Four main themes emerged from thematic analysis: (1) dietary and lifestyle practices, (2) the effects of cancer on body weight, (3) the impact of cancer on psychology, and (4) the effect of the environment on body weight. Lack of information from healthcare professionals and lack of time were the main barriers to body weight management, whereas the main facilitators were support from their social environment, along with a comfortable physical environment, and the facility of technology. Participants suggested that an effective weight-loss lifestyle intervention should include psychological and social support, guidance and education, collaboration, flexible recommendations, personalised goals, and a follow-up plan. The needs of breast cancer survivors need to be considered when designing weight-loss lifestyle interventions. A personalised approach may prove more effective in promoting a healthy lifestyle and improving patients’ care.The present study aimed to identify the factors that prohibit or enable breast cancer survivors from adopting a healthy lifestyle, as well as to record patients’ suggestions towards developing a weight-loss lifestyle intervention. Twenty-three breast cancer survivors participated in four online, semi-structured focus groups in Greece. All discussions were video-recorded and transcribed verbatim. Participants were 50⋅5 ± 7⋅4 years old with a current mean BMI of 29⋅1 ± 3⋅4 kg/m Several patients with a diagnosis of breast cancer are overweight or obese, and all women are at risk of gaining up to 5 kg in post-cancer treatment. Weight gain is caused by a variety of factors, including stress-related eating, decreased activity, a lowered metabolic rate due to chemotherapy, and pre- and post-therapy medications. Weight gain is also more common in women undergoing treatment-related menopause and is frequently accompanied by changes in body composition. This population is prone to fat accumulation and muscle loss, a condition known as sarcopenic obesity.,4 This distinct pattern of weight gain combined with unfavourable changes in body composition is distressing for the majority of breast cancer survivors, poses a significant risk for the development of comorbid conditions, and may affect long-term disease-free survival.Weight gain is common among breast cancer survivors and has been linked to disease progression, recurrence, and mortality. Moreover, the World Cancer Research Fund (WCRF) recently published a guide for healthcare professionals on how to effectively support behavioural change. However, weight management lifestyle interventions for breast cancer survivors have not explicitly included tailored behavioural strategies in their protocols. Lifestyle interventions focusing on nutrition and physical activity changes have demonstrated effectiveness in weight loss and concomitant health benefits in several clinical trials in breast cancer survivors. As a result, more evidence-based nutrition and physical activity guidance following breast cancer treatment is required to help provide personalised interventions that enable survivors to adhere to the recommendations.Treating obesity in breast cancer survivors is associated with higher survival rates, lower risk of metastasis, and decreased risk of developing obesity-related comorbidities, such as type 2 diabetes and cardiovascular disease. Recommendations for cancer survivors highlight the importance of treating obesity by targeting energy balance-related behaviours , as this may support weight loss and weight control more effectively. The most recent guidelines for cancer survivors published by the American Cancer Society emphasise the importance of counselling in providing ongoing support for survivors’ behaviour changes. Barriers against adopting a healthy lifestyle and obtaining healthy weight status include individual , social , or environmental  factors. Although this information is essential to further understand the specific needs and preferences of breast cancer survivors, the current knowledge is limited. Understanding patients’ perspectives and identifying the determinants of lifestyle change and intervention delivery in breast cancer survivors is a significant step towards designing better education and communication tools to make weight loss more feasible. This may also lead to the overall development of effective, safe, well-tolerated, and equitable interventions to limit the obesity-related burden of breast cancer.Adopting a healthier dietary and physical active lifestyle with the aim to lose weight is difficult in breast cancer survivors since they face a number of challenges.The purpose of this study was to identify barriers and facilitators of breast cancer survivors for adopting a healthy lifestyle and record their suggestions for developing lifestyle interventions to treat overweight/obesity in this patient population.This study was performed according to the principles of the Declaration of Helsinki and European General Data Protection Rules (GDPR) and approved by the Bioethics Committee of the Department of Nutrition and Dietetics at the University of Thessaly (07/02.02.2022). All participants were informed for the purpose and objectives of the study, signed the informed consent and provided permission for video-recording. Subsequent to their participation in the focus groups, every participant received a complimentary 60-min dietary consultation with the researcher (MP), along with a personalised diet plan.2, and no active cancer therapy or ongoing treatment, except for hormonal or immune therapy, were eligible.Participants were recruited through non-profit cancer organisations via announcements on their websites and social media during March and April 2022. Female breast cancer survivors, all over Greece, between the ages of 18 and 65, with BMI ≥25 kg/mBreast cancer survivors were defined as women who have received a diagnosis of breast cancer and having completed overall treatment, including surgery, chemotherapy, radiotherapy, and other cancer treatments, excluding hormone or immune therapy.A voluntary response sampling technique was used, a process that breast cancer survivors who were interested in participating in the study were invited to contact MP, who provided details on the objectives and the procedures. Prior to their assignment to the study, an online meeting was conducted between MP and every potential participant to collect information about the medical history and socio-demographic data and address any queries regarding the procedures. The study ultimately included twenty-three of the twenty-seven eligible breast cancer survivors, with the rest dropping out due to other obligations. To reach data saturation, four focus groups were conducted, each with four to nine participants. Data saturation was reached when no new themes came up in the discussion in the fourth focus group. The term ‘data saturation’ refers to the moment that no new information is added anymore on top of the already existing information. It is derived from grounded theory but is frequently used in various qualitative research designs.All focus groups were conducted with the use of an online videoconferencing platform (ZOOM). The rapid development of telehealth during the COVID-19 era can be attributed to the imposed lockdowns. However, its widespread utilisation beyond the period of confinement can be attributed to its numerous advantages, such as its efficiency in terms of time and cost. It is worth noting that telehealth does have a few disadvantages as well, primarily related to technical difficulties, specifically limited access to technology and reliable internet connections. This method was preferred because the participants were living in different areas across Greece, thus a face-to-face meeting was not feasible. Focus groups were led by MP who was the moderator and supported by GS who acted as the co-moderator . The researchers were registered dietitians, MP with a master's in nutrition, and GS with an MD and a PhD in nutrition and cancer. Both of them had prior experience in interviews and qualitative research. The moderator introduced the focus groups by outlining the objectives. The focus groups were semi-structured and guided using a predetermined list of topics . The guiBasic socio-demographic and medical history data were collected, including age, weight, and height; educational status; region of residence; marital status; number of children; years of survivorship; type of breast cancer; medication; and exercise level. This method is commonly utilised in qualitative research and includes identifying, analysing, and reporting themes resulting from the data, following inductive coding. It is also considered a flexible and useful type of analysis suitable for use by non-experienced qualitative researchers.Qualitative data were analysed using the thematic analysis approach as described by Braun and Clark.Prior to coding and analysing the transcripts, MP read all of them to familiarise herself with broad themes of conversations and to facilitate early identification of patterns. Then, MP and GS conducted a line-by-line coding of two randomly selected transcripts. Initial codes were then generated through discussion until a coding framework was reached. The agreed codes were applied to all focus groups, with only minor modifications. Following that, codes were organised into themes, which were later reviewed, defined, and finalised into four themes. An Excel spreadsheet was used to manage and organise data to ensure clarity, avoid losing the content of conversations, and indicate a clear justification from coding to the finalised conclusion.Four main themes with sub-themes were identified: dietary and lifestyle practices; the effect of cancer on body weight; the impact of cancer on mental health; and the role of the environment .Table 22, and a lower mean BMI of 26⋅9 kg/m2 at the time of diagnosis, based on self-reported measurements.Participants’ demographic, anthropometric, and medical characteristics are shown in I know that I must consume foods from all food groups; I know it's bad, but I just love sweets. I lived on sweets’ P920.‘‘I am aware that “bad” nutrition is harmful; I am aware of this because I have read far too many articles’ P601.The majority of the participants stated that they acknowledged what ‘healthy’ or ‘unhealthy’ nutrition meant, as well as what foods to eat for a healthy lifestyle.Speaking personally, officially from my doctor, my oncologist, I never received any specific recommendation, any guidance, or anything’ P702.‘‘My doctor suggested I follow the Mediterranean diet, reduce red meat consumption, eat a lot of fruits and vegetables, choose no other oils except olive oil and avocado, and avoid processed foods. That's what he recommended’ P610.Most of the participants have never heard of or been informed about breast cancer survivors’ lifestyle recommendations, except for two who were told by their oncologist to adopt the Mediterranean diet, two others whose oncologist told them to watch their weight, and three more who consulted a dietitian by themselves or were informed by a non-profit breast cancer survivors organisation.deprivation’, ‘programme’, ‘restriction’, ‘desperation’, or ‘a painful story’ with only three participants believing that diet is a healthy way of eating.I have never linked obesity to cancer, but rather to other diseases like diabetes or heart disease’ P608.‘‘For me, obesity is definitely a disease. For me, it has a significant and direct impact on my mental health’ P919.