mobility and function and these values were highly significant for non-BC death in the NHS cohorts. Our rigorously developed non-BC death prediction model outperformed a model that only included risk factors for death that were selected based on expert opinion. In addition, our model for predicting 5-year breast cancer risk demonstrated excellent calibration but only modest discrimination in predicting breast cancer, similar to the other breast cancer prediction models. Specifically, the Gail and Tyrer-Cuzick breast cancer prediction models have been shown to have c-statistics of < 0.60 in NHS participants ≥ 70 years , 46 and While mortality indices exist for estimating adults’ 10-year overall mortality risk , 48, nonWe used competing risk regression to obtain the estimated HRs and CIFs because HRs from competing risk models are directly associated with CIFs and take into account competing risks, while HRs from cause-specific PHR models examine a risk factor’s effect in a hypothetical world with no competing risks. (Competing risks are censored.) Putter et al. have elegantly shown that the HRs from competing risk models are directly associated to those from cause-specific proportional hazard models via the negative logarithm of the reduction factor from the cause-specific model . In our In addition, while the hazard ratios associated with many of the risk factors for non-BC death differed significantly between the predominantly white women in NHS and the Black women in BWHS, qualitative trends were similar. When predicting breast cancer, only the HRs for increasing BMI and prior mammography differed significantly between the cohorts; however, increasing BMI was associated with increasing breast cancer risk in both cohorts and having a mammogram in the past 2 years was associated with women being less likely to be diagnosed with breast cancer in 5 years. Simulation modelers have also found that it is necessary to consider women’s prior use of mammography in estimating breast cancer incidence . While wWhile our rigorously developed model predicts breast cancer and non-breast cancer death, it also has limitations. Since actual mammographic density was not available for most participants, we considered predicted mammographic density. However, we did not find an association with breast cancer risk likely because our model already included several factors associated with breast density  and because the prevalence of high mammographic density decreases with age as does its effect on breast cancer risk –56. FurtWe formally modeled prediction of breast cancer and non-BC death in a competing risk model we are developing for clinical use. As demonstrated with the examples in Table Additional file 1. Supplementary materials.


This systematic review aims to identify factors associated with risk-reducing salpingo-oophorectomy (RRSO), including the uptake rate and decision timing, among women at high risk for hereditary breast and ovarian cancer (HBOC).We found 4,935 relevant studies using MEDLINE, Embase, CINAHL, and PsycINFO on July 6, 2020. Two authors screened the articles and extracted data. Twenty-four studies met the inclusion criteria. Quality assessment of articles was conducted using the Risk of Bias for Nonrandomized Studies tool.BRCA1/2 carrier, mastectomy history, perceived risk for ovarian cancer, and perceived advantages of RRSO, whereas objective cancer risk was not significant. The uptake rate of RRSO was 23.4% to 87.2%  among high-risk women for HBOC. The mean time to decide whether to undergo RRSO after BRCA testing was 4 to 34 months.Five types of factors were identified . The specific significant factors were older age, having child(ren), being a RRSO decisions are affected by demographic, clinical, and psychological factors, rather than objective cancer risk. Nonetheless, women seeking RRSO should be offered information about objective cancer risk. Even though decision-making for RRSO is a complex and multifaceted process, the psychosocial factors that may influence decisions have not been comprehensively examined, including family attitudes toward RRSO, cultural norms, social values, and health care providers’ attitudes. BRCA1 and BRCA2, respectively) [BRCA mutations are found in 15.7% of women with a personal or family history of breast/ovarian cancer in Korea [BRCA1 carriers, the average lifetime cancer risks are 67% for breast cancer and 45% for ovarian cancer. Among BRCA2 carriers, these risks are 66% and 12% for breast and ovarian cancer, respectively. Therefore, clinical prevention options, such as risk-reducing salpingo-oophorectomy (RRSO), risk-reducing mastectomy (RRM), intensive surveillance for early detection of ovarian/breast cancer, and chemoprevention with tamoxifen, are offered to women at high risk for HBOC [Hereditary breast and ovarian cancer (HBOC) is a syndrome that is associated with an increased incidence of breast and ovarian cancers . Approxiin Korea . Among BBRCA mutations aged 35 to 40 years who have completed childbirth [Among these preventive strategies, the most frequently offered option is RRSO because it reduces the risk of cancer incidence by more than 95% for ovarian cancer and 50% for breast cancer . The Natildbirth ,5,6. Becildbirth ,5, but aildbirth . Previouildbirth , to percildbirth . Therefoildbirth .BRCA test, it takes a long time for some women to select a preventive option [After disclosure of the results of the e option , and RRSe option . TherefoBRCA1/2 tests and RRSO for high-risk populations for HBOC in 2012 and 2013, respectively [BRCA and preventive surgery has increased since the actress Angelina Jolie, who is a BRCA1 carrier, received RRM in 2013 [Although previous studies have shown that RRSO decision-making is influenced by demographic, clinical, psychological, and social factors ,11-13, oectively . In addi in 2013 . DespiteBRCA testing and RRSO among women at high risk for HBOC.This systematic review sought to identify the factors that influence the decision to undergo RRSO based on the existing literature. In addition, we explored the uptake rate of RRSO and the time interval between Ethics statement: This study is a literature review of previously published studies and was therefore exempt from institutional review board approval.This systematic review was conducted in accordance with the guidelines proposed by the Preferred Reporting Items of Systematic Review and Meta-Analysis (PRISMA) . The stuBRCA,” “risk-reducing surgery,” and “decision-making,” using “OR” for similar concepts and using “AND” for differing clusters. On July 6, 2020, the MEDLINE, Embase, CINAHL, and PsycINFO databases were searched, without any limitations on publication date ; (2) reported on the factors influencing RRSO decision-making; and (3) were written in Korean or English. The exclusion criteria were as follows: (1) gray literature without peer review ; (2) animal experiments or preclinical experiments; (3) reviews, letters, and editorials; and (4) qualitative research.To identify suitable studies for this study purpose, PICO  criteria were defined and listed . Based oDuplicate studies and gray literature were removed using a bibliography management program . Two authors (SYP and YLK) independently reviewed the titles and abstracts of identified studies, and selected studies according to the selection criteria.Two authors (SYP and YLK) independently assessed the quality of selected articles using the Risk of Bias for Nonrandomized Studies tool  . RoBANS One author (SYP) extracted the data from the selected literature using a predesigned form , and another author (YLK) cross-checked the accuracy of data extraction. To show the overall significance of the reported factors, we synthesized data if the relevant factors were reported in two or more studies, and presented the ratio of the number of papers between significant and non-significant factors. The factors affecting decisions about RRSO were categorized into (1) demographic factors, (2) clinical factors, (3) family history of ovarian/breast cancer, (4) psychological factors, and (5) the objective risk of developing ovarian or breast cancer. To analyze the RRSO uptake rate, the intent and rate of RRSO were presented separately.The chosen search strategies identified a total of 4,935 studies, from which 24 studies were finally