Background and Objectives: As one of the most common treatments for breast cancer, mastectomy has adverse effects on the quality of sexual life and sexual functioning in the impacted women. Various strategies have therefore been proposed to resolve their sexual problems. The present study was conducted to determine the effect of sexual rehabilitation using the PLISSIT model in post-mastectomy breast cancer survivors. Materials and Methods: The present quasi-experimental study was conducted on a population of post-mastectomy breast cancer survivors and their husbands. Sample size was calculated as 50 each for intervention and non-intervention groups. The former received sexual counseling based on the PLISSIT model consisting of four levels of intervention: permission, limited information, specific suggestion and intensive therapy, presented in four 90-minute sessions. Data were collected using the Sexual Quality of Life-Female (SQOL-F) questionnaire and the Female Sexual Function Index (FSFI). Results: No significant differences were observed in the mean quality of sexual life scores between the intervention and control groups (P>0.05) before the intervention; however, a significant difference emerged between the groups after the intervention (P<0.01). Thus the mean score for sexual functioning in the intervention group was $26.3{\pm}3.76$ before and $30.0{\pm}4.38$ after the intervention (P<0.0001). In the control group, however, the difference between the pre- and post-intervention mean scores was not statistically significant (P=0.713). Conclusion: The present study showed that nurses can use the PLISSIT model in conjunction with chemotherapy and radiotherapy to teach coping and problem-solving skills to women with breast cancer and their husbands and to encourage their participation in group programs for expressing their feelings and attitudes about their current sex life and thus help enhance quality of sexual life and sexual functioning in this group.
Background: Breast cancer is the most prevalent malignancy in women worldwide; lack of awareness of symptoms and delay on diagnosis of breast cancer are the main causes of mortality among women. This study was conducted with the purpose of assessing the effect of educational consulting for breast self-examination (BSE) based on the health belief model (HBM) on the knowledge and performance of women over 40 years attending health care centers in Hamadan, Iran. Materials and Methods: In this quasi-experimental study, eligible women admitted to health centers in Hamadan city in 2015 were randomly assigned to intervention and control groups (n=75 in each group). The intervention group received 4 weekly sessions of breast cancer screening consulting based on the HBM. Control group received only routine care. Knowledge, HBM constructs, and BSE practice were compared between the groups before, immediately after and three months after the consultation. Results: Before the intervention, no significant differences were observed in knowledge, health belief and practice between two groups. However, after the intervention a significant difference was observed between two groups in mean scores of perceived benefits, perceived barriers, self-efficacy and the health motivations (p <0.05). Significant differences were also observed in terms of knowledge and BSE practice (p <0.01). Conclusions: The results indicate the importance of consultation on knowledge and beliefs to improve BSE performance and prevention of breast cancer in Iranian women.
Objectives : This study was aimed to grasp the stages of change in breast cancer screening of the nurses and general women who were over 20 and under 50 and specify the factors which affected the stages of change in breast cancer screening, based on Precaution Adoption Process Model. Methods : This study was conducted for 158 people who consisted of the nurses and general women who were over 20 and under 50. Results : As a result of examining the factors of cues to action and the belief in cancer screening according to the stages of change in the breast cancer screening of the nurses and general women, there was not a statistically significant difference and the perceived barriers showed a statistically significant difference in the stage of behavioral decision, the fifth stage. Conclusion : It is necessary to approach the individuals with the recommendation of cancer screening through the people around them and differentiated strategies considering the stages of change in cancer screening in order to induce the behavioral change in breast cancer screening, and develop and apply the strategies to enhance the severity perceived on the breast cancer.
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.
In recent years, using Deep Learning methods to apply for medical and biomedical image analysis has seen many advancements. In clinical, using Deep Learning-based approaches for cancer image analysis is one of the key applications for cancer detection and treatment. However, the scarcity and shortage of labeling images make the task of cancer detection and analysis difficult to reach high accuracy. In 2015, the Unet model was introduced and gained much attention from researchers in the field. The success of Unet model is the ability to produce high accuracy with very few input images. Since the development of Unet, there are many variants and modifications of Unet related architecture. This paper proposes a new approach of using Unet++ with pretrained EfficientNet as backbone architecture for breast tumor cell nuclei segmentation and uses the multi-organ transfer learning approach to segment nuclei of breast tumor cells. We attempt to experiment and evaluate the performance of the network on the MonuSeg training dataset and Triple Negative Breast Cancer (TNBC) testing dataset, both are Hematoxylin and Eosin (H & E)-stained images. The results have shown that EfficientUnet++ architecture and the multi-organ transfer learning approach had outperformed other techniques and produced notable accuracy for breast tumor cell nuclei segmentation.
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.