‘A diet means deprivation for me; I will have to give up some of the things that I currently enjoy’ P203.Obesity and diet were considered negative concepts for the majority of participants. Their perceptions of obesity include its characterisation as a disease or bad health, with a link to cancer in general, comorbidities, and negative emotions. Additionally, diet was mainly described as ‘I may not have been obese; I was overweight, but I have always been concerned about diets, either with dieticians or on my own’ P812.‘Regarding their attitudes towards lifestyle, nutrition, and weight control, participants admitted that weight loss was often their objective before cancer diagnosis, which was achieved through healthy nutrition and lifestyle in general.Yes, I definitely want to lose weight. I don't prioritize health, maybe because my experience with cancer is more recent; I want it only for aesthetics and appearance’ P203.‘‘I just want to lose my extra body weight because I've read research that says extra body fat increases the chances of relapse, and I don't want to go through that again, or at least avoid it for a long time’ P610.‘That's enough. I think I must start over. I am a young woman; I can't feel so bad; everything hurts. We must survive’ P601.All participants wanted to change their lifestyle, and their motivations included being physically and mentally healthy, energetic, having overall wellness, improving their appearance, loving themselves, practicing self-care, avoiding recurrences, and being alive.I have a complaint: in my opinion, there should have been recommendations and support for women going through this’ P702.‘Group sessions have many advantages. It will not, however, be able to meet individual needs. So I prefer a mix of group and individual sessions because we don't all have the same needs, ailments, or experiences’ P1021.‘‘I think I should do it for the rest of my life. I’m overweight, and I have to fight it. I believe I will achieve this through maintaining contact’ P1022.‘I don’t want to deprive myself of that. We will fix the body, and we will destroy the psychology. I believe in everything in moderation’ P615.Based on their previous experiences, all participants expressed their needs in terms of body weight control. These unmet needs included emotional support, cooperation, education, flexibility in recommendations, individualised goals, demarcation but not deprivation, persistence in maintenance, and lifetime changes.A diet plan adapted to everyone's special needs; to be flexible, with some suggestions. I prefer the group session, where we can talk about what worries us, what obstacles we face, and what went well’ P702.‘‘For me, the ideal is a combination, because individual sessions may provide more targeted suggestions, but group sessions provide better communication and support. We all struggle together’ P1021.Moreover, participants had several expectations and suggestions about weight management programmes and interventions.After breast cancer treatments, my hormone profile changed, and I gained weight that I can't get rid off’ P514.‘‘I don't believe I gained weight solely because of the treatments, menopause, or diet. These reasons are not sufficient. It's our fault as well; perhaps we ate more; I ate more than I should have’ P615.All participants stated that they gained weight after completing their cancer treatments, except for one (P1022). The majority of them agreed that losing weight after cancer treatments was extremely difficult and that they needed to adjust to their new metabolism. Cancer treatments, drugs, hormone therapy, and menopause were the primary causes of their excess body weight, according to all breast cancer survivors. Some of the women were diagnosed at the beginning of menopause, and the premenopausal breast cancer survivors should undergo artificial menopause. In any case, the participants would have to deal with their cancer as well as menopause, which are both difficult conditions. Aside from menopause, some of the participants believed they gained weight as a result of their unhealthy lifestyle.I cut back on my dinner portion and no longer add sugar to my coffee. I also do Pilates twice a week and walk on a regular basis’ P304.‘‘I changed my lifestyle. I have a daily routine that I'm trying to stick to. Only through this program I was able to lose my excess body weight. I improved my diet and increased my physical activity; it was a huge and painful effort, but the final result was well worth it. I'm absolutely pleased’ P608.The majority of participants tried to manage their body weight after cancer treatments, thus altering their lifestyle, either through dietary changes, physical activity changes, or both. In very few cases, cancer or its treatments led to poorer dietary habits.Because of my stress, I ate more’ P610.‘‘To love myself and to take care of myself also helped me deal with cancer and its treatments’ P113.The emotional state of participants after completing cancer treatments was a major topic of discussion in all focus groups. It emerged that experiencing feelings such as stress, sadness, depression, and anger pushed the breast cancer survivors to engage in more unhealthy behaviours and become trapped in a vicious cycle of negative thoughts like disappointment, guilt, and being emotionally upset, reaction, denial, and/or exhaustion. Calmness and joy, on the other hand, led in some cases to self-care.I am unable to control my appetite because my hormone therapy has also had an emotional impact on me’ P702.‘The majority of breast cancer survivors believed that hormone therapy and anti-menstrual medications could have a negative impact on their emotional health as well as their body weight. Two women stated that after completing cancer treatments, they felt depressed and required antidepressant medication, which adversely affected their body weight.I don't feel psychologically well enough to stick to the diet prescribed by the dietitian’ P601.‘‘Diet is a psychological issue for me. When my mental wellbeing is strong, when I feel good, it helps me avoid eating unhealthy foods’ P920.All participants discussed the role of their mental wellbeing in changing their mindset. As a result, mental wellbeing appeared to be both a barrier and a facilitator of weight management. Additionally, weight control success appears to lead to psychological improvements in breast cancer survivors.I am bothered by my current image. I want my previous body image back. This is too intense for me’ P615.‘‘I'm angry that I've gotten to this point of being obese. I'm very angry. Why should I gain so much weight?’ P615.Body image and feelings about body changes were frequent topics of discussion among focus groups participants. Breast cancer survivors stated that changes in body image can strongly influence participants’ psychology and behaviours.They were extremely supportive. My husband in particular, but also my parents and the rest of the family. I couldn't do anything without them, especially my husband. 90 % of my effort was accounted for by his psychological support’ P316.‘‘I got divorced and gave up everything. Unfortunately, I had given up on myself’ P601.The family's role in weight loss was thoroughly discussed. It was helpful in some cases and hindering in others.The obstacle is that on the weekends I go out with friends, and I want to enjoy it, so I eat and drink without restriction’ P608.‘Aside from family, the social environment appeared to be important in weight management, either as a barrier or as a facilitator.No doctor deals with nutrition; no doctor tells you to change your way of life’ P113.‘Support from healthcare professionals was a major issue for breast cancer survivors. The focus groups revealed that participants expected information, education, recommendations, and support from their medical team, particularly their oncologist.When I locked myself up at home, I gained weight again’ P608.‘‘The nice weather helped me go for a walk’ P609.Natural environmental conditions have been found to influence participants’ weight loss efforts in a variety of ways. The coronavirus pandemic and impending confinements, as well as weather and home environments , all had an impact on outcomes, both positively and negatively.Technology does not bother me. Every one of us is incorporating online communication into our daily lives. So, the distance will not be an issue’ P1021.‘The vast majority of participants stated that they were familiar with digital technology or that it could be adapted. Most of them found technology a facilitator in their efforts to change their behaviours. Among other things, they could save time and eliminate distance by using digital media.I do too many things, I don't have enough time, I get tired, and I eat. The nibble is my way out’ P702.‘Finally, time management could either aid or inhibit participants’ efforts to change their lifestyle.This study explores breast cancer survivors’ beliefs, experiences, barriers, and facilitators about weight management and provides an in-depth perspective about their needs and expectations of a weight-loss intervention programme. According to the findings, the majority of the participants were not informed about the lifestyle changes they should make after cancer or about the recommendations of cancer survivors. Their main motivation for making lifestyle changes was to maintain their health. Most of them had struggled with weight control issues prior to cancer, and they had tried a variety of dietary patterns; resulting in their attitude towards diet being negative. They did not link breast cancer to their excess weight, but somehow they changed their dietary and physical activity habits after being diagnosed. All except one participant gained weight after cancer treatments, believing that it was primarily due to side effects of cancer medications and therapies, menopause, and/or post-cancer hormone therapy. A vicious cycle was observed in which post-cancer body changes affected body image, impacted psychological status, influenced dietary choices, and closed the cycle with an impact on body weight. Barriers like negative psychology, temptations, a lack of information, and a lack of time, as well as facilitators like positive psychology, support from family, medical team and social environment, good time management, and easier environmental and technological conditions, were identified. Lack of family support appeared to be an important determinant for the adoption of a healthy lifestyle among the participants. Finally, based on their previous experiences, breast cancer survivors expressed their needs and expectations of a weight-loss intervention programme that included psychological support, counselling and education from credible healthcare professionals, collaboration among specialists, recommendations that can be adjusted to their needs, avoidance of restrictions, individually tailored goals, and a long-term weight maintenance plan.,14 These findings were confirmed by similar studies in Ireland, Malaysia, and China.–17 Reviews of qualitative studies reported ineffective dietary guidance and limited weight control follow-up from healthcare professionals.