included in the systematic review -14,17-36The risk of bias in the selected literature was moderately low . In partAmong the 19 studies that explored the effect of age on RRSO, 13 (68.4%) reported that older age was associated with a higher uptake of RRSO ,31,33,35In 60.0% of the articles ,23,26, mBRCA1/2 gene mutations were a significant factor in decision-making about RRSO [BRCA mutation was not a significant factor in the articles (83.3%) that reported it [All of the articles (100%) found that out RRSO ,19,23,30orted it ,14,26,28orted it ,18,22,27orted it ,23,27 anThe vast majority of articles (81.8%) ,28,32,36The perceived risk/anxiety/concern for ovarian cancer was a significant factor in determining RRSO in most studies  that reported it ,29,31-36As a possible factor influencing RSSO decision-making, the reported objective cancer risk was the risk level evaluated by family cancer/genetic specialists based on a person’s family cancer history ,36, and The RRSO rate was 11% to 87.2% across the 21 articles. In six studies ,33,36, 1BRCA test and RRSO  and ovarian cancer 66.7%) were not associated with having RRSO. This result is supported by a systematic review reporting that RRM was more strongly affected than RSSO by family cancer history % were no, RRSO waBRCA carriers chose RRSO more frequently than non-carriers, which was an expected result. Although Padamsee et al. [BRCA mutation, in this study there was no evidence that the type of BRCA mutation affected decision-making about RRSO [BRCA mutation type [Perceived risk of cancer is a well-known factor contributing to the choice to undergo risk-reducing surgery among women at high risk for HBOC ,7,37. Oue et al.  suggesteout RRSO ,14,26,28ion type .A systematic review  found thPrevious qualitative studies showed that family factors were related to RRSO ,39, and In this review, objective cancer risk was not related to the decision to undergo RRSO. This result implies that women decide to undergo RRSO to reduce anxiety based on the perceived risk of ovarian cancer , rather The uptake rate of RRSO varied from 11% to 87.2% across the selected articles in this review. Among those who opted for RRSO, Koreans were younger than Europeans ,13,25, aBRCA carrier are major factors affecting RRSO decision-making.The generalizability of the results of this systematic review is limited because we did not review the factors associated with RRSO from qualitative research. Nevertheless, this study is meaningful in that it provides fundamental information regarding factors affecting RRSO decisions based on current evidence. In particular, we found that the perceived risk of ovarian cancer, older age, and being a Based on the results of this study, we suggest the following: (1) considering that the decision process of RRSO is complex and involves various factors, it is necessary to identify how family factors, socio-cultural characteristics, and healthcare systems affect the decision process; (2) further studies are needed to confirm the significance of factors that have been reported in a few studies or have shown contradictory results across articles; and (3) interventions should be developed based on information about objective cancer risk.


Breast cancer patients are at elevated risk of depression during treatment, thus provoking the chance of poor clinical outcomes. This retrospective cohort study aimed to investigate whether integrating Chinese herbal medicines citation(CHM) into conventional cancer therapy could decrease the risk of depression in the long-term breast cancer survivors.n = 1,450) and did not receive  CHM treatment were enrolled. The incidence rate and hazard ratio citation(HR) for depression between the two groups was estimated at the end of 2012. A Cox proportional hazard model was constructed to examine the impact of the CHM use on the risk of depression.A cohort of patients aged 20–70 years and with newly diagnosed breast cancer during 2000–2008 was identified from a nationwide claims database. In this study, we focused solely on survivors of breast cancer at least1 year after diagnosis. After one-to-one matching for age, sex, and baseline comorbidities, breast cancer patients who received ], and the adjusted HR remained significant at 0.74 (95% CI 0.58–0.94) in a Cox proportional hazards regression model. The corresponding risk further decreasing to 43% among those using CHM for more than 1 year.Finding from this investigation indicated that the lower risk of depression observed in breast cancer patients treated with CHM, suggesting that CHM treatment should be considered for disease management toward breast cancer. Yet, the optimal administered dose should be determined in further clinical trials. Depression is a chronic medical condition that impacts the cognitive, affective and physical wellbeing of a person . GloballBreast cancer is the most common form of malignancy in women, and affected patients are at a higher likelihood of experiencing depression, a condition aggravated by the necessity to undergo continuous life-saving treatments. After administering their cancer-related questionnaire to 179 women with breast cancer, via regulating HPA Axis and the level of amino acids neurotransmitters  has shown promising results in improving the body’s ability to fight malignant disease. Several of these herbs were further proven to improve cognitive function through the suppression of monoamine oxidase activity and oxidative stress as well as the modulation of the hypothalamic-pituitary-adrenal axis activation . Take ussmitters . In thisTaiwan’s NHI program, launched in 1995, is a single-payer government-operated compulsory health insurance program. As of 2015, up to 99.6% of Taiwan’s population was enrolled in the NHI program Research data for this retrospective cohort study were obtained from the Longitudinal Health Insurance Database citation(LHID) administered by the Ministry of Health and Welfare. The LHID contains data on one million beneficiaries randomly sampled from the Registry for Beneficiaries of the NHI Research Database. The use of multistage stratified systematic sampling ensures no significant deviations in the distribution of sex and age between the LHID enrollees and the general population . The clan = 3,512). Meanwhile, to reduce the potential for disease misclassification, only those with catastrophic illness certification due to breast cancer were recruited. In Taiwan, insured persons with major chronic conditions can apply for catastrophic illness certification that grants exemption from co-payment. The date on which the patient gained approval for catastrophic illness registration due to breast cancer was considered the index date  code for the identification of patients with breast cancer. Patients aged 20–70 years who were newly diagnosed with breast cancer (ICD-9-CM code: 174) were considered for enrollment in the study. To ensure the identification of new breast cancer cases, we employed a 4-year washout period (1996–1999) to exclude any patients who had been diagnosed with breast cancer before entering the cohort (dex date .n = 94), and those followed up for less than 1 year after diagnosis of breast cancer (n = 38). Afterward, the final cohort included 3,380 patients.The study outcome was the first diagnosis of depression, which included major depressive disorder (ICD-9-CM codes: 296.2 and 296.3), dysthymic disorder (ICD-9-CM code: 300.4), and depressive disorder not elsewhere classified (ICD-9-CM code: 311). In this study, the diagnosis of depression was determined if patients were treated with ≧ 3 outpatient treatment claims or ≧1 hospitalization due to depression. We then excluded those who had a prior diagnosis of depression before the breast cancer onset  17800, NTD 17,881–43,900, and ≥ NTD $43901. As to the urbanization level, it was calculated according to a published scheme that classified 359 communities in Taiwan into seven stratums, with a higher level indicating a higher degree of urbanization. The classification scheme included the population density, proportion of persons with a college-level education or higher, proportion of elderly residents, proportion of agricultural workers, and number of physicians per 100,000 population. In this work, the urbanization degree was grouped into three strata: urban (levels 1–2), suburban (levels 3–4), and rural (levels 5–7) . The inft-test. Then we conducted a Cox proportional hazards regression analysis to compute the adjusted hazard ratio citation(HR) with 95% confidence interval citation(CI) of risk of depression in association with CHM use, after adjusting for age, sex, insurance premium (an indicator of income), urbanization level, and CCI simultaneously in the model. To test the robustness of the relationship between CHM use and depression risk, all CHM users were divided into two groups based on time of CHM use: (1) 31–365 days, and (2) ≥ 366 days. The Kaplan–Meier method was used to estimate the cumulative risk of depression in each group, and the difference between groups was assessed using the log-rank test. The proportional hazards assumption was examined by plotting the log [–log ] vs. the log citation. A P < 0.05 was considered statistically significant.Data were analyzed using SAS version 9.3 software . Distributions of sociodemographic data and comorbidities between the CHM users and non-CHM users were compared by using the chi-square and Student’s n = 1,450) and non-CHM users . Demographic data are shown in Data were analyzed for CHM users (P < 0.01) , respectively. The incidence of depression was significantly lower among CHM users than non-CHM users   . The use < 0.01) .Puerariae Lobatae Radix), Xiang Fu citation(Cyperi Rhizoma), Bai-Hua-She-She-Cao citation(Hedyotidis Herba), Shao-Yao-Gan-Cao-Tang citation, and Yin-Qiao-San .The most commonly prescribed Chinese herbal products for breast cancer patients are summarized in In this evidence-based cohort study exploring the relationship between CHM use and subsequent depression risk in breast cancer patients, we found that patients receiving CHM had a nearly 25% lower risk of depression than did those not using CHM. Furthermore, those receiving CHM for more than 365 days were found to have a significantly lower risk of depression by 43%. Through the determination of dose-response relation between an exposure citation(CHM use) and the risk of an outcome citation(depression incident), it may indeed support the causal association between the intensity of CHM use and the resultant lower risk for depression among breast cancer patients.No previous studies have reported the long-term influence of CHM on depression risk in breast cancer patients, thus precluding comparison of results. Nevertheless, the positive therapeutic effect of CHM observed in this work adds to the accumulating evidence suggesting that CHM exerts antidepressant effects by modulating dysfunctional neurotransmission . ProposeA major contribution of this study is the identification of specific CHM products associated with the observed lower risk of depression in breast cancer patients. We found that three single-product CHM commonly used to treat breast cancer were associated with a lower sequent risk of depression, like use of Ge-gen, Xiang-fu, and Bai-hua-she-she-cao. A previous study using an animal model reports that Pueraria, the principal ingredient of Ge-gen, exerted marked anti-depressant effects by abating nuclear factor kappa beta (NF-κB) signaling . NF-κB iin vivo study by Xiang-fu is a cytotoxic herb that inhibits cell growth and promotes apoptosis of breast cancer cells . A recenAnother commonly used single-herb product, Bai-Hua-She-She-Cao (Hedyotis diffusa), is commonly used to relieve heat and toxicity in cancer patients . Recent With regard to multi-herb products, the use of Shao-Yao-Gan-Cao-Tang was observed to be associated with a decreased risk of depression in our cohort. A previous study reported that an active component of Shao-Yao-Gan-Cao-Tang decoction, such as glycyrrhizin, affected multiple biological processes and pathways that participate in neuron apoptosis and inflammatory responses , all of As previously described in “Materials and methods” section, the database used in this study has several strengths, including its large sample size, the use of electronic records from a national health insurance registry, and a uniform approach to outcome assessment, all of which could strengthen validity of the study findings. On top of that, the selection bias ought to be minimized to a great extent by using data from the NHI database, which included over 99% of insured persons in Taiwan. Nonetheless, several limitations of this study merit attention. First, our findings were derived from analysis of retrospective cohort data based on ICD-9-CM diagnostic codes. Thus, relevant cases may have been misclassified. To improve diagnostic accuracy and avoid overestimation of the prevalence of cases of interests, we applied a 4-year washout period for breast cancer, where patients with a diagnosis of breast cancer during that period were considered prevalent and, therefore, excluded from analyses. Medical records were confirmed by requiring at least 3 outpatient service claims, or at least 1 inpatient hospitalization claim during the study period. Additionally, the diagnostic inclusion of breast cancer was further verified by the catastrophi illness certification. The NHI of Taiwan randomly reviews the charts and audits medical charges to verify the accuracy of claims. Despite this procedure, we recognize that the misclassification of cases is always a risk in database research, but this would be expected to occur at random which would likely serve to only bias the overall HR observed toward the null value and thus provide a more conservative estimate of effect. Second, data used in this study were drawn from a claim-based database and, accordingly, no detailed clinical information regarding laboratory data, family history, physical activity, and individual social network relationship was available. Thus, future studies that examine the influence of these variables are worthy of pursuit. Nevertheless, to carefully address the confounding by indication that may arise in this real-world comparative effectiveness study, we have capitalized on propensity score—matched analysis to analyze the association of CHM use with the attack of depression. For each breast cancer patient who received CHM, one control patient was selected by 1:1 matching, based on a propensity score. Additionally, to more robustly assess if other treatments may affect the finding herein, we reanalyzed the relationships between CHM use and subsequent risk of depression by adjusting for the utilization numbers of radiotherapy after breast cancer onset. The rational underlying this procedure was based on the assumption that radiotherapy for breast cancer patients is an obligatory component of a breast-conserving treatment modality and could cause deleterious psychological symptoms in such a group of patients . The re-in vivo studies that attempt to uncover the main mechanisms of prescribed herbal formulae that may be beneficial for such groups.Individuals with breast cancer suffer from the mood disorders more frequently than the general population, especially depression. This is the first population-based survey that rigorously evaluated the impact of CHM use on the prevention of depression among them. We found that integration of CHM into the conventional treatment regimen for breast cancer for more than 2 years may reduce the subsequent risk of depression by nearly 50%. This noteworthy finding can provide an impetus for further research venues, such as focusing on factors associated with utilization of CHM, as well as The data supporting the conclusion of this study are available from the authors, but the raw data (NHIRD) needs to be obtained from the National Health Research Institute of Taiwan through an application process upon approval, further inquiries should be directed to the corresponding author.This study was approved by the Research of Ethics Committee of Dalin Tzuchi Hospital. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.SY-Y, C-CY, C-KW, and T-YT: conception and design. M-CL and T-YT: provision of study material and patients. HL and T-YT: collection and assembly of data. SY-Y, HL, JS-J, S-WY, C-KW, and T-YT: data analysis and interpretation. SY-Y, HL, JS-J, S-WY, H-LH, MC, C-CY, C-KW, and T-YT: manuscript writing. SY-Y, HL, JS-J, S-WY, H-LH, MC, M-CL, C-CY, C-KW, and T-YT: final approval of manuscript. All authors contributed to the article and approved the submitted version.


