• Asian Pacific Journal of Cancer Prevention
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• v.16 no.1
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• pp.303-306
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• 2015

Purpose: This study was conducted to determine risk of developing of breast cancer among Turkish women. Materials and Methods: Using a descriptive and cross-sectional approach, data were collected from 231 women. Breast cancer risk was calculated using the National Cancer Institute's on-line verson of called as the Breast Cancer Risk Assessment Tool or the Gail Risk Assesment Tool. Results: The average age of women was $45.0{\pm}8.06$ years. It was revealed that 6.1% of participants reported having first degree relatives who had had breast cancer, with only four women having more than one first-degree relative affected (1.7%). The mean five-year breast cancer risk for all women was $0.88{\pm}0.91%$, and 7.4% of women had a five-year breast cancer risk >1.66% in this study. Mean lifetime breast cancer risk up to age 90 years was $9.3{\pm}5.2%$. Conclusions: The breast cancer risk assessment tool can help in the clinical management of patient seeking advice concerning screening and prevention. Healthcare providers in Turkey can use this approach to estimate an individual's probability of developing breast cancer.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.6
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• pp.2759-2763
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• 2012

Objectives: Compared with Western countries, the incidence rates for breast cancer in China are still low. However, breast cancer appears to be hitting Chinese women at a much younger age, with a peak between 40 and 50 years. Furthermore, breast tumors of Asian women have molecular and genetic characteristics that are different from those of Caucasian women. Methods: A community-based study was designed to evaluate the relationship between lifestyles and breast cancer risk in Chinese women residing in Guangzhou. 16,314 subjects completed the questionnaire. Potential confounding factors included sociodemographic characteristics. Results: 33 individuals reported a history of breast cancer, yielding a prevalence rate of 202.3/100000. Associations between subjects' demographic and breast cancer risk factors were assessed. Breast cancer is associated with family history of breast cancer, X-rays received, benign breast disease and hyperlipoidemia or hypercholesteremia with elevated odds ratios. Conclusions: Family history of breast cancer, X-ray received benign breast disease and hyperlipoidemia or hypercholesteremia were significantly associated with risk of breast cancer and may havepotential for breast cancer risk assessment.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.8
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• pp.3759-3762
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• 2016

Background: Breast cancer risk assessment is a helpful method for estimating development of breast cancer at the population level. Materials and Methods: In this cross-sectional study, participants consisted of a group of 3,847 volunteers ($mean{\pm}SD$ age: $463{\pm}7.59$ years) in a convenience sample of women referred to health centers affiliated to Tehran University of Medical Sciences in Tehran, Iran. The risk of breast cancer was estimated by applying the National Cancer Institute's online version of the Gail Risk Assessment Tool. Results: Some 24.9% of women reported having one first-degree female relative with breast cancer, with 8.05% of them having two or more first-degree relatives with breast cancer. The mean five-year risk of breast cancer for all participants was $1.61{\pm}0.73%$, and 9.36% of them had a five-year risk of breast cancer >1.66%. The mean lifetime risk of breast cancer was $11.7{\pm}3.91%$. Conclusions: The Gail model is useful for assessing probability of breast cancer in Iranian women. Based on the their breast cancer risk, women may decide to accept further screening services.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.3
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• pp.895-904
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• 2016

Breast cancer is the most commonly diagnosed invasive cancer among women. Many factors, both genetic and non-genetic, determine a woman's risk of developing breast cancer and several breast cancer risk prediction models have been proposed. It is vitally important to risk stratify patients as there are now effective preventive strategies available. All women need to be counseled regarding healthy lifestyle recommendations to decrease breast cancer risk. As such, management of these women requires healthcare professionals to be familiar with additional risk factors so that timely recommendations can be made on surveillance/risk-reducing strategies. Breast cancer risk reduction strategies can be better understood by encouraging the women at risk to participate in clinical trials to test new strategies for decreasing the risk. This article reviews the advances in the identification of women at high risk of developing breast cancer and also reviews the strategies available for breast cancer prevention.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.3
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• pp.1737-1742
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• 2013

Early diagnosis has a major role in improving prognosis of breast cancer. The purpose of this study was to assess the risk status of women 35-69 years of age using risk assessment models and the prevalence of mammography in a community setting. The sample of this cross sectional study consisted of 227 women, 35-69 years of age residing in Izmir, a city located in western region of Turkey. A questionnaire was used to collect data and the Gail and Cuzick-Tyrer models were applied to assess the risk of breast cancer. In this study, 52.7% of women had mammography at least once, and 41.3% of the women over the age of 40 had mammography screening in the last two years. The five years risk for breast cancer was high in 15.8% of women according to the Gail model and ten years risk was high in 21.7% with the Cuzick-Tyrer model. In the present study, the breast cancer risk levels were assessed in a population setting for the first time in Turkey using breast cancer risk level assessment models. Being in 60-69 age group, having low education and not being in menopause were significant risk factors for not having mammography according to logistic regression analysis. Mammography utilization rate was low. Women must be educated about breast cancer screening methods and early diagnosis. The women in the high risk group should be informed on their risk status which may increase their attendance at breast cancer screening.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.10
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• pp.5877-5882
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• 2013