–21 All these studies also highlighted the critical role of health professionals in monitoring weight, providing advice, and referring to a multidisciplinary team. The contradictory messages in dietary advice and weight management following cancer have also been noted.,22 This lack of communication with healthcare professionals could be linked to a lack of willingness among breast cancer survivors to adopt healthier lifestyles. It has been shown that a healthcare professional’s recommendation to exercise significantly improves physical activity engagement and weight management.The absence of information about post-cancer lifestyle recommendations observed in this study is an issue that systematically appears throughout the survivorship care trajectory. According to an Australian study on weight management after breast cancer, 79⋅79 % of women reported not receiving any advice about weight loss or weight gain prevention at the time of diagnosis, and researchers declared significant information gaps regarding weight management in this population.,15,19 Our study showed that participants’ key motivators for change was maintaining physical and mental health, along with improving their appearance. Previous studies have also identified healthy eating to prevent recurrences as a motivator.,17 The increase in aesthetic evaluation to improve self-acceptance was a primary motivation for breast cancer survivors to participate in a behavioural intervention. The same study found numerous other motivations, including participants’ physical and mental health, coping with the illness, and sharing their experiences. Motivations should also be enhanced because they facilitate intervention adherence. For this purpose, motivational interviewing may be useful in behavioural interventions. This behaviour change technique is effective in determining and exploring motivations, overcoming hesitation, and reinforcing behaviour change.The identification and reinforcement of motivations are critical for achieving behavioural changes. Several studies have revealed that a lack of motivation is a significant impediment to adopting new lifestyle habits.,19 Female cancer survivors held ambivalent beliefs about the relationship between body weight, dietary intake, and physical activity to their cancer diagnosis and potential recurrence. Personal beliefs and preferences regarding diet–cancer relationships have been described as a risk factor for post-treatment dietary information needs.The willingness to change an individual's lifestyle is greatly influenced by personal beliefs, attitudes, and thoughts about diet, body weight, and their connections to cancer. Most of the participants in this study had negative attitudes towards diet as a result of pre-cancer restrictive dietary practices, and they did not correlate their diagnosis with their excess body weight, which could be a barrier to behavioural modifications. Earlier studies indicate that the most frequently mentioned personal perceptions as impediments to lifestyle change are beliefs that cancer is unrelated to lifestyle and uncertainty about the benefits of lifestyle in relation to cancer and health. Many other studies have confirmed weight gain from treatments and premature menopause after breast cancer diagnosis.,22,26 Cancer-induced menopause is a major contributor to weight gain following breast cancer.,27,28 Other causes of weight gain have been identified, including ‘stress eating’, decreased physical activity, chemotherapy-induced lower metabolic rate, and cancer medication use. Evidence from the Women’s Healthy Eating and Living (WHEL) study reported that chemotherapy was significantly associated with weight gain, but hormone therapy (Tamoxifen) was not. More specifically, women who received chemotherapy were 65 % more likely to have gained significant weight than women who did not receive either chemotherapy or hormone therapy. Many women attribute their weight gain to hormonal therapies such as Tamoxifen. Tamoxifen may exacerbate the body composition changes that occur with the onset of menopause.All but one participant in this study admitted to gaining weight after being diagnosed with cancer. The only participant who lost weight had morbid obesity, and her doctors advised her to lose weight as a part of her cancer treatment. An Australian study found that 64 % of participants gained weight overall after diagnosis, with an average weight gain of 9⋅1 kg. The overall sense of bodily self, including body image, could be damaged after diagnosis and treatments. According to emerging evidence, negative body- and weight-related emotions are important and often overlooked predictors of psychological health. In particular, shame and guilt have been identified as important body-related emotions in individuals struggling with weight and may be pertinent relevant in the experience of breast cancer. A recent meta-synthesis about body image experiences of women with breast cancer concluded that women’s body image and its psychological implications should be considered a process in constant development. For these reasons, strategies to ameliorate these negative feelings are essential for women with breast cancer. Physical activity may be one of them, as they promote positive body image, emotional regulation, cognitive development, and individual self-esteem. The grounded theory of body image for women diagnosed with breast cancer should be taken into consideration as it illustrates intrapersonal and interpersonal factors and strategies to manage their body image.The psychological impact of cancer on participants’ body weight was discussed thoroughly, and weight cycling was observed as a vicious cycle of negative emotions, impacted body image and weight gain. In other words, this could be the vicious cycle of emotional hunger. As mentioned previously, in the current study, participants’ impaired body image triggered emotions such as stress, sadness, depression, and anger, which drove them to engage in unhealthy behaviours, which trapped them in disappointment, guilt, emotional upset, and other negative thoughts, leading them to more unhealthy behaviours. Breast cancer survivors suffer from severe psychological distress after gaining post-treatment weight. In the previous study, only 4⋅3 % of breast cancer survivors thought a breast cancer-specific programme would be beneficial. A more recent study by Ee et al. included specific advice from healthcare professionals, environmental restructuring , motivations (creating an expectation of looking and feeling better), persuasion (aiming to prevent recurrence), and providing women with specific knowledge and skills as major enablers in adopting optimal lifestyle behaviours and weight management. Another study identified the lack of individualisation, lack of time, and lack of support as important barriers, but knowledge on food preparation and recipes, goal setting, a stable routine, and support from friends and family as facilitators for diet interventions. The lack of information or advice from healthcare professionals, the lack of time, and the role of family, and social support in weight management have been thoroughly explored by many other studies in breast cancer survivors.,22,34,35This study identified the main obstacles in managing weight after breast cancer, which included negative mental wellbeing, temptations, a lack of information, and a lack of time, as well as the main enablers, which included positive psychology, support from the family, the medical team and the social environment, good time management, and more conductive environmental and technological conditions. Only a few previous studies have explored barriers and facilitators of weight management in breast cancer survivors. An Australian study recorded fatigue among weight loss barriers and identified a structured exercise programme, a prescribed diet, accountability to someone else, and social support among the facilitators. Face-to-face communication, online and telephone support, printed materials, and different specialists to share care in the primary healthcare setting were among the preferences of cancer survivors for the delivery of dietary information after treatment. On the other hand, group interactions facilitate strategic skills and encourage self-reflection and potential change, thus may be beneficial to share feelings and experiences with others who have experienced a similar position. According to a survey of 122 breast cancer survivors, the respondents indicated that they preferred virtual platforms to in-person meetings (68⋅9–21⋅3 %), due to better time management. The use of technology could facilitate the participation in weight-loss intervention programmes.Finally, participants discussed their needs and expectations for a weight-loss intervention programme. Breast cancer survivors stated that psychological support, guidance, and education from reputable healthcare professionals, collaboration among specialists, flexibility in recommendations, avoiding restrictions, individually tailored gradual goals, and a long-term weight maintenance plan could help them control their weight more successfully. These findings are in accordance with a scoping review, where cancer survivors preferred specific recommendations, direct interaction with the medical team, and peer support from other cancer survivors.The findings of the present study should be considered under the light of its strengths and limitations. To our knowledge, this is the first study to investigate the needs and perceptions of breast cancer survivors prior to a weight-loss lifestyle intervention in Greece. Focus groups were conducted by an online videoconferencing platform, which has the advantages of convenience, time efficiency, and cost-effectiveness, while also facilitated the participation of individuals residing in geographically distant areas. However, it is important to acknowledge that this approach has certain limitations, including technical difficulties and the potential for a partial loss of non-verbal information, particularly body language rather than facial expressions. Additionally, sampling and selection bias may have occurred. Subjects were recruited through self-selection via announcements on cancer non-profit organisations’ websites and social media, and those who were well-educated, most keen on digital technology, most motivated, and most interested in nutrition and health were more likely to participate. All data, including body weight and height measurements, were self-reported, making it vulnerable to recall bias and socially desirable answers. Finally, no qualitative data analysis software was used, and thus, researcher bias may have emerged, despite the fact that the qualitative analysis was closely monitored by two authors (MP and GS).This study identified barriers and facilitators, and it also revealed unmet weight management needs among breast cancer survivors in Greece. The impact of psychology on weight control was assessed. The main barriers were a lack of information, time, and family support while the main facilitators were support from family, friends, and healthcare professionals, as well as easier environmental and technological conditions. According to participants, a weight-loss lifestyle intervention would have been more effective if it included psychological and social support; counselling and education from credible healthcare professionals; specialists’ collaboration; flexibility in recommendations; avoidance of restrictions; personalised, gradual goals; and a long-term weight maintenance plan. Identifying the unmet needs of breast cancer survivors could be supportive to healthcare professionals to design more effective weight-loss lifestyle interventions for breast cancer survivors.