Assessment of ER-negative subtype breast cancer (ER−BC) risk indicated that OCs use significantly increased the risk: OR = 1.3079, 95% CI: 1.0003 to 1.7100, p = 0.050. Analysis for HER2-positive breast cancer (HER2+BC) risk showed that OCs use statistically non-significantly lowered the risk: OR = 0.8810, 95% CI: 0.5977 to 1.2984, p = 0.522. Meta-analysis with regard to Triplet-negative breast cancer (TNBC) risk showed non-statistically significant increased risk: OR = 1.553, 95% CI: 0.99 to 2.43, p = 0.055. The findings of the meta-analysis suggest that breast cancer risk in premenopausal women may vary with respect to molecular subtypes. Extensive scientific work is still necessary in order to understand the impact of OCs use on breast cancer risk in young women.Breast cancer is divided into four molecular subtypes. Each one has distinct clinical features. The aim of this study was to assess individual breast cancer subtype risk in premenopausal women taking oral contraceptives (OCs). Databases  were searched to January 2022 to identify case-control studies meeting the inclusion criteria. The influence of OCs intake on the risk of ER-positive breast cancer (ER+BC) was revealed to be non-significant with regard to reduction: OR = 0.9134, 95% CI: 0.8128 to 1.0265,  Breast cancer is the leading type of cancer in women in most countries in the world. The incidence of breast cancer has increased dramatically in the past fifty years. Indeed, it is estimated that one in eight women will develop cancer during their lifetime. According to GLOBOCAN 2020 data, breast cancer is currently one of the most prevalently diagnosed cancers, with an estimated number of 2.3 million new cases worldwide. This figure represents 11.7% of all cancer cases globally . SeveralBreast cancer remains the most common malignancy among younger patients. The incidence of breast cancer in young women is 5.6% and is rising rapidly . DiagnosIntrinsic molecular classification of subtypes of breast cancer was done according to gene expression patterns ,12,13. FProlonged exposure to ovarian hormones may increase the risk of breast cancer. Endogenous estrogens are involved in the development of breast tumors by stimulating proliferation, increasing the number of cell divisions, and accumulating DNA damage caused by replication, as well as generating genotoxic compounds ,20.Globally, around 140 million women, approximately 13% of all women between 15 and 49 years old, utilize OCs . AlthougThe aim of this study was to assess the risk of individual breast cancer subtypes in premenopausal women taking OCs.Based on PRISMA  guidelines, electronic databases—MEDLINE (PubMed), EMBASE, and the Cochrane Library—were searched to identify works published to January 2022 examining the impact of oral contraception (OC) on the risk of the breast cancer molecular subtypes in premenopausal women ,28. The To evaluate a study’s eligibility for inclusion, titles, abstracts, and articles were reviewed independently. Two researchers independently graded the included studies with differences resolved by consensus between other investigators. A combined search was performed, looking for case-control studies . The studies included in the meta-analysis provided information on the relationship between OC use and breast cancer by molecular status. The exclusion criteria were: postmenopausal women as participants; insufficient quantitative data, the results were reported as graphics; duplicate reports; case-only studies, and articles published in languages other than English.Data were extracted and subsequently reviewed for accuracy. From each of the included studies, the following data were extracted: (a) the first author’s last name, source of study, country, publication year, years of data collection, and the number of participants in subgroups; (b) information on the use of OCs in subgroups: ever/never, duration, age at first use, and years since last use prior to diagnosis; (c) in the original studies, different definitions and combinations of subgroup used; this meta-analysis included subtypes grouped into the four categories: ER-positive (regardless of their PR/HER2 status), ER-negative (regardless of their PR status), HER2-positive (absence of ER/PR), and Triplet-negative (absence of ER/PR/HER2).To evaluate the methodological quality of the included studies, we applied the Newcastle–Ottawa Scale (NOS) . Each of2. I considered the cuts off points of I2 suggested by Higgins et al. [Meta-analysis was performed using Statistica 13.3 software . The risks  of breast cancer in premenopausal women associated with the OC were estimated for each study. The distribution of cases and controls at risk, ORs, and 95% CI were separately identified by molecular characteristics and for OC use (ever or never). Summary risk was calculated as estimates (95% CIs) and values from single studies were combined using the random effects model (DerSimonian and Laird). Random effects incorporate an estimate of the between-study variance and tend to provide wider confidence intervals when the results of the constituent studies differ among themselves ,29. Hetes et al. , categorThe publication bias was assessed using Begg & Mazumdar’s rank correlation test and Egger’s regression test ,31. FunnDetails of the search and identification process are presented in This analysis is based on data from nine case-control studies evaluating the effect of OCs on the risk of specific molecular subtypes of breast cancer in premenopausal women. The quality of the studies included in the meta-analysis assessed on the basis of the NOS ranged between 4 and 8, and the average score was 6.89 for the included studies.The characteristics of the selected works are summarized in The presented meta-analysis is based on data from nine studies ascertaining the effect of OCs on the risk of individual molecular subtypes of breast cancer among premenopausal women.p = 0.128, I2 = 0.00%. Results of Begg’s test: tau b = −0.0476, z = −0.1502, p = 0.881, and Egger’s test: b0 = −0.0404, 95% CI: −3.3254 to 3.2445, t = −0.0316, p = 0.976 indicated the lack of evidence of publication bias , duration of use of OCs , and time since last use  showed these covariates had a non-significant impact on breast cancer risk in premenopausal women.The assessment of the influence of OC intake on modifying factors of ER+BC risk is presented in  studies ,37,39 anp = 0.050, with relatively moderate heterogeneity: I2 = 54.71% , for age at first OC use , and for years since last use  has not confirmed the impact of these covariates on this breast cancer subtype.Estimation of the effect of duration of use on the risk of HER2+BC was based on data from three studies ,36,38. T= 58.57% . The rel= 19.30% . Multivap = 0.055, with relatively high heterogeneity, I2 = 77.97% , years since last use , and age at the start of OC taking  did not confirm the impact of these covariates on this breast cancer subtype.The analysis of the effect of the duration of OC use on the risk of TNBC was performed based on the results of three studies ,37,38. M= 82.14% . The inf= 81.18% . Multivap = 0.128. Moreover, the meta-analysis risk of ER-negative subtype breast cancer indicated that ever-use of OCs significantly increased breast cancer risk, compared to non-taking OCs: OR = 1.3079, 95% CI: 1.0003 to 1.7100, p = 0.050. In addition, the relationship between OC taking and HER2+BC risk showed that ever-use of OCs statistically non-significantly lowered the risk: OR = 0.8810, 95% CI: 0.5977 to 1.2984, p = 0.522. Finally, the performed meta-analysis of TNBC risk showed non-statistically significant increased TNBC risk in women taking OCs: OR = 1.553, 95% CI: 0.99 to 2.43, p = 0.055.The presented meta-analysis conducts for the first time an assessment of breast cancer risk in premenopausal women as related to molecular subtypes. The influence of OCs intake on the risk of ER-positive breast cancer among women showed that, compared to not using OCs, ever-taking OCs statistically non-significantly reduced the risk of breast cancer: OR = 0.9134, 95% CI: 0.8128 to 1.0265, p = 0.002, as well as ER−BC: OR = 1.20, 95% CI: 1.03 to 1.40, p = 0.019. The summary meta-analysis also showed a significant reduction in the risk of ER+BC: OR = 0.92, 95% CI: 0.86 to 0.99, p = 0.026, and a slight reduction in the risk of HER2+BC: OR = 0.95, 95% CI; 0.79 to 1.14, p = 0.561 after OC taking [Our previous meta-analysis of the effect of OC use on the risk of breast cancer was conducted for the general population . We inclp < 0.00001). In addition, the meta-analysis of Kahlenborn et al. [p = 0.04), as did OC use longer than 5 years  [p > 0.05) [Similar results were seen in the meta-analysis of Li et al.  evaluatin et al.  performen et al.  for the n et al. . Resultsn et al.  suggest  = 0.02) . A study > 0.05) . My resuThe results of this meta-analysis should be interpreted in light of some limitations. The first may be the searching of publications submitted only in English and the fact that most of the included studies were conducted in North America. The second is that it can be difficult to define the cutoff point for the adopted age of the ‘premenopausal woman’ or ‘young woman’ categories . Thirdly, evidence for the associations between different OC formulations and breast cancer risk, especially by disease subtype, is limited. Fourthly, self-reporting of OC use may lead to an overestimation or underestimation of data. Fifthly, the number of cases was relatively small and previous case-control studies were based predominantly on older women. In addition, it was not reported which type of OCs they used. Moreover, there was a lack of information on confounders that could probably have had an influence on the statistical power limitations involved in examining subgroup associations.The findings of the study suggest that breast cancer risk in premenopausal women may vary by molecular subtype. This conclusion prompts the suggestion that young women who use OCs should be examined more closely in population screenings of breast cancer. Unquestionably, extensive scientific work is still necessary in order to understand the impact of OC use on breast cancer risk in premenopausal women.


Food additive emulsifiers are found in thousands of industrial foods and may exert deleterious effects on gut microbiota and carcinogenesis according to experimental studies. However, their associations with cancer risk has not been investigated yet. This study aimed to investigate these associations in a large population-based prospective cohort.This study included 102,485 French adults from the NutriNet-Santé cohort . Food additive emulsifier intakes were estimated using repeated 24h dietary records linked to brand-specific food composition databases on food additives. Associations with incident cancer risk were assessed using Multivariable Cox models.3,511 incident cancer cases were diagnosed during follow-up . Intakes of sodium citrate , xanthan gum , and mono- and diglycerides of fatty acids  were associated with increased overall cancer risk. Higher intakes of E331 (p-trend = 0.046), sodium stearoyl-2-lactylate , total lactylates , total celluloses , carob bean gum , and E471 (p-trend=0.006) were associated with increased overall breast cancer risk. Higher intakes of carrageenan , E415 (p-trend=0.02), and triphosphates  were associated with increased post-menopausal breast cancer risk.These results are the first to investigate and report direct associations between cancer risk and exposures to seven individual and three groups of food additive emulsifiers. If replicated, they may have an important public health impact, considering the omnipresence of these additives in industrial foods globally.• This study is the first to precisely assess exposures to food additive emulsifiers in a population-based study.• Intakes of food additive emulsifiers were associated with increased risk of cancer.