Background: The aim of the study was to determine breast cancer risk and early diagnosis applications in women aged ${\geq}50$. Materials and Methods: This cross-sectional, descriptive field study focused on a population of 4,815 in Mansuro$\breve{g}$lu with a 55.1% participation rate in screening. In the study, body mass index (BMI) was also evaluated in the calculation of breast cancer risk by the Breast Cancer Risk Assessment Tool (BCRA) (also called the "Gail Risk Assessment Tool"). The interviewers had a three-hour training provided by the researchers, during which interactive training methods were used and applications were supported with role-plays. Results: The mean age of the women participating in the study was $60.1{\pm}8.80$. Of these women, 57.3% were in the 50-59 age group, 71.7% were married, 57.3% were primary school graduates and 61.7% were housewives. Breast-cancer development rate was 7.4% in the women participating in the study. When they were evaluated according to their relationship with those with breast cancer, it was determined that 73.0% of them had firstdegree relatives with breast cancer. According to the assessment based on the Gail method, the women's breast cancer development risk within the next 5 years was 17.6%, whereas their calculated lifetime risk was found to be as low as 0.2%. Statistically significant differences (P=0.000) were determined between performing BSE-CBE and socio-demographic factors. Conclusions: It was determined that 17.6% of the participants had breast cancer risk. There was no statistically significant difference between the women with and without breast cancer risk in terms of early diagnosis practices, which can be regarded as a remarkable finding. It was planned to provide training about the early diagnosis and treatment of breast cancer for people with high-risk scores, and to conduct population-based breast cancer screening programs.

• Women's Health Nursing
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• v.11 no.1
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• pp.46-51
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• 2005

Purpose: The aim of this study was to identify risk factors for breast cancer and early screening behavior in women in the community. Method: The participants were 125 women residing in W city. Data was collected using an instrument developed by the researchers. Analysis was done using descriptive statistics, and the $x^2$ test. Result: For risk based on the Gail Model, age (above 50 years) had a distribution of 24.8%, first degree family history, 4.9%, age at first full term pregnancy, 13.8%, and benign breast cancer history, 4.9%. For risk based on other common risk factors, menopause had a distribution of 20.7%, did not breast feed, 15.4%, history of HRT, 7.3%, meat preference, 35.0%, and history of smoking or drinking, 2.4% and 43.5%, respectively. There was a significant difference in BSE and mammography screening behavior ($x^2=22.5$, p<.00), but no difference in distribution of risk factors and screening behavior. Conclusion: For effective prevention of breast cancer, it is necessary to develop an instrument for risk assessment and, through assessment, select women at high risk. It is also necessary to provide education and appropriate recommendations on screening behavior.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.5
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• pp.3281-3288
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• 2013

Background: Breast cancer is the leading cause of cancer-related deaths in women. Despite being associated with high morbidity and mortality, breast cancer is a disease that can be diagnosed and treated early. Materials and Methods: In this cross-sectional study of 321 women, data were collected by Questionnaire, Breast Cancer Risk Assessment Form and Champion's Health Belief Model Scale. Mann-Whitney U, Kruskal-Wallis, Chisquared tests and logistic regression were used in the statistical analysis. Results: It was found that only 2.2% of women have high and very high risk levels of breast cancer risk. There is a positive correlation between early diagnosis techniques and Health Belief Model Sub-Dimension scores which are sensibility, health motivation, BSE (Breast self-examination) self-efficient perception and negative correlation between mammography barrier score and BSE barrier score (p 0.05). When factors for not having BSE were examined, it was determined that the women who do not have information about breast cancer and the women who smoke have a higher risk of not having BSE. Conclusions: It is important to determine health beliefs and breast cancer risk levels of women to increase the frequency of early diagnosis. Women's health beliefs are thought to be a good guide for planning health education programs for nurses working in this area.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.11
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• pp.4913-4916
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• 2016

Objective: As a source of information, medical data can feature hidden relationships. However, the high volume of datasets and complexity of decision-making in medicine introduce difficulties for analysis and interpretation and processing steps may be needed before the data can be used by clinicians in their work. This study focused on the use of Bayesian models with different numbers of nodes to aid clinicians in breast cancer risk estimation. Methods: Bayesian networks (BNs) with a retrospectively collected dataset including mammographic details, risk factor exposure, and clinical findings was assessed for prediction of the probability of breast cancer in individual patients. Area under the receiver-operating characteristic curve (AUC), accuracy, sensitivity, specificity, and positive and negative predictive values were used to evaluate discriminative performance. Result: A network incorporating selected features performed better (AUC = 0.94) than that incorporating all the features (AUC = 0.93). The results revealed no significant difference among 3 models regarding performance indices at the 5% significance level. Conclusion: BNs could effectively discriminate malignant from benign abnormalities and accurately predict the risk of breast cancer in individuals. Moreover, the overall performance of the 9-node BN was better, and due to the lower number of nodes it might be more readily be applied in clinical settings.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.8
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• pp.3233-3239
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• 2015

Background: Whether depression causes increased risk of the development of breast cancer has long been debated. We conducted an updated meta-analysis of cohort studies to assess the association between depression and risk of breast cancer. Materials and Methods: Relevant literature was searched from Medline, Embase, Web of Science (up to April 2014) as well as manual searches of reference lists of selected publications. Cohort studies on the association between depression and breast cancer were included. Data abstraction and quality assessment were conducted independently by two authors. Random-effect model was used to compute the pooled risk estimate. Visual inspection of a funnel plot, Begg rank correlation test and Egger linear regression test were used to evaluate the publication bias. Results: We identified eleven cohort studies (182,241 participants, 2,353 cases) with a follow-up duration ranging from 5 to 38 years. The pooled adjusted RR was 1.13(95% CI: 0.94 to 1.36; $I^2=67.2%$, p=0.001). The association between the risk of breast cancer and depression was consistent across subgroups. Visual inspection of funnel plot and Begg's and Egger's tests indicated no evidence of publication bias. Regarding limitations, a one-time assessment of depression with no measure of duration weakens the test of hypothesis. In addition, 8 different scales were used for the measurement of depression, potentially adding to the multiple conceptual problems concerned with the definition of depression. Conclusions: Available epidemiological evidence is insufficient to support a positive association between depression and breast cancer.