The aim of this study is to determine the proportion of women unaware of family history of cancer among female relatives and associated socio-demographic characteristics.Results: the proportion of women unaware if any relative had cancer was 33%, and was significantly higher among controls (43.2%) compared to 23.9% among cases (p<0.001) (Adjusted Odds Ratio (OR) = 2.51, 95% CI = 2.14 - 2.95). Age, education and marital status remained significantly associated with being unaware of FH among controls on multiple regression.using case-control data on breast cancer among 4294 women in Nigeria, Uganda and Cameroon, we investigated the proportion of women unaware of family history of cancer among their female relatives. The association between participants' response to their awareness of female relatives' cancer history and socio-demographic characteristics was analysed according to case-control status, family side and distance of relation. about a third of women interviewed did not know about cancer history in at least one of their female relatives. Efforts aimed at improving cancer awareness in sub-Saharan Africa (SSA) are needed. Our findings could be useful for future studies of cancer risk assessment in SSA. Family history (FH) is an important tool in clinical practice with utility in the diagnosis and management of single-gene disorders and chronic diseases. It also plays an important role in public health as a tool for risk assessment, decision-making about tailored interventions, and as a motivation for behaviour change . In the The accuracy of family history reports has been the focus of several investigations with varying reports about accuracy -7. AdditAlthough a small proportion of breast cancer is hereditary (about 5-10%), life-saving interventions now exist for individuals with hereditary breast cancer and their relatives. The risk of breast cancer is about 2 times higher for women with one affected first-degree female relative and 3-4 times higher for women with more than one first-degree relative compared to women without a family history . The mosWhile the management of familial breast cancer is well established in the developed world, with the availability of cancer risk clinics for the evaluation of breast cancer patients and their families, the situation is different in developing countries where these services are not available in most health institutions. Moreover, in the SSA region, breast cancer is disproportionately of the aggressive triple-negative type with late presentation and poor prognosis. Additionally, we have recently reported a high prevalence of deleterious BRCA mutations among Nigerian women ,19, suppStudy design: data for this study was obtained from the African Breast Cancer Study (ABCS), a case-control study of the risk factors for breast cancer in Nigeria, Cameroon, and Uganda. The study protocol was reviewed by the institutional review boards of the three sites and the University of Chicago Biological Sciences Division Institutional Review Board (13304B and 10-023-B), University of Ibadan/University College Hospital Ethics Committee (UI/IRC/02/0003), Cameroon National Ethics Committee (N141/CNE/SE/2010), and Makerere University College of Health Sciences Ethics Committee (2011-023). Details of the study methods are provided in previous publications [ications .Participants: briefly, women aged 18 years and above with breast cancer and age-matched controls without breast cancer in Nigeria (since 1999) and in Uganda and Cameroon (since 2005) were recruited from tertiary hospitals in the three countries. Cases were defined as females who were 18 years or older, black of African descent, capable of providing informed consent, and had a histologic or clinical diagnosis of invasive breast cancer while controls were those of the same age criteria, without breast cancer, and able to give informed consent.Data sources: face-to-face interviews were conducted to obtain data on socio-demographic characteristics and lifestyle variables, anthropometric characteristics, previous treatments for breast conditions, and family history of cancer. We investigated the proportion of women unaware of family history of cancer among their female relatives . Data on the response to the question about a family history of cancer among female relatives was analysed as the dependent variable. The proportion of participants that responded ‘don't know’ to any of the female relatives was determined and analysed according to case-control status, family side (father- or mother-side), and distance of relation.Statistical methods: Generalized Estimating Equations (GEE) with the logistic regression option were used to compare the odds of reporting don't know responses for female relatives, adjusting for socio-demographic characteristics. Multiple logistic regression analysis was used to determine socio-demographic factors associated with ‘don't know’ response for any of the female relatives.Of 4294 women, there were 2271 cases and 2023 controls; 450 were studied in Uganda (231 cases and 219 controls), 570 in Cameroon (297 cases and 273 controls), and 3335 in Nigeria (1743 cases and 1531 controls). The mean age of cases was 48.5 years (SD = 11.9) compared to 44.4 years (SD = 13.0) for controls. About a third of women interviewed in a breast cancer case-control study setting in three African countries did not know about cancer history in at least one of their female relatives. The focus of this study is different from many others that examined the accuracy of family history reports by comparing them with gold standards such as disease registers -7. RatheSignificant differences were found between cases and controls in the rates of DK responses with an odds ratio over twice as high among controls compared to cases. The finding could be due to women with breast cancer more willing to answer questions asked in the hospital setting, as they could perceive that providing such information could influence their care. Family history taken during the evaluation of relatives of cancer patients in a cancer-risk clinic setting may be quite different from that in a case-control study, our study setting. The higher DK proportions among controls suggests that cancer-free individuals, including relatives of cancer patients, may need a more vigorous approach in obtaining FH, and interventional studies are required to investigate the efficacy of multiple approaches to obtaining FH. Studies are also needed among relatives of cancer patients that will investigate the rate and accuracy of reporting of cancer FH. Previous studies have shown that educational and motivational messages  or the uAnother explanation for the difference in DK responses between cases and controls is the fact that some of the interviews were conducted at home while others were in the hospital, and the possibility of obtaining information from available family members in a more relaxed atmosphere could improve the quality of the report. On the other hand, more accurate recollection could be possible in the hospital setting as discussed above. It is worthy of note that the lower DK rates among cases do not necessarily imply correct responses for ‘Yes’ and ‘No’ but at least suggest that they make the effort to provide more information. In this study, the DK responses were more likely in Uganda compared to Cameroon and Nigeria, among both cases and controls. We also found differences in DK responses about cancer family history by ethnicity. In Nigeria, Ibos and other ethnic groups compared to Yoruba, and Cameroonian Semi-Bantous compared to Bantous were less aware of cancer family history. The differences found by ethnicity suggest there are possible cultural influences in the level of attention paid to family cancer history in these populations. For example, the Ibos in Nigeria are a more mobile group and could have lower family connectedness, and that could explain their higher DK rates. Future studies using qualitative designs would provide greater insights into the level of awareness of family history of cancer or other common diseases. Previous studies have alluded to the strong cultural influences on responses about FH such as cancer stigmatization or desire to protect relatives .The finding that controls in the oldest age group were more likely to report DK is surprising given that older people should be more familiar with relatives' histories, having been around for a longer period. A similar study about DK responses to a FH of diabetes and heart disease conducted among an underserved minority Mexican population in the United States also found lower, though non-significant levels of unawareness of FH of these diseases among younger people . The higAmong controls in Nigeria and overall, educated women more commonly gave 'don't know' responses to questions about cancer family history compared to women with primary or no formal education. Among cases, however, the reverse was the case, though only significant in the total sample. The reason for the difference in association between cases and controls is unclear and deserves further study. The limitations of this study include the fact that DK responses may not directly translate to inaccurate responses, and studies of cancer FH accuracy would require study designs that verify FH reports using cancer registry data. However, the findings from this study give some insight into the degree of awareness or interest in cancer FH among native SSA women. Secondly, the controls in this study may not be representative of relatives of cancer patients that constitute the population from which most information about cancer family history would be required for cancer prevention efforts, for example in the cancer risk clinic setting. Additionally, as alluded to earlier, it is also possible that responses from participants with a family history of cancer may be systematically different from those without such history, and studies focusing on relatives of those with breast cancer are advocated. Another limitation is the absence of detailed data on responses to cancer history in male relatives, hence we could not study the rates of awareness of cancer history and compare with our findings for responses about female relatives. In spite of these limitations, we have reported on responses related to family history from a large multi-country SSA sample, and our findings could be useful for future studies of cancer risk assessment in SSA.Funding: This project was supported by Susan G. Komen for the Cure (SAC110026 to O.I. Olopade), NIH Commons Credits Pilot Award (CCREQ-00079 to O.I. Olopade), Breast Cancer Research Foundation , and .About a third of women interviewed in three SSA countries did not know about cancer history in at least one of their female relatives. Future studies need to investigate the accuracy of reports of cancer FH, though this could be difficult in the SSA setting where cancer records are incomplete or could be totally absent. The incorporation of precision medicine in patient care in low-resource settings such as SSA may take some more years due to prohibitive costs and a lack of trained personnel. However, a cheap and readily available temporary alternative could be the use of family history data to plan preventive interventions. These findings underscore the need for studies about obtaining family history information in hospital and population settings in sub-Saharan Africa. Research should also investigate health workers as studies have shown only modest knowledge of FH information among medical personnel . In addiThe management of familial breast cancer is well established in the developed world unlike in most sub-Saharan African countries;The use of accurate family history information could serve as a cheap strategy for comprehensive cancer risk assessment in sub-Saharan Africa.A third of women did not know about cancer history in their female relatives;Being unaware of cancer family history was more common among breast cancer cases compared to controls;Age and education were associated with being unaware of cancer family history.