Background and Objectives: In 2020, the World Health Organization (WHO) reported 9.9 million deaths from cancer, with a mortality rate of 10.65%. Early detection of cancer can decrease mortality and increase the chance of cure. In Saudi Arabia, multiple studies were performed for awareness and attitudes toward cancer, but few studies evaluated the awareness of familial and inherited cancers. Materials and Methods: This is a cross-sectional observational survey of the awareness, knowledge, and attitudes of Saudi women toward familial and inherited cancers. The estimated sample size was 385. Questionnaires were distributed through social media platforms from 1 January 2021 to 22 January 2021. Results: Of the 385 participants, the majority have a bachelor’s degree. More than half (68.9%) know that family history is related to cancer, and approximately 57.2% are aware of genetic testing. The most common indication of genetic testing is premarital testing (18.5%). An inverse relationship is noted between the awareness of familial and inherited cancers and age . However, awareness of inherited and familial cancer is positively associated with awareness of the association of genetic mutation to cancer  and knowledge about genetic testing . Conclusions: Our results reveal that Saudi women, especially older adults, have suboptimal knowledge about inherited and familial cancers, and poor attitudes toward genetic screening. We recommend increasing public awareness regarding risk factors and screening for inherited and familial cancers. Cancer is a common cause of morbidity and mortality. In 2020, breast, lung, colorectal, prostate, stomach, and liver cancers were the most common cancers worldwide . The WorIn Saudi Arabia, the number of newly diagnosed cancer cases in 2020 was 27,885 . The most common cancers in males were colorectal cancer, non-Hodgkin lymphoma, leukemia, and thyroid and lung cancers. In females, the most common types of cancer were breast, thyroid, colorectal, and uterine cancers, and leukemia. The number of deaths due to cancer was 13,069  [Given the huge impact of malignancy, early cancer detection and treatment initiation can decrease mortality and increase the chance of cure . The mosMany studies addressed the Saudi populations’ awareness and attitude toward cancer. Awareness of breast cancer among Saudi women was found to be poor ,12. MisiThere are many etiologies of cancer; one of them is inherited/familial, such as Lynch syndrome  and BRCADespite the availability and tangibility of information in the Internet era, worldwide communities had poor–moderate knowledge about inheritance features and factors of breast cancer ,21 and pThis was a cross-sectional observational survey of the awareness, knowledge, and perception of Saudi women toward familial and inherited cancers. On the basis of the Saudi female census of 2018, which included 10,192,732 females, the sample size was estimated. With a confidence level of 95% and a confidence interval of 5%, the approximate sample size was 385.There were two major sections of close-ended elements in the questionnaire. The first section included sociodemographic data, and the second evaluated the respondents’ awareness of familial and inherited cancer, adapted from a study in Jordan ,27. A pip < 0.05 considered significant. Data were then exported for analysis using SPSS for Windows, version 21.0 . Categorical variables are expressed as percentages. The odds ratio was used to study association between different variables. Univariate and multivariate logistic regression were used to assess the predictive factors of the awareness of familial and inherited cancer among Saudis, with The study was approved by the King Saud University Institutional Review Board (E-20-5397). The participants completed the online surveys anonymously and voluntarily. Furthermore, each participant had a unique IP address to prevent duplication, and the participants were not offered rewards or incentives for their participation.A total of 385 participants completed the questionnaire. Most participants are 18–24 years (35%), have a bachelor’s degree (65%), are single (55.9%), are unemployed (77.2%), and have no health insurance (68.4%). Only 3.5% of them are smokers, and 32.7% have children .There is a huge variation in the awareness of the participants toward familial and inherited cancer in different cities in Saudi Arabia .p = 0.017, CI = 0.765–0.973), awareness of the association of genetic mutation with cancer , and the knowledge about genetic testing  , awareness about the association of genetic mutation with cancer , and knowledge about genetic testing  are found to be significant for awareness of familial and inherited cancer  . Howeverd cancer .p = 0.003, CI = 0.723–0.938).This study addressed the awareness and attitude of Saudi women toward inherited cancer and assessed the associated factors. Although most participants are educated (with a bachelor’s degree), most have suboptimal knowledge about inherited and familial cancers. Moreover, an inverse relationship is observed between awareness of familial and inherited cancers and age; older participants are significantly less aware , with some regional variations, and the highest prevalence being in rural areas . ConsangMost participants are aware of the association of family history (68.9%) and genetic mutations (57.5%) with cancer. Although more than half of the respondents (57.2%) know that there are genetic tests to detect familial and inherited cancers, the majority (74.2%) have never undergone genetic testing. Costs and lack of insurance are reported as major factors that discourage genetic testing ,33,34. MOf the 105 participants who underwent genetic testing, 59% participated for premarital testing , and only 7.6% through a family physician. The low tendency of participants toward genetic testing could be linked to the fact that most participants (68.4%) do not have insurance to cover it. Furthermore, only 21.8% understand the role of the genetic counselor. The Healthy Marriage Program is a national premarital screening program for some of the highly prevalent inherited diseases in Saudi Arabia, such as sickle cell disease and thalassemia . Only 73Family physicians and general practitioners play a vital role in referring at-risk patients to genetic counselors or clinical geneticists. However, one study shows that general practitioners have limited knowledge about hereditary cancers, testing services, and genetic counseling , which mThe attitudes of our participants toward genetic screening are not reassuring: 43% are unwilling to undergo cancer screening through genetic testing. Further efforts are required to ensure the proper counseling, consenting, and privacy of those undergoing genetic testing.This study has a few limitations. The study design is a cross-sectional study, which may be prone to incidence–prevalence bias. The sample size only includes women, who happen to be mostly bachelor’s degree graduates. Therefore, the results of this study cannot be generalized to the general Saudi population. Also, there is an inflation of the CI due to the use of 95% CI, therefore, the problem of the monotonic likelihood of the univariate model may be noted in this study . We recoIn conclusion, our findings indicate suboptimal knowledge among Saudi women, particularly older women, about inherited and familial cancers, and poor attitudes toward genetic screening. We recommend increasing public awareness regarding risk factors and screening for inherited and familial cancers.


Previous studies on the association between glycaemic index (GI) and glycaemic load (GL) in relation to breast cancer risk are contradictory. The aim of this study was to examine the association between dietary GI and GL and risk of breast cancer in Iranian women.Population-based case–control study. Dietary GI and GL were assessed using a validated Willett-format 106-item semi-quantitative FFQ.Isfahan, Iran.Cases were 350 patients with newly diagnosed stage I–IV breast cancer, for whom the status of breast cancer was confirmed by physical examination and mammography. Controls were 700 age-matched apparently healthy individuals who were randomly selected from general population.After controlling for potential confounders, individuals in the highest tertile of dietary GI had 47 % higher odds of breast cancer than women in the lowest tertile ). Stratified analysis by menopausal status showed such association among postmenopausal women ). We found no significant association between dietary GL and odds of breast cancer either before ) or after adjustment for potential confounders ). In addition, stratified analysis by menopausal status revealed no significant association between dietary GL and odds of breast cancer.Our findings showed a significant positive association between dietary GI and odds of breast cancer. However, we observed no significant association between dietary GL and odds of breast cancer. In Iran, among different types of cancer, breast cancer is considered as the first malignancy diagnosed in women.Breast cancer (BC) is the second most common cancer globally that affects 1·4 million subjects each year. Although the majority of studies assessing the association between diet and breast cancer have emphasised on the role of dietary fats, dietary