Disparities in Breast Cancer Stage at Diagnosis: Importance of Race, Poverty, and Age

This study investigated the association of race, age, and census tract area poverty level on breast cancer stage at diagnosis. The study was limited to women residing in Missouri, aged 18 years and older, diagnosed with breast cancer, and whose cases were reported to the Cancer Registry between 2003 and 2008. The risk, relative risk, and increased risk of late-stage at diagnosis by race, age, and census tract area poverty level were computed. We found that the odds of late-stage breast cancer among African-American women were higher when compared with their white counterpart (OR 1.433; 95% CI, 1.316, 1.560). In addition, the odds of advanced stage disease for women residing in high-poverty areas were greater than those living in low-poverty areas (OR 1.319; 95% CI 1.08; 1.201). To close the widening cancer disparities gap in Missouri, there is the need for effective and programmatic strategies to enable interventions to reach areas and populations most vulnerable to advanced stage breast cancer diagnosis

Current State of Breast Cancer Diagnosis, Treatment, and Theranostics

Breast cancer is one of the leading causes of cancer-related morbidity and mortality in women worldwide. Early diagnosis and effective treatment of all types of cancers are crucial for a positive prognosis. Patients with small tumor sizes at the time of their diagnosis have a significantly higher survival rate and a significantly reduced probability of the cancer being fatal. Therefore, many novel technologies are being developed for early detection of primary tumors, as well as distant metastases and recurrent disease, for effective breast cancer management. Theranostics has emerged as a new paradigm for the simultaneous diagnosis, imaging, and treatment of cancers. It has the potential to provide timely and improved patient care via personalized therapy. In nanotheranostics, cell-specific targeting moieties, imaging agents, and therapeutic agents can be embedded within a single formulation for effective treatment. In this review, we will highlight the different diagnosis techniques and treatment strategies for breast cancer management and explore recent advances in breast cancer theranostics. Our main focus will be to summarize recent trends and technologies in breast cancer diagnosis and treatment as reported in recent research papers and patents and discuss future perspectives for effective breast cancer therapy

Relationship of religiosity and spirituality with quality of life in breast cancer patients

Background Breast cancer is most common, most lethal and most effective cancer in women that affect patient's quality of life at diagnosis, during treatment, and after recovery. Religion and spirituality are meaning factors in life as part of patients strategy for coping with diagnosis and treatment can be effective to improve quality of life in cancer survivors. METHODS This study was a comprehensive literature review performed through searches in databases such as Medline, PubMed, Science Direct, Scopus, and Google Scholar using the terms " Breast Cancer, Oncology, Religiosity/Spirituality, Quality of Life ". Findings Based on the results of many studies religiosity/spirituality are associate with physical and mental health, that by reducing the emotional distress, anxiety, feelings of hopelessness, helplessness and fear of death, as an adjustment approach in coping after diagnosis and improving the patient's quality of life be effective. Conclusion According to the studies, sketching care interventions with holistic approach with an emphasis on the spiritual dimension of care can be high chance of success in coping of cancer survivors with their diseases and improve their quality of life

Improved Classification of Breast Cancer Data using Hybrid Techniques

Breast cancer is the second leading cancer for women in developed countries including India. Many new cancer detection and treatment approaches were developed. The most effective way to reduce breast cancer deaths is detect it earlier. The frequent occurrence of breast cancer and its serious consequences have attracted worldwide attention in recent years. Problems such as low rate of accuracy and poor self-adaptability still exist in traditional diagnosis. In order to solve these problems, an Ada Boost-SVM classification algorithm, Combined with k-means is proposed in this research for the early diagnosis of breast cancer. The effectiveness of the proposed methods are examined by calculating its accuracy, confusion matrix which give important clues to the physicians for early diagnosis of breast cancer

Breast cancer: early diagnosis and effective treatment by drug delivery tracing

Breast cancer is the most frequent cancer in women and it is the main reason of cancer-related deaths of women worldwide. Different types of breast cancer diagnostic examinations are also available, such as mammography, MRI, biopsy, ultrasound and molecular imaging. Radionuclide-based imaging methods including SPECT and PET are useful in early diagnosis and treatment of the cancer. The radiolabeling of chemo drugs with nanoparticles should be recommended from the standpoint of an early diagnosis and effective treatment of breast cancer

Breast cancer treatment: survival facts and associated side effects

In the world the cancer is a prevailing disease therefore some rational and effective therapy required. The breast cancer is one of the most common cancers in a woman and now a day’s patients are increase. Therefore, development and research are ongoing on the effective treatment on breast cancer. The breast cancer treatment is depending on the cancer stage disease and risk, based on this therapeutic agent should be employed in the patients to protect the breast cancer disease. Such treatments are reducing the mortality and morbidity but constant monitoring of drug adverse effect. Moreover, it has been seen that the survival rates in breast cancer is rising that is good news for science but on the other side the side effects of the treatments bring new challenges.  The early stage diagnosis of the breast cancer can survive the effective or healthy patient life because of long-term and various treatment can be employed on the cancer disease otherwise breast cancer is life threatening illness. Survivors of breast cancer have not only the side effects issues of the cancer therapy treatment but also, they have many other issues of previous treatments therefore it is challenging job for the researchers. Consequently, this review article is dealing with the breast cancer effective treatments and side effects of it. Moreover, it includes the other long-term medical issues after breast cancer diagnosis and treatment. This review will help to the researchers for better understanding of the long-term medical issues in the breast cancer

ANIMAL VENOM FOR TREATING BREAST CANCER

Breast cancer is one of the most common malignancies found in women and is associated with increased mortality in advanced disease. With the use of improved screening techniques and improvisation in treatment, 89% of the women diagnosed with breast cancer will survive 5 years from diagnosis. Despite significant advancement in the diagnosis and treatment of breast cancer, many patients succumb to this disease. The elucidation of aberrant signaling pathways that lead to breast cancer should help develop more effective therapeutic strategies. This review focuses on the different targets of breast cancer and how they can be acted upon by different animal venoms

Evaluation of Joint Multi-Instance Multi-Label Learning For Breast Cancer Diagnosis

Multi-instance multi-label (MIML) learning is a challenging problem in many aspects. Such learning approaches might be useful for many medical diagnosis applications including breast cancer detection and classification. In this study subset of digiPATH dataset (whole slide digital breast cancer histopathology images) are used for training and evaluation of six state-of-the-art MIML methods. At the end, performance comparison of these approaches are given by means of effective evaluation metrics. It is shown that MIML-kNN achieve the best performance that is %65.3 average precision, where most of other methods attain acceptable results as well