Statins are the most widely prescribed cholesterol lowering medications and have been associated with both improved and unchanged breast cancer outcomes in previous studies. This study examines the association between the post-diagnostic use of statins and breast cancer outcomes (death and recurrence) in a large, representative sample of New Zealand (NZ) women with breast cancer.Women diagnosed with a first primary breast cancer between 2007 and 2016 were identified from four population-based regional NZ breast cancer registries and linked to national pharmaceutical data, hospital discharges, and death records. Cox proportional hazard models were used to estimate the hazard of breast cancer-specific death (BCD) associated with any post-diagnostic statin use.Of the 14,976 women included in analyses, 27% used a statin after diagnosis and the median follow up time was 4.51 years. Statin use (vs non-use) was associated with a statistically significant decreased risk of BCD . The association was attenuated when considering a subgroup of ‘new’ statin users , however other analyses revealed that the protective effect of statins was more pronounced in estrogen receptor positive patients , postmenopausal women , and in women with advanced stage disease .In this study, statin use was associated with a statistically significant decreased risk of breast cancer death, with subgroup analyses revealing a more protective effect in ER+ patients, postmenopausal women, and in women with advanced stage disease. Further research is warranted to determine if these associations are replicated in other clinical settings.The online version contains supplementary material available at 10.1007/s10549-022-06815-w. Breast cancer is the most common cancer in women and the leading cause of female cancer mortality worldwide . ComorbiStatins reduce cholesterol levels by inhibiting the rate limiting enzyme of the mevalonate pathway (HMGCR), which has been shown to be over expressed in breast cancer tumours , 9. StatThere is conflicting evidence on the potential protective effect of statins with respect to the molecular subtype of breast cancer. Some studies indicate that statins exhibit a more protective effect in ER+ tumours , 45–47, n = 14) or if their date of death was on or before their recorded date of breast cancer diagnosis (n = 3). The final cohort for analyses was comprised of 14,976 women.Eligible women were all those with a first primary breast cancer diagnosed and recorded in any of four population-based regional breast cancer registries   in New ZIn the PHARMS database, medications dispensed any time after breast cancer diagnosis were determined using the therapeutic group ID, a PHARMAC identifier for each group of Anatomical, Therapeutic, and Chemical properties . All staDeaths were determined from the underlying cause of death in the regional breast cancer registries and National Mortality Collection, with ICD codes C50.0 to C50.9 classified as deaths from breast cancer.Demographic and clinical information came from the regional breast cancer registries, and covariates considered included date of diagnosis, age, ethnic group , 64, socComparisons by statin use at baseline (date of diagnosis of breast cancer) were conducted using the chi-square test. We used Cox proportional hazard models to assess hazard ratios (HRs) of breast cancer-specific mortality associated with any post-diagnostic statin use vs non-use. Death registrations and Pharmaceutical Collection coverage were complete to the end of 2017, so we followed patients from their breast cancer diagnosis until death or 31 December 2017. Women with no death recorded prior to 31 December 2017 were assumed to be alive as at 31 December 2017. Medication use was conceptualised as a time varying covariate , such that time before the first dispensing was counted as ‘nonuser’ time, and time from the first dispensing to end of follow up was counted as ‘user’ time . Models Analyses were conducted considering statin use as a binary variable (user/nonuser), and also by splitting statin use into seven categories based on the number of daily defined doses . Dose analyses were conducted using a time varying approach, such that women spent time in the lowest category before moving into the next dose category.As dispensings towards the end of life may reflect changes in morbidity (including cancer recurrence/progression) or in health care related to end of life care , 72, we To evaluate the effect of the competing risk of death from other causes, the proportional subhazards model was also used . For thiWe stratified the main analysis by estrogen receptor (ER) status to explore the relationship between statin use and tumours expressing different ER profiles (ER+ vs ER−). We also stratified the main analysis by triple negative status . In all of these analyses, patients with an ‘unknown’ ER, PR, or HER2 status were excluded where appropriate.To investigate the effect of statin use in a more homogenous group and one in which the mechanisms of estrogen production   patients. In these analyses, patients with an ‘unknown’ stage were excluded. In order to address the selection bias inherent in analysing both incident and prevalent users together –80, an aIn order to compare statin users to patients using a different medication for a similar indication, a further analysis was carried out comparing statin users to statin nonusers who were dispensed aspirin. In this analysis, statin nonusers who used aspirin were followed from their first post-diagnostic aspirin dispensing until death or 31 December 2017.We also conducted an analysis with breast cancer recurrence (BCR) as the outcome. In this analysis, we defined a BCR as either a local/regional recurrence or distant metastasis and restricted the cohort to patients with early-stage breast cancer as above. Recurrences were determined from the breast cancer registry data through patient’s routine clinical records, and women were followed from their breast cancer diagnosis until BCR, death, last follow up date, or end of Pharmaceutical Collection coverage (31 December 2017), whichever came first. These analyses examined risk of BCR associated with statin use vs non-use, and the same analyses were also carried out separately for local and distant recurrences.Finally, we also conducted an analysis with all-cause mortality as the outcome. In this analysis, women were followed from their breast cancer diagnosis until death or 31 December 2017. Women with no death recorded prior to 31 December 2017 were assumed to be alive as at 31 December 2017.Comparisons by statin use at baseline (date of diagnosis of breast cancer) were conducted using the chi-square test. We used Cox proportional hazard models to assess hazard ratios (HRs) of breast cancer-specific mortality associated with any post-diagnostic statin use vs non-use. Death registrations and Pharmaceutical Collection coverage were complete to the end of 2017, so we followed patients from their breast cancer diagnosis until death or 31 December 2017. Women with no death recorded prior to 31 December 2017 were assumed to be alive as at 31 December 2017.Results are reported as HRs and their 95% confidence intervals (CIs), with the two-sided significance level set at 0.05. Statistical analyses were conducted in STATA 17.0 .p < 0.05 for all differences).Median follow up for our cohort of 14,976 women was 4.51 years (range 0.01–10.99 years), with 1,341 dying of breast cancer, and 884 dying from other causes. Of these 14,976 women, 27% were dispensed a statin after diagnosis . This decreased risk was further reduced after adjustment for demographic and breast cancer clinical factors , and reduced again with further adjustment for other medication use and comorbidities, with the fully adjusted model indicating a statistically significant 26% reduction in BCD associated with statin use vs non-use . In exploratory analysis in which we additionally adjusted for chemotherapy and radiotherapy (both as binary yes/no variables and including both neoadjuvant and adjuvant therapies), the HR was not attenuated . Lagging statin use by various lengths of time did not substantially alter the HR. A similar finding was noted when adjusting for the competing risk of death from other causes . When adjusting for demographic variables, clinical variables, comorbidities, and other medication use in four steps, it was found that demographic variables were the strongest confounders of the association (Supplementary Table 1).We compared the risk of BCD associated with statin use (vs non-use) after diagnosis Table . In the In the dose analysis, the highest HR was observed during the initial 0–3 months of statin use , statin use was associated with a statistically significant decreased risk of dying from any cause .There was a statistically significant decreased risk between any statin use after breast cancer diagnosis and BCD in this large New Zealand population-based cohort study of patients with breast cancer after adjustment for demographic and clinical factors, comorbidities, and other medication use. There were suggestions of effect modification across subgroups, in that statins were more protective for ER+ cancers, in postmenopausal women, in late-stage patients, as well as in ‘prevalent’ statin users.Our primary finding is consistent with a number of previous studies indicating a statistically significant protective effect between statin use and BCD in their fully adjusted analyses –22. For In the dosing analysis Table , the risStatins were more protective in ER+ cancers  than in ER- cancers   patients , but no effect in early stage  patients   than in ‘new’ users . This result is in line with what we would expect, in that prevalent users are likely to have tolerated the medication well and are also likely to have a higher propensity for health seeking behaviours  than statin initiators . AlthougThe primary strength of our study is that we had a large cohort of patients with breast cancer followed up over a relatively long time period sourced from four population-based databases. The databases have been checked against the National Cancer Registry and found to be at least 99% complete, and the registry data we used contains more comprehensive and accurate information than the national data sources –90. Our Our study also has limitations. We did not have access to primary care data, which meant that our comorbidity data was restricted to hospital admissions in the relevant timeframe. Furthermore, this limited access to a range of potential confounders such as body mass index, alcohol intake, and smoking status, all of which would generally be available through general practitioner records. However, these limitations in residual confounders were somewhat mitigated by the use of a more balanced comparison group. Serum cholesterol levels were also not available in our data, which would likely induce confounding by indication as cholesterol has been associated with both the risk and prognosis of breast cancer . Over niIn conclusion, we found a statistically significant protective effect between post-diagnostic statin use and BCD in this large population-based study on NZ patients with breast cancer. The protective effect of statins was attenuated when considering ‘new’ users as the exposure, but there was a more protective effect found in ER+ patients, postmenopausal women, and in women with advanced stage disease. Further research is warranted in these subgroups to ascertain a targeted population of breast cancer patients that may benefit from statin therapy in the adjuvant setting.Supplementary file1 (DOCX 24 KB)Below is the link to the electronic supplementary material.


The cancer incidence among adolescents and young adults (AYAs) has significantly increased in recent years, but there is limited information about the factors that influence the perceived cancer risk among AYAs. A cross-sectional, web-based survey of 281 physically active Black and White AYA women was administered to assess the influences of demographic characteristics, family history of cancer, cancer risk factor knowledge, and lifestyle-related risk and protective behaviors on perceived cancer risk. Linear regression analyses were performed in SAS version 9.4. Self-reported Black race  and routine doctor visits  were related to a lower perceived cancer risk. Family history of cancer , cancer risk factor knowledge , and current smoking status  were related to a higher perceived cancer risk. Perceptions of cancer risk varied among this sample of physically active, AYA women. Lower perceptions of cancer risk among Black AYA women demonstrate a need for culturally tailored cancer educational information that presents objective data on lifetime cancer risk. Reportedly higher perceptions of cancer risk among AYA smokers presents an ideal opportunity to promote smoking cessation interventions. Future interventions to address cancer risk perception profiles among physically active, AYA women should tailor approaches that are inclusive of these unique characteristics. Cancer remains the second leading cause of death among both men and women in the US, as approximately 1.9 million new cancer cases and approximately 610,000 cancer deaths were projected to occur in 2022 .In contrast to non-AYA populations, AYA women are more likely to be diagnosed with cancer than AYA men ,5. The mApproximately 13,000 AYA women are diagnosed with breast cancer annually , and AYATo improve our understanding of AYA breast cancer across the cancer control continuum, researchers must work to better understand unique health profiles of AYA women. Currently, women at elevated risk include those who engage in risky health behaviors, like limited physical activity, or those with a genetic predisposition. Previous studies have suggested better implementation of multidisciplinary care models to address psychosocial and cancer-related needs across the cancer continuum ,10. NotaIn the present analysis, we ascertained the influences of demographic characteristics, family history of cancer, cancer risk factor knowledge, and engagement in cancer-related risk and protective behaviors on perceived cancer risk among physically active, AYA Black and White women aged 18 to 39 years. Perceived risk is a subjective psychological phenomenon that describes an individual’s susceptibility to disease and probability to benefit from interventions ,12,13. TFollowing participation in a larger study, physically active AYA women were invited to complete an exploratory, web-based survey to identify cancer-related risk and protective behaviors and personal perceptions about cancer risk given their unique social and health profile between January and April 2019. Additional information regarding the study design has been previously described ,15. Brie2 = 0.15), 0.05 significance level (α = 0.05), an estimated 15 predictors, and an achieved sample size of n = 281 participants. Based on these input parameters, it was determined that the 80% power estimate was exceeded.For this secondary data analysis, we conducted a post-hoc power calculation utilizing specific input parameters since multiple regression analyses were