carbohydrate intake may also play a role in this regard. Dietary glycaemic index (GI) and glycaemic load (GL), as indicators of quality and quantity of dietary carbohydrate intake, have extensively been investigated in relation to risk of breast cancer in earlier studies; however, findings are contradictory. For instance, dietary GL was positively associated with the risk of breast cancer in the Italian European Prospective Investigation into Cancer and Nutrition cohort; however, such association was not observed for dietary GI. In a cohort study among Canadian postmenopausal women, high-GI diet was associated with an increased risk of breast cancer. However, no significant association was observed between dietary GI and GL and the risk of breast cancer in another prospective study.The aetiology of breast cancer is largely unknown. However, several factors including age, sex, race, genetic factors, reproductive history, menopausal hormone use, alcohol intake, tobacco use, physical inactivity, radiation exposure and dietary intakes might contribute to its aetiology. The present study has nearly 2·5 times higher sample size compared with a similar study that was done in 2020 in the country. The aim of this study, therefore, was to investigate the association between dietary GI, GL and risk of breast cancer among Iranian women.Most previous studies on the association between dietary GI, GL and risk of breast cancer came from developed countries and limited information is available in developing countries in this regard. Investigating the association of dietary GI and GL and the risk of breast cancer is particularly relevant for the Middle-Eastern countries, where more than 60 % of total energy intake is taken from carbohydrates and much of them are high GI carbohydrate with greater portion sizesThis population-based case–control study was conducted on women aged > 30 years in Isfahan, Iran. A total of 350 women with incident breast cancer and 700 age- and sociodemographic-matched controls were recruited between July 2013 and July 2015. Convenience-sampling method was applied to select cases from those who were referred to hospitals or private clinics if disease status was diagnosed during the maximum of last 6 months by physical examination, mammography findings and pathological verification. We hypothesised that unhealthy dietary patterns would increase breast cancer risk by 1·5 times. Therefore, considering type I error of 5 %, the study power of 80 %, the common ratio of 0·25 and the ratio of controls to cases as 2, the required sample size was calculated to be 350 cases and 700 controls for this project. Among breast cancer patients , those who had a prior history of surgical resection or chemotherapy or radiotherapy or all of them (this was for the current and their past conditions) were permitted to attend in our project. Patients with a history of any type of neoplastic lesion or cysts (except BC) and those with a prior history of any hormone replacement therapy were excluded. Cluster random sampling method was applied to select controls from apparently healthy women. Individuals who were not relatives of patients with BC that attended primary health care centres for their annual personal checkup or attended to receive required information about their children  were selected. From several healthcare centers in Isfahan, two centres were randomly chosen. First, considering the population under coverage, and then based on attendance of women to these centres, required sample was recruited. Controls were not included if they were of non-Iranian nationality, had a history of any cancer, cysts and pathological disease, followed special diets and had a history of hormone replacement therapy. Study participants who agreed to attend in our project, after informing about the study methodology, signed an informed consent form.. In brief, dietary information of study participants was examined using a validated Willett-format semi-quantitative dish-based FFQ for Iranian population with 106 items about usual dietary intake over the past year. Trained nutritionists through face-to-face interviews with each participant, completed FFQ. Each participant was questioned about the usual consumption frequency of a specified portion of a given food in the preceding year (the last year before diagnosis of breast cancer for cases) on a daily, weekly or monthly basis. The interviewer was not blind to the health condition of study participants; however, the same FFQ was passed to both groups. The questionnaire comprised of five groups of foods and dishes as following: (1) mixed dishes ; (2) carbohydrate-based foods ; (3) milk-derived products ; (4) fruits and vegetables (twenty-two items) and (5) sundry food items and beverages . For each food and mix dishes in the questionnaire, there was nine multiple-choice frequency response categories, which ranged from ‘never or less than once a month’ to ‘12 or more times per day’. The number of options in frequency response categories occasionally varied according to frequency consumption of food or dishes, for instance regarding seldom-used foods the number of multiple-choice options reduced, while for frequently used foods, more multiple-choice categories were considered. By considering the daily frequency and weight of the portion sizes of each food and mix dishes on the basis of household measures, all the information was converted to food consumption in grams per day. Subsequently, the average daily intake of energy and nutrients was derived using US Department of Agriculture food composition database (Iranian modified version).Detailed dietary intake assessments have been described elsewhere–18, it seems that the questionnaire works well in reflecting long-term dietary intakes.A classic validation study was not conducted for the current FFQ used in this study; however, given the significant expected associations between dietary data derived from this FFQ and several health-related outcomes in our previous publicationsa × available carbohydratea)/total available carbohydrate, in which available carbohydrate was computed as total carbohydratea minus fibrea. The US Department of Agriculture food composition table was the main source for extracting the total carbohydrate and fibre content of foods. Of the eighty-five carbohydrate-containing foods in our food list, the Iranian GI table provided GI values for only six foods. Thus, for the remaining food items, we used data from International glycaemic index tables,22. Out of seventy-nine remaining food items, we found GI values for sixty-two foods in the International table. Glycaemic index values for seventeen food items were not available in that table; therefore, for these food items, we used the values for similar foods based on physical and chemical features. All derived GI values from International glycaemic index tables were relative to glucose as the reference food however for values derived from Iranian GI table since the reference food was white bread we multiplied the amount of GI for each food by 0·7 to obtain the GI value based on glucose as the reference. Regarding mixed meals and dishes, the GIs of individual food constituents were summed up. The total dietary GL was calculated using the following formula: /100.Total dietary GI values were computed by the following formula: ∑  by height squared (m2).A pretested questionnaire was used to collect information about socio-demographic status , lifestyle information including alcohol consumption, smoking, medical information including disease history, menopause status, family history of BC, history of breastfeeding and supplement use in a face-to-face interview with each subject. A short form of the International Physical Activity Questionnairer = 0·003 and 0·041, respectively), we did not use the residual method to adjust dietary GI/GL for energy intake. In other words, all analyses were done with non-adjusted values of dietary GI and GL for energy. To classify participants, tertile cut-points of dietary GI and GL were used. General characteristics of study participants across tertiles of dietary GI and GL were examined using one-way ANOVA for continues variables and chi-square for categorical variables. Comparison of dietary intakes across tertiles of dietary GI and GL was done using one-way ANOVA. The association of dietary GI and GL with breast cancer was assessed by using binary logistic regression in different models. Age (continuous) and energy intake (continuous) were considered in the first model. Then, we further controlled for educational status (educated/not educated), socio-economic status (poor/middle class/high class), place of residency , supplement use (yes/no), family history of breast cancer (yes/no), physical activity (continuous), marital status (married/not married/other), smoking status (smoker/non-smoker/ex-smoker), alcohol consumption (yes/no), history of breastfeeding (yes/no) and menopausal status (pre-menopause/post-menopause). BMI (continuous) was taken into account in the third model. In these analyses, the lowest intake of dietary GI and GL was considered as the reference category. The trend of odds ratios across increasing tertiles of dietary GI and GL was computed through considering the tertiles as an ordinal variable. In addition to the whole study