Field-in-Field Technique is applied to the radiation therapy of breast cancer patients, and it is possible to compensate the difference in breast thickness and deliver uniform dose in the breast. However, there are several fields in the treatment field that result in a more complex dose delivery than a single field dose delivery. If the patient's respiration is irregular during the delivery of the dose by several fields and the change of respiration occurs, the dose distribution in the breast changes. Therefore, based on the computed tomography images of breast cancer patients, a human model was created by using a 3D printer (Builder Extreme 1000) to describe the volume in the same manner. A computerized tomography (CT) of the human body model was performed and a treatment plan of 260 cGy / fx was established using a 6-MV field-in-field technique using a computerized treatment planning system (Eclipse 13.6, Varian, USA). The distribution of the dose in the breast according to the change of the respiration was measured using a moving phantom at 0.1 cm, 0.3 cm, 0.5 cm amplitude, using a MOSOXIDE Silicon Field Effect Transistor (MOSFET, Best Medical, Canada) Were measured and compared. The distribution of dose in the breast according to the change of respiration showed similar value within ${\pm}2%$ in the movement up to 0.3 cm compared to the treatment plan. In this experiment, we found that the dose distribution in the breast due to the change of respiration when the change of respiration was increased was not much different from the treatment plan.
Purpose: One of the main reasons why mothers quit breast feeding is that the volume of breast milk is inadequate due to insufficiency in suckling. We believe suckling experience may be a factor affecting nipple confusion. So an alternative feeding method, namely cup, spoon, finger, or nasogastric tube feeding may be needed to prevent nipple confusion. The purpose of this study was to construct a predictive model for demand for alternative feeding education by nurses. Methods: A descriptive design with structured self-report questionnaires was used for this study. Data from 175 nurses working in hospitals in Busan were collected between April 1 and 15, 2009. Data were analyzed by decision tree method, one of the data mining techniques using SAS 9.1 and Enterprise Miner 4.3 program. Results: Of the nurses, 81.1% demanded alternative feeding education and 5 factors showed that most of them expressed intention to pay, desire to know about alternative feeding, age, and learning experience. From these results, the derived model is considered appropriative for explaining and predicting demand for alternative feeding education. Conclusion: This confirms that knowledge and compliance in alternative breast feeding for newborn babies should be correct and any inaccuracies or insufficient information should be supplemented.
Xin, Yue;Li, Xiao-Yu;Sun, Shi-Ran;Wang, Li-Xia;Huang, Tao
Asian Pacific Journal of Cancer Prevention
/
v.16
no.12
/
pp.5125-5135
/
2015
Background: Total fat intake may be associated with increased risk of breast cancer, and fish oil has been suggested as a protection factor to breast cancer. But the effect of vegetable oils is inconclusive. We aimed to investigate the association with high vegetable oils consumption and breast cancer risk, and evaluated their dose-response relationship. Design: We systematically searched the MEDLINE, EMBASE, Cochrane databases, and CNKI updated to December 2014, and identified all observational studies providing quantitative estimates between breast cancer risk and different vegetable oils consumption. Fixed or random effect models were used to estimate summary odds ratios for the highest vs. lowest intake, and dose-response relationship was assessed by restricted cubic spline model and generalized least-squares trend (GLST) model. Results: Five prospective cohort studies and 11 retrospective case-control studies, involving 11,161 breast cancer events from more than 150,000 females, met the inclusion criteria. Compared with the lowest vegetable oils consumption, higher intake didn't increased the risk of breast cancer with pooled OR of 0.88 (95% CIs:0.77-1.01), and the result from dose-response analyses didn't show a significant positive or negative trend on the breast cancer risk for each 10g vegetable oil/day increment (OR=0.98, 95% CIs: 0.95-1.01). In the subgroup analyses, the oils might impact on females with different strata of BMI. Higher olive oil intake showed a protective effect against breast cancer with OR of 0.74 (95% CIs: 0.60-0.92), which was not significant among the three cohort studies. Conclusions: This meta-analyses suggested that higher intake of vegetable oils is not associated with the higher risk of breast cancer. Olive oil might be a protective factor for the cancer occurrence among case-control studies and from the whole. Recall bias and imbalance in study location and vegetable oils subtypes shouldn't be ignored. More prospective cohort studies are required to confirm the interaction of the impact of vegetable oils on different population and various cancer characteristic, and further investigate the relationship between different subtype oils and breast cancer.
Breast cancer remains the second leading cause of cancer death among woman, worldwide, despite advances in identifying novel targeted therapies and the development of treating strategies. Classification of clinical subtypes (ER+, PR+, HER2+, and TNBC (Triple-negative)) increases the complexity of breast cancers, which thus necessitates further investigation. Mouse models used in breast cancer research provide an essential approach to examine the mechanisms and genetic pathway in cancer progression and metastasis and to develop and evaluate clinical therapeutics. In this review, we summarize tumor transplantation models and genetically engineered mouse models (GEMMs) of breast cancer and their applications in the field of human breast cancer research and anti-cancer drug development. These models may help to improve the knowledge of underlying mechanisms and genetic pathways, as well as creating approaches for modeling clinical tumor subtypes, and developing innovative cancer therapy.
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