the selected method for this study ,17. PoweThe inclusion criteria were 18 to 39 years of age, self-reported female sex at birth, self-reported participation in at least one recreational sporting event on average per month, and self-reported racial identity as Black or White. Recreational sports provide an opportunity for young adults to increase their engagement in physical activity alongside fostering social interactions in a seemingly supportive environment. Along with self-reported participation in at least one recreational sporting event per month, women were also asked to report the number of days they engaged in physical activity of at least moderate intensity, which was defined as brisk walking, bicycling at a regular pace, swimming at a regular pace, and heavy gardening in the questionnaire. Together, these criteria were selected to capture a uniquely, physically active population. Furthermore, we only included participants engaging in at least one recreational sporting event per month as AYAs are a highly transient population that are often concerned with short-term disease risk management rather than long-term chronic disease risk management. Future partnership with recreational sporting organizations to promote healthy behaviors and chronic disease prevention may provide the best opportunity to leverage existing healthy behaviors  among this unique subgroup of the population.n = 147) or Black (n = 134).Lastly, participants with a previous cancer diagnosis were excluded from the study under the presumption that they would have a higher perception of cancer risk, were abiding by healthcare recommendations, such as consistent screening and follow-up cancer care treatment. Missing values for covariates of interest were removed from the sample. Therefore, we limited our analysis to 281 physically active AYA women who self-identified as White , self-reported access to healthcare information , self-reported family history of cancer, cancer risk factor knowledge score, and self-reported lifestyle behaviors .Demographics. Age was treated as a continuous variable with normal distribution. The level of education was ordinal and categorized into six groups, namely (1) high school graduate, (2) some college, (3) two-year degree, (4) four-year degree, (5) professional or graduate degree, and (6) doctorate degree. Employment was dichotomized to represent part-time or full-time working status versus otherwise . The income level was treated as ordinal and classified in increments of $10,000 up to $100,000 followed by the remaining categories: $100,000–$149,999, more than $150,000, and prefer not to answer. The current marital status was dichotomized to represent not being married  versus otherwise.Access to Healthcare Information. Three healthcare access-related variables were dichotomized. A routine visit denoted a participant that self-reported attendance at a healthcare visit within the past two years versus otherwise . Self-reFamily History of Cancer. Family history was dichotomized to represent any self-reported first-degree or second-degree family member with a past cancer diagnosis versus otherwise.Cancer Risk Factor Knowledge. Items on the survey assessing knowledge of cancer-related risk behaviors were adapted from a previous study . The 12 Lifestyle Behaviors. Fruit consumption was dichotomized to represent compliance with the recommended daily fruit intake of two cups versus otherwise . SimilarThe perceived cancer risk was the primary outcome of interest for this study. Items comprising a perceived cancer risk scale were adopted from the Health Information National Trends Survey (HINTS) . HINTS iFor the first item, response options included a five-point Likert-type scale: “extremely likely” and “somewhat likely” were coded as high (2 points) perceived cancer risk; “neither likely nor unlikely” was coded as moderate (1 point) perceived cancer risk; and “somewhat unlikely” and “extremely unlikely” were coded as low (0 points) perceived cancer risk. Response options were on a four-point Likert-type scale for the second item and included high, moderate, and low/no perceived cancer risk. The last item included response options on a seven-point Likert-type scale where “much higher” and “moderately higher” corresponded to a high perceived cancer risk (2 points); “slightly higher”, “about the same”, and “slightly lower” corresponded to a moderate perceived cancer risk (1 point); and “moderately lower” and “much lower” corresponded to a low perceived cancer risk (0 points).The perceived cancer risk score was treated as a continuous variable with normal distribution and a higher value representing a higher perceived risk of developing cancer. A sum scale variable on a scale of 0 to 6 points was computed for linear regression analyses.t tests and ANOVA for categorical variables and pairwise correlation coefficients for continuous variables. Using linear regression, we estimated the associations between modifiable and non-modifiable independent predictors of perceived cancer risk score. Our model was adjusted for the following a priori selected covariates: age, race, education, employment, family history of cancer, routine doctor visit, healthcare coverage, healthcare provider, cancer risk factor knowledge, fruit and vegetable consumption, physical activity engagement, and current combustible cigarette and e-cigarette smoking status [Descriptive statistics, such as the frequencies and percentages for categorical variables and means (M) and standard deviations (SD) for continuous variables, were computed. Demographic and social characteristics of participants were summarized in total, and differences between the two racial groups were examined using g status ,27,28,29n = 134, 47.7%) and White  women. Most women were employed (59.4%) and not currently married (73.3%). The largest proportion of the sample received at least a 4-year degree and had an income level less than $50,000. Half of the sample (50.2%) did not have a family history of cancer, and the average cancer risk factor knowledge score was 7.9 out of a possible 12 points. In terms of access to healthcare services, most women self-reported having a routine checkup within the past two years (84.0%), health insurance (91.3%), and sought care from a healthcare provider (87.7%). Most participants were self-reported binge drinkers (81.1%) but did not engage in combustible cigarette (81.9%) or e-cigarette (86.8%) use. Most of the sample did not meet the daily fruit (83.2%) and vegetable (90.8%) intake recommendations. More than half of participants self-reported engagement in physical activity for at least four days of the week (52.5%); nearly 60% of participants reported engagement in individual sport activities, such as running, walking, and cycling.The characteristics of the study sample and their respective perceived cancer risk scores are provided in p < 0.05). Participants without a family history of cancer  also reported a lower perceived cancer risk score compared to participants with a family history of cancer . Participants who did not routinely attend a doctor’s appointment  had a higher perceived cancer risk score compared to participants who did attend a doctor’s appointment within the past two years . Current combustible cigarette smokers  also had a higher perceived cancer risk score compared to current non-combustible cigarette smokers .Significant differences in perceived risk scores were observed for self-reported race, cancer risk factor knowledge, family history of cancer, routine doctor visit, and current combustible cigarette smoking status . Black wSelf-reported race, family history of cancer, routine doctor visit, cancer risk factor knowledge, and current combustible cigarette smoking status were associated with perceived cancer risk score differences. The β-values presented in Our study corroborates known differences in perceived cancer risk by self-reported race, family history of cancer, routine doctor visit status, cancer risk factor knowledge, and cigarette smoking status, but extends this knowledge to a new focus on an understudied AYA population of physically active women aged 18–39 years ,32,33,34Breast cancer is the most diagnosed cancer subtype among AYA populations, and greater consideration for cancer education and behavioral interventions that address both modifiable and non-modifiable risk factors within unique subgroups is needed . PreviouOur findings demonstrate the importance of identifying the role of modifiable risk factors  and non-modifiable factors . In our sample, more than 80% of participants self-reported having a routine checkup within the past two years, health insurance, and access to a healthcare provider despite a healthcare transition, which is characterized by changes in the provision of healthcare services starting at age 18 years . HealthcBoth modifiable and non-modifiable risk factors may influence perceived cancer risk, and it is critical to heighten perceived cancer risk of breast and other trending cancers among AYA women. Understanding the contributors for physically active Black women reporting lower perceptions of cancer risk may provide a better understanding of AYAs overall and site-specific cancer trends among Black women. Reasons for lower perceived cancer risk among Black women are multifactorial and related to the persistence of health disparities, in terms of excess mortality relative to other racial and ethnic groups—notably non-Hispanic White women—across multiple chronic health outcomes related to cardiovascular, cancer, and maternal health . As noteVulnerable subgroup populations of women who smoke, self-identify as Black, are physically active, and between the ages of 18 and 39 years should be included in culturally relevant educational interventions developed to address the unique healthcare needs of AYA populations to reinforce positive health behaviors and, in turn, reduce rising cancer incidence rates. For example, pamphlets, electronic or print handouts, or presentations that provide an overview of cancer risk factors at individual and team recreational sport game locations can provide education in a more relaxed, non-clinical setting. Dissemination of cancer risk factor knowledge at frequently visited exercise locations may be worthwhile to target at times hard-to-reach populations that consider themselves to be in good health.Another segment of the population that may bypass traditional clinic visits include individuals without a family history of cancer. Previous studies found that participants with a family history of cancer reported a significantly higher perceived cancer risk in comparison to participants with no known family history of cancer ,46. ThisA known family history of cancer, heightened perceptions of personal cancer risk, and routine doctor visits can be ideal for promoting cancer screening or early detection interventions . TraditiThe association of family history of cancer and perceived cancer risk may also demonstrate the need to develop and implement interventions that address awareness about genetic testing interventions. Pathogenic germline mutations present in up to 17% of breast cancer patients younger than age 45 . DespiteOur sample of physically active women presents as a uniquely, at-risk group for cancer given that 18% of our sample self-reported being a current smoker in contrast to the 13% of current smokers in the general population . CurrentOverall, our study assessed cancer risk perceptions within an understudied AYA population of physically active Black and White women between 18 and 39 years of age. Participants were recruited outside of the traditional clinical setting, which presents an alternative pathway to reach AYA population subgroups. Nevertheless, several limitations should be considered. First, our predictors of interest were self-reported, which may be unreliable for sensitive topics, such as family history of cancer and current smoking status, due to limited knowledge of family health or health behavior stigma. Second, we were not able to collect information about other relevant female-dominated cancers, such as breast and cervical cancer, risk factors, such as obesity (measured using BMI), reproductive health outcomes (measured using age at menarche and parity), and premenopausal hormone therapy use due to the scope of the survey instrument. We also did not screen our sample to include the cancer subtypes diagnosed within their family, which can also have implications about the influence and prevalence of hereditary-based cancers among AYA populations.Due to rising trends in cancer incidence, more research is needed to better understand the unique social and health-risk related profiles of AYA populations. Efforts to reduce the lifetime risk of cancer among physically active, AYA women aged 18 to 39 may consider cultural , personalized , and lifestyle-focused  interventions. Given the discordance in the perceived and actual cancer risk among Black women, cancer public health strategies may consider strengthening community outreach activities and partnerships to provide opportunities to better support the development of cancer risk factor knowledge among the AYA community. We expect our study to help AYA women, clinicians, and researchers to better understand the contribution of modifiable and non-modifiable factors to improve knowledge about cancer risks and outcomes in an at times hard-to-reach population. Further studies to pinpoint the influence of additional demographic, social, and medical characteristics are needed for understanding the current perceived cancer risk among AYA populations.