population, the analyses were also done stratified by menopausal status. The statistical analyses were carried out by using SPSS (version 16). P values were considered significant at < 0·05.Due to the weak correlation coefficients between dietary GI and GL and energy intake in the current dataset ) or after adjustment for potential confounders ). Stratified analysis by menopausal status showed that postmenopausal women in the highest tertile of dietary GL had 48 % greater chance for having breast cancer compared with those in the lowest tertile ). This was the case when we controlled for age and energy intake ). However, the association became non-significant in the fully adjusted model ). No significant association was seen between dietary GL and odds of breast cancer among premenopausal women.In this case–control study, we found a significant positive association between dietary GI and odds of breast cancer. Such association was also seen in postmenopausal women. However, we failed to find any significant association between dietary GL and odds of breast cancer.. Decreased age at the onset of this malignancy highlights the need for more attention to deal with this problem,29. Among modifiable lifestyle factors, diet plays an important role in the pathogenesis of breast cancer. We observed a positive association between dietary GI, but not dietary GL, and odds of breast cancer. In line with our findings, a recent case–control study on 136 Iranian breast cancer survivors showed a significant association between dietary GI and odds of breast cancer; however, no significant association was found for dietary GL. Similarly, a recent meta-analysis on global data from 185 prospective studies  and 58 clinical trials  with 4635 adult participants showed a significant association between dietary GI, but not dietary GL, and breast cancer among postmenopausal women. However, several studies that examined dietary GI/GL in relation to the risk of breast cancer showed no significant association–34. A modest non-significant association of GI/GL and breast cancer have also been suggested by Turati et al. in a systematic review and a series of meta-analyses which included original cohort or case–control studies up to May 2019. Numerous studies have provided evidence on the increased risk of breast cancer with increased consumption of foods with high GI and GL, or GL alone,36,37. The inconsistencies between our findings and those of earlier studies might be explained by several reasons: (1) different study designs: some studies,33,34 with prospective design were undertaken to obtain required insight in this regard; whereas our work was a case–control study; (2) different sample size: Amadou et al. in a similar study design has assessed this association on 1000 cases and 1074 matched control women; while our study was done on 350 cases and 700 control subjects; (3) different methodology: considering confounding effects of the overall diet on GI and GL, Woo et al. in their study applied more holistic approach to assess GI/GL in relation to breast cancer risk. In other words, they applied the reduced rank regression method to identify high GI and GL dietary pattern, rather than considering dietary GI and GL alone as an independent variable and (4) different dietary patterns: the dietary GI/GL differs between different societies.Breast cancer, as one of the most important health issues, globally consumes substantial health resources, which in turn would inflict an enormous health burden in future. A positive association between dietary GI and GL and breast cancer in postmenopausal women was also documented by two case–control studies,36. In contrast to our findings, in a recent meta-analysis, postmenopausal women with higher dietary GL had higher risk of breast cancer. Two prospective cohort studies have failed to find any significant association between dietary GI and GL and risk of breast cancer among postmenopausal women,8. Consistent with ours, previous published data showed no association between dietary GI/GL with breast cancer risk among premenopausal women,32,38. However, some studies reported a positive association between dietary GI or GL and risk of breast cancer among premenopausal women. The possible reasons for the different associations in pre- and postmenopausal women have been provided below.In our study, a significant positive association was observed between dietary GI and odds of breast cancer among postmenopausal, but not premenopausal women. With regard to dietary GL, we found no significant association between dietary GL and odds of breast cancer among either pre- or postmenopausal women. Our findings were in agreement with a prospective Canadian National Breast Screening Study, conducted by Navarro Silvera and colleagues on 1461 women diagnosed with breast cancer. In that study, the RR for breast cancer in postmenopausal women comparing extreme tertiles of GI was 1·87 –41. Proliferative property of these factors in conjunction with cell differentiative and antiapoptotic actions of IGF-1,42 create metabolic environment which is susceptible for breast tumour growth. In addition, dietary GI and GL may be involved in pathways that affect concentrations and composition of serum lipids, C-reactive protein and other markers of inflammation which has long been proposed in the pathology of breast cancer. Finally, to justify potential interaction of menopause status with breast cancer risk, oestrogen depletion is a trigger for increased insulin resistance in postmenopausal women and as a result impairment of glucose transport into the cells is expected. However, in our study, the increased risk among postmenopausal women was limited to dietary GI, not GL. In trying to shed light on this difference, it is worth mentioning that overall dietary GI is indicative of overall carbohydrate quality in the diet, whereas total dietary GL that was structured based on the amount of carbohydrate consumed, captures both the quality and quantity of total dietary carbohydrate intake.Some hypotheses have been proposed on how high-GI/GL diets might elevate the risk of breast cancer. First, elevated levels of insulin after high glycaemic meals might provide a reason. Given the biological function of insulin in the liver as down-regulating the synthesis of sex hormone-binding globulin and insulin-like growth factor (IGF-1) – binding proteins 1, increased bioavailability of both sex hormones and IGF-1 is evidentIn our study, median values of dietary GI were 62·9 ± 2·4 for control subjects and 63·2 ± 2·4 for cases. In terms of dietary GL, these values were equal to 179·3 ± 63·9 for controls and 186·9 ± 66·6 for cases. In a Mexican population-based case–control study, European Prospective Investigation into Cancer and Nutrition and Melbourne Collaborative Cohort Study median values of dietary GI/GL were lower than those in our study. In a hospital-based case–control study in Italy, median values of dietary GI were higher, and those of dietary GL was lower than those of our study. The difference between values of dietary GI/GL in different studies originates from the different food patterns across different communities which may justify inconsistent findings across studies.Several strengths of this study are noteworthy. We had the chance of performing a large population-based study. Another strength was given by controlling for a wide range of confounders, therefore, an independent association between dietary GI/GL and odds of breast cancer was expected. Finally, the possibility of changing usual dietary intakes of participants has been reduced by enrollment of new cases of breast cancer. However, interpretation of our findings should be done in the context of potential limitations. The main limitation is given by the nature of case–control study such that we cannot confer causality. In addition, as with all case-control studies, we cannot rule out the possibility of selection and recall bias. Due to the nature of FFQ, it is difficult to exclude the impacts of subject’s misclassification on the final results. Despite controlling for several confounders, the possibility of residual confounding still remains. One might question the lack of controlling for dietary fibre intake in our study. It must be kept in mind that dietary GI, GL and dietary fibre are all concepts related to carbohydrates. We did not control the GL models for dietary fibre because the fibre content of foods can affect its GI and therefore GL values. Therefore, adjustment for dietary fibre intake would somehow be an overadjustment.In this case–control study, the interviewer was not blind to the health condition of individuals because cases were interviewed in the clinical setting of healthcare office or private clinics while controls were interviewed in other places; however, the interviewer was trained to use similar questions for both groups. The included cases were not representative of breast cancer cases in general since we recruited patients from hospitals or private clinics through convenience sampling method  and no random sampling was done in this regard.In conclusion, the findings of this study revealed a significant positive association between dietary GI and the odds of breast cancer. However, we observed no significant association between dietary GL and odds of breast cancer.