Breast cancer is one of the world’s most prevalent cancer and the most common type of cancer in Malaysia. Interestingly, breast cancer in young women is more aggressive compared to older women and the survival rate among these groups of individuals is poor. Thus, breast cancer awareness is essential among young women as early detection is possible and treatment will be effective during which the disease is curable. Hence, the purpose of this study is to design and evaluate the impact of an educational game on breast cancer awareness among female university students in Malaysia.This is a one-group pre-and post-intervention pilot study. It was conducted in Private and public higher education institutions around Malaysia. An online education game was created and used as the intervention. A self-administered questionnaire was administered to the participants during the pre-and post-intervention test to evaluate the online educational game on breast cancer awareness.A total of 52 responses were collected. The mean age of the participants was 21.98 (SD = 1.896) years. The findings showed a statistically significant median increase (p < 0.05) in breast cancer knowledge scores among participants in the post-intervention. A median increase in breast cancer knowledge score of 6 was shown when participants were exposed to the online education game (24.00) compared to before they were exposed to it (17.00).Using online educational games effectively raised awareness of breast cancer among university students. Online games can be used as a health educational tool to promote awareness of a topic of interest, as digital games can be accessed easily, game content can be tailored made or updated, and improve participant engagement in learning. According to the World Health Organization (WHO), breast cancer is the world’s most prevalent cancer with a total of 7.8 million women diagnosed with breast cancer from 2015 to 2020 globally .A comprehensive review revealed that breast cancer knowledge and awareness were poor among AYAs . CentersThe AYA generation has grown up using the internet and social media platforms . In 2018A single pre/post-intervention pilot study was conducted on a convenient sample of 30 Malaysian female students from private and public higher education institutions with age ≥ 18 years old, live in Malaysia, own a laptop, and can speak, read, and write in English , 18. ThoAn online self-administered questionnaire was distributed to the eligible participants to assess their baseline breast cancer awareness in the pre-intervention phase. Participants were asked to provide their phone number and email address for subsequent communication between the researchers and participants to ensure their full participation.A self-administered questionnaire was administered in pre-intervention and post-invention phases. The questionnaire consisted of 2 sections, including Section A: 12 socio-demographic items, Section B: 24 breast cancer knowledge items. The questionnaire was reviewed and validated by various experts from medical and academicians who have had conducted and published validated quantitative studies. An online Google form was created, and the link was disseminated to the participants through various online social platforms including WhatsApp and Facebook. The QR code to access the Google form was distributed physically to participants at the campus. They were also encouraged to share the Google form link with their classmates or friends for snowball sampling. The same questionnaire was administered before and after the intervention to access the changes in their breast cancer awareness. A digital educational game was developed as a platform-styled video game with a total of 5 levels. The main character named Emily (participant) was required to complete the game by killing a group of enemies and answering breast cancer knowledge related questions at each level. Information and keywords related to breast cancer knowledge were provided to the main character.A platform-styled video game was created using the game-creation programme “Unity” Figs. , 5 and 6The game began with the participant (Emily) received a message from her friend, Andrea asking her to meet up in the town. Andrea informed Emily of her breast cancer diagnosis and treatment plan. Andrea urged Emily to get mammography, but Emily refused because she was afraid. Emily arrived home and fell asleep in her bed. That night, she had a dream about some enemies (cancer cells) attacking her.Game-play consisted of guiding the participant (Emily) character to destroy enemies (cancer cells), for example moving, jumping, attacking and how to proceed to the next level.The participant can engage with the blue creature (sprite) by pressing the letter “C” on their keyboard to open a text message about breast cancer .These blue creatures (sprite) can be found throughout the game, providing breast cancer information to the participant, including general knowledge, signs and symptoms, risk factors, treatment, and screening.To advance to the next level, participant must defeat all the enemies. Enemies can inflict damage on players, which reduces one red heart (top left of the screen) per hit. Participant must restart the level (respective level) if they lose all of their red hearts.Before moving to the next level, participants had to answer all of the breast cancer-related questions. By answering correctly, participants will receive power level-ups such as increased damage inflicted to enemies. If the answer was incorrect, the correct answer will be given.The image above shows the game’s end after participant completed all 5 levels.Data were collected from August to October 2022 from web and physical. An online Google form was disseminated to the participants through various online social platforms including WhatsApp and Facebook. The QR code to access the Google form was distributed physically to participants at the campus. They were also encouraged to share the Google form link with their classmates or friends who fulfilled the recruitment criteria. Once the participants completed the pre-intervention questionnaire, the digital game link and post-intervention questionnaire were shared to the participants.The Statistical Packages for the Social Sciences (SPSS) version 20 was used for the descriptive and inferential analysis of the data. Categorical data were summarized using frequencies and percentages. For knowledge items, ‘1 mark’ for correct response and ‘0’ mark for incorrect response and do not know. The data obtained were not normally distributed, a Mc-Nemar test. and Wilcoxon Signed Rank test were used to determine pre- and post-test changes. The results were expressed in median ± standard deviation (SD) and a p-value of < 0.05 was considered statistically significant.This study was approved by the Faculty Research and Scholar Activities (FRSA), Faculty of Pharmaceutical Science, UCSI University and Institutional Ethics Committee (IEC-2022-FPS-044), UCSI University. All methods were carried out in accordance with relevant guidelines and regulations. Written informed consent was obtained from each participant who was assured of confidentiality and anonymity before their participation. Any type of dissemination of the data was done anonymously.The sociodemographic characteristics of participants were presented in Table Table Tables The majority of the breast cancer knowledge items improved significantly (p < 0.05) following intervention especially item no 2 (35.85% vs. 96.23%) under general knowledge section; item no 2 (49.06% vs. 92.45%) and item no 3 (30.19% vs. 66.04%) under risk factors section; item 4 (56.60% vs. 98.11%), item 7 (43.40% vs. 84.91%) and item 8 (35.95% vs. 86.79%) under breast cancer screening and treatment section. Some of the items had intermediate or high scores in the pre-intervention trial (such as signs and symptoms of breast cancer), the changes after intervention were still significant. Never breastfeeding (risk factor) received the lowest score and showed the least improvement.A Wilcoxon signed-rank test showed a statistically significant median increase in breast cancer awareness score post-intervention (24.00) compared to pre-intervention (17.00), z = -6.101, p < 0.05.Table Table Breast cancer is the most common type of cancer among females and the second leading cause of cancer death among females. Young women who are diagnosed with breast cancer tend to have a poorer survival rate (prognosis) due to the more aggressive nature of breast cancer compared to the ones in older women –22. PoorThe use of video games other than for the sole purpose of entertainment is called a ‘serious game’ . A serioThe results of the present study indicated that the digital education game significantly improved breast cancer awareness among young females, including their general knowledge, risk factors, signs and symptoms, and screening and treatment of breast cancer. According to our pre-intervention results, early menstruation before the age of 12, late menopause after the age of 55, use of birth control pill, not breastfeeding, and nulliparity are the less well-known risk factors, in comparison to factors like age, family history of breast cancer, and an unhealthy lifestyle. The findings were consistent with the previous studies conducted in the south of Peninsular Malaysia and Shah Alam , 34, 35.Overall, the participants provided positive comments, claiming that the digital educational game was an innovative tool to raise their level of health awareness and that it encouraged them to learn more. The outcome was consistent with past studies , 31, 37 The biggest drawback of the current version of digital educational game is that it is difficult for participants to use the “fighting” system. The game can be improved further in a number of ways, including (1) expanding the gameplay’s mechanics such as extension of the range of attack, smooth action, and movement, to make it easier for players to participate; (2) making it mobile devices compatible to improve its convenience and playability; (3) adding game mechanics like challenges ; and (4)The previous studies showed that young women have limited breast cancer knowledge. With the high mortality rate and the fact that there is currently no prescribed breast cancer screening program for AYA women without known risk factors for the disease, it is crucial for young women to learn and understand their breast cancer risk and to be proactive about their health to lower their risk of getting breast cancer. The results of the current study show that gamification can enhance AYAs’ learning motivation and experience with breast cancer. With the advancement of educational technology and its convenience, educational games are becoming more and more popular, and further research is therefore recommended in Malaysia to improve the content of the digital game and its features on breast cancer. In conclusion, gamification can enhance breast cancer awareness among AYAs.


Experimental studies suggest a role for osteoprotegerin (OPG) and tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) in mammary tumor development and progression. These biomarkers have been minimally investigated with respect to outcomes in breast cancer patients.OPG and TRAIL were evaluated in blood samples collected from 2459 breast cancer patients enrolled in the MARIE study, a prospective population-based patient cohort, at median of 129 days after diagnosis. Participants were between ages 50 and 74 at diagnosis and recruited from 2002 to 2005 in two regions of Germany. Follow-up for recurrence and mortality was conducted through June 2015. Delayed-entry Cox proportional hazards regression was used to assess associations between OPG and TRAIL with all-cause and breast cancer-specific mortality, and recurrence, both overall and by tumor hormone receptor status.log2) = 1.24 . Associations were observed in women diagnosed with ER-PR- tumors or discordant hormone receptor status ; discordant ERPR, 1.70 (1.03–2.81)), but not for women with ER + PR + tumors (HRlog2 = 1.06 (0.83–1.35)). OPG was associated with a higher risk of recurrence among women with ER-PR- disease (HRlog2 = 2.18 (1.39–3.40)). We observed no associations between OPG and breast cancer-specific survival, or for TRAIL and any outcome.Median follow-up time was 11.7 years, with 485 deaths reported (277 breast cancer-specific). Higher OPG concentrations were associated with a higher risk of all-cause mortality (hazard ratio for 1-unit log2-transformed concentration (HRHigher circulating OPG may be a biomarker of a higher risk of poor outcome among women diagnosed with ER- breast cancer. Further mechanistic studies are warranted.The online version contains supplementary material available at 10.1186/s13058-023-01625-4. Receptor activator of nuclear factor-κB (RANK) signaling plays a critical role in breast development, mediated by a transmembrane receptor (RANK), its ligand (RANKL) and osteoprotegerin (OPG), a decoy receptor for RANKL . Experimental research suggests a role for RANK-axis members in breast cancer etiology, treatment, and prevention –4. An eaWe hypothesized that the positive association observed between OPG and ER- breast cancer risk in our prior study may be due to the dual role of OPG as the decoy receptor for RANKL and TNF-Related Apoptosis-Inducing Ligand (TRAIL). TRAIL induces apoptosis, particularly in hormone receptor-negative breast cancer cell lines –12, and This study was conducted in the Mammary Carcinoma Risk Factor Investigation (MARIE) Study, a prospective population-based patient cohort study that began as a case–control study conducted in two regions of Germany: Rhine-Neckar-Karlsruhe and Hamburg . From 20Women who provided blood samples at recruitment and for whom a blood specimen was available (n = 2730) were initially eligible for analyses. Women with metastases at diagnosis (n = 84), previous tumors other than breast cancer or non-melanoma skin cancer before diagnosis n = 154), previous breast cancer recurrence (n = 19), missing data for tumor grade (n = 11), size (n = 2), and ERPR status (n = 1) were excluded. Additionally, missing measurements (OPG n = 3/TRAIL n = 0) and outliers (OPG n = 0/TRAIL n = 2) were excluded. Overall, 2459 women were available for analysis including 2456 observations with OPG measurements and 2457 with TRAIL  . Self-reported recurrences of the primary breast cancer, second cancers, and metastatic disease were provided at two follow-ups  were verified by clinical records or with treating physicians. For patients who died, data were collected from medical records or treating physicians. Primary outcomes were all-cause mortality , breast cancer-specific mortality, and recurrence  [OPG and TRAIL were log2-transformed for analyses on the continuous scale and categorized into quartiles based on the distribution in the full study sample. Linear regression models adjusted for age and study center were used to assess cross-sectional associations between OPG and TRAIL concentrations and clinical and lifestyle characteristics. Pearson partial correlations adjusted for age were calculated for the subsample of 28 women with OPG and TRAIL measured at two time points (median time between blood collections: 5.2 years (range: 3.6–5.9)) to estimate within-person stability of analyte levels.Delayed-entry Cox proportional hazards regression was used to estimate hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) for associations between OPG and TRAIL with outcomes overall and by tumor hormone receptor subtype. Analyses by hormone receptor subtype are restricted to invasive disease. Time-to-event started from the date of diagnosis, and time-at-risk started from the date of blood collection. Years from diagnosis was used as the timescale. Women who did not experience one of the defined endpoints (recurrence or death) after diagnosis were censored at the time of the last follow-up. Associations were investigated for the entire duration of follow-up (median = 11.7 (range = 0.30–14.5) years calculated using reverse Kaplan–Meier method ), as welHeterogeneity in associations between OPG and TRAIL and outcomes by tumor hormone receptor subtype at diagnosis , ER-/PR-) were assessed by evaluating the Wald p-value associated with an interaction term in the model. Heterogeneity by HER2 status, and restriction to triple-negative tumors, was also investigated. Additionally, we assessed heterogeneity by BMI  and conducted a sensitivity analysis restricted to women reporting natural menopause (91%).All models were adjusted for the following prognostic factors: tumor size, nodal status, tumor grade, and age, and stratified by study center and hormone receptor status. The proportional hazards assumption was evaluated using a weighted least‐squares line fitted to the plots of scaled Schoenfeld residuals ; no viol) or IIIb or higher, and who had blood drawn (1) within 7 days or (2) within 3 months after surgery. The cutoff points for the timing of blood collection were selected based on data showing OPG concentrations tended to be lower up to 3 months after surgery .A total of 2,459 total breast cancer patients (93.7% invasive disease) were included in this study Fig. , with a In the cross-sectional analysis, older age was associated with higher circulating OPG and TRAIL concentrations Table , and higConcentrations were lower in women with blood collection within less than 3 months of breast cancer surgery for OPG, and within 7 days of surgery for TRAIL, compared to blood collected later : 1.24 (1.03–1.49)) for all cases (Table het) = 0.09), associations were only observed for ER-PR- and ERPR-discordant disease ; ERPR-discordant, 1.70 (1.03–2.81), ER + PR + , 1.06 (0.83–1.35)). Higher circulating OPG was not significantly associated with a higher risk of breast cancer-specific death but was associated with a higher risk of recurrence among cases diagnosed with ER-PR- disease (HRlog2: 2.18 (95% CI: 1.39–3.40); phet = 0.01). No significant associations for recurrence were observed for ERPR-discordant or ER + PR + cases, though the HR for the ERPR-discordant group (HRlog2: 1.50 (0.92–2.45)) was intermediate to the ER-PR- (HRlog2: 2.18 (1.39–3.40)) and ER + PR + groups (HRlog2: 0.97 (0.77–1.21)). Associations in triple-negative cases were similar to those for ER-PR- cases (HRlog2: 1.97 (1.16–3.34); data not tabled). We observed no heterogeneity in associations by HER2 status. Associations for 5-year survival followed a similar pattern to those observed for the full follow-up period, though HRs were somewhat attenuated for some associations ; 5-year follow-up: 1.55 (0.79–3.06) ) but not in women with BMI < 25 kg/m2 (HRlog2: 0.87 (0.64–1.18); phet = 0.02). When restricting the analysis to women reporting natural menopause, associations were similar to those observed in the full study sample. No differences by BMI or menopausal status were observed for associations between TRAIL with mortality and recurrence.In analyses stratified by BMI, a positive association was observed between OPG and all-cause mortality in women with BMI ≥ 25 kg/mFinally, we conducted sensitivity analyses excluding women based on the stage at diagnosis, use of neoadjuvant chemotherapy, and the time between surgery and blood collection. The pattern of associations for OPG was similar to that observed in our primary analyses 4 and DR5) with intracellular death domains and activation of an apoptotic program. Further non-apoptosis-inducing TRAIL receptors include TRAIL-R3 and -R4, in addition to OPG –21. OPG This study is the first to evaluate circulating OPG and TRAIL and outcomes following a breast cancer diagnosis in a large cohort of breast cancer patients with postdiagnosis blood samples . We observed a higher risk of overall death, but not breast cancer-specific death, with higher OPG in the current study. To our knowledge, only two studies have evaluated circulating OPG and breast cancer survival, with one study measuring circulating postdiagnosis OPG in breast cancer patients  . The mosAssociations between OPG and mortality following a breast cancer diagnosis were only observed among participants with ER-PR- and ERPR-discordant tumors in the current study. While no significant associations were observed for breast cancer-specific mortality, higher OPG was associated with a higher risk of recurrence among women with ER-PR- tumors. Prior studies on circulating OPG and survival following a breast cancer diagnosis have largely investigated associations in hormone receptor-positive disease , 9, giveThe associations observed in women with hormone receptor-negative disease in the current study were in line with our a priori hypothesis for OPG, given data suggesting that TRAIL-induced apoptosis is particularly relevant in hormone receptor-negative breast cancer cell lines –12 and tThe lack of data on OPG and TRAIL, and TRAIL receptors, at the tumor tissue level is a limitation of this study. Further studies characterizing circulating and tumor tissue levels are needed to inform the interpretation of the associations observed here and previously. Further limitations include the single measurement of OPG and TRAIL, which may not reflect longer-term concentrations. Based on the data available to date, the relevant window of exposure for prognosis is not established . The current study included samples collected at median of 129 days after breast cancer diagnosis and during time of active treatment, and while treatment data were collected and had minimal impact on concentrations, concentrations collected more proximate to diagnosis and before active treatment may be of relevance.We observed that higher circulating OPG may be a biomarker of a higher risk of poor outcome among women diagnosed with ER-PR- or ER/PR-discordant breast cancer. While further mechanistic studies are needed, OPG may be a marker of prognosis in breast cancer patients.Additional file1. Postdiagnosis circulating osteoprotegerin and TRAIL concentrations and survival and recurrence after a breast cancer diagnosis: Results from the MARIE patient cohort: Tables S1- S5 and Figure S1. Table S1: Geometric means for OPG and TRAIL (in pg/mL) adjusted for age and center by clinical characteristics and lifestyle factors. Table S2: Hazard ratios and corresponding 95% confidence intervals for the association between circulating OPG concentration at blood collection and 5-years survival, stratified by ERPR status. Table S3: Hazard ratios and corresponding 95% confidence intervals for the association between circulating TRAIL concentration at blood collection and 5-years survival, stratified by ERPR status. Table S4: Sensitivity analysis for the association between circulating OPG and TRAIL concentration at blood collection and overall survival. Table S5: Sensitivity analysis for the association between circulating OPG and TRAIL concentration at blood collection and 5-years survival. Figure S1: OPG and TRAIL concentrations by time between breast cancer operation and blood collection.