• Korean Journal of Adult Nursing
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• v.21 no.6
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• pp.705-717
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• 2009

Purpose: The purpose of this study was to identify symptom clusters in patients with breast cancer and to investigate the associations among them with functional status and quality of life (QOL). Methods: A convenient sample of 303 patients was recruited from an oncology-specialized hospital. Results: Two distinct clusters were identified: A gastrointestinal- fatigue cluster and a pain cluster. Each cluster significantly influenced functional status and QOL. Based on these two clusters, we identified subgroups of symptom clusters using K-means cluster analysis. Three relatively distinct patient subgroups were identified in each cluster: mild, moderate, and severe group. Disease-related factors (i.e., stage, metastasis, type of surgery, current chemotherapy, and anti-hormone therapy) were associated with these subgroups of symptom clusters. There were significant differences in functional status and QOL among the three subgroups. The subgroup of patients who reported high levels of symptom clusters reported poorer functional status and QOL. Conclusion: Clinicians can anticipate that breast cancer patients with advanced stage, metastasis, and who receive mastectomy, and chemotherapy will have more intense gastrointestinal-fatigue or pain symptoms. In order to enhance functional status and QOL for patients with breast cancer, collective management for symptoms in a cluster may be beneficial.

• Journal of Korean Clinical Nursing Research
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• v.14 no.1
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• pp.61-70
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• 2008

Purpose: Women with gynecologic cancer often experience various physical and psychological symptoms relating to the cancer and its treatment. The purpose of this study was to identify symptom clusters. Method: A survey was conducted on 184 women with diagnoses of cervical, ovarian or endometrial cancer. Fifty symptoms were assessed for prevalence, severity and interference, and symptom clusters were identified. Cluster analysis was done using SPSS version 12.0. Results: Fatigue was identified as the most prevalent symptom (81.52%), lack of vaginal lubrication (2.26) as the most severe symptom, and lack of vaginal lubrication as the most interfering one (2.15). Identified six clusters were: Anorexia-pain cluster (loss of appetite, taste change, weight loss, appearance change, alopecia, weakness, pain), Fatigue cluster (lack of concentration, lack of memory, fatigue, dry mouth), Urinary-bowel distress cluster (urinary difficulty, constipation), Abdominal discomfort cluster (lower abdominal pain, abdominal pain, bloating), Emotional distress (sadness, anxiety-worry, nervousness, restlessness), and Menopausal cluster (sweating, hot flush, fever). Conclusion: The result of this study provides fundamental data to health care professionals in developing interventions for effective symptom management for women with gynecologic cancer by understanding identified 6 symptom clusters.

• Asian Oncology Nursing
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• v.3 no.1
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• pp.66-74
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• 2003

Purpose: This study is designed to identify clusters according to the causal attribution that people make about the cancer and to determine influences of coping behavior and depression as output of causal attribution. Method: The subjects were 192 patients who had been diagnosed cancer one year ago and attended an outpatient clinic. For cancer patients to be classified homogenious groups according to causal attribution, cluster analysis of subjects' ratings on the Causal Dimension Scale was been made. Results: Cluster 1(n=71) had patients with having external, stable and uncontrollable attribution. Cluster 2(n =70) had patients with having unstable and external controllable attribution regarding cause of cancer. They were not important whether cause of cancer was self or other. Cluster 3(n=51) had patients with having internal, unstable and internal controllable attribution. Coping behaviors between cluster 1 and 3 were significant difference. However, depression was not significant difference among clusters. Conclusion: Based upon these results, it is recommended that the developing training program to be changed to the more positive attribution is necessary.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.1
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• pp.455-460
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• 2014

Background: The purpose of the present study was to determine geographic clustering of breast cancer incidence in Kanagawa Prefecture, using cancer registry data. The study also aimed at examining the association between socio-economic factors and any identified cluster. Materials and Methods: Incidence data were collected for women who were first diagnosed with breast cancer during the period from January to December 2006 in Kanagawa. The data consisted of 2,326 incidence cases extracted from the total of 34,323 Kanagawa Cancer Registration data issued in 2011. To adjust for differences in age distribution, the standardized mortality ratio (SMR) and the standardized incidence ratio (SIR) of breast cancer were calculated for each of 56 municipalities (e.g., city, special ward, town, and village) in Kanagawa by an indirect method using Kanagawa female population data. Spatial scan statistics were used to detect any area of elevated risk as a cluster for breast cancer deaths and/or incidences. The Student t-test was performed to examine differences in socio-economic variables, viz, persons per household, total fertility rate, age at first marriage for women, and marriage rate, between cluster and other regions. Results: There was a statistically significant cluster of breast cancer incidence (p=0.001) composed of 11 municipalities in southeastern area of Kanagawa Prefecture, whose SIR was 35 percent higher than that of the remainder of Kanagawa Prefecture. In this cluster, average value of age at first-marriage for women was significantly higher than in the rest of Kanagawa (p=0.017). No statistically significant clusters of breast cancer deaths were detected (p=0.53). Conclusions: There was a statistically significant cluster of high breast cancer incidence in southeastern area of Kanagawa Prefecture. It was suggested that the cluster region was related to the tendency to marry later. This study methodology will be helpful in the analysis of geographical disparities in cancer deaths and incidence.

• Asian Oncology Nursing
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• v.9 no.2
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• pp.77-85
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• 2009

Purpose: The purpose of this study was to identify symptom cluster experienced by patients with advanced non-small cell lung cancer (NSCLC) on gefitinib treatment. In addition, this study assessed the patterns in severity of the symptom cluster and differences in quality of life (QOL) and function among subgroups by the severity of symptom cluster. Methods: This study was conducted as a secondary analysis of symptoms of 72 patients from a mother study. Factor analysis was used to identify symptom clusters measured with EORTC QLQ-C30 and LC13 symptom related items. Results: Three symptom clusters were identified: cluster 1 was comprised of fatigue, anorexia and dysphagia; cluster 2 of dyspnea, cough and insomnia; and cluster 3 of pain, constipation and nausea/vomiting. These three symptom clusters were improved one week after gefitinib administration. The group with more severe symptom clusters showed significantly lower QOL and function than the group with less severe symptom clusters. Conclusion: Since symptom clusters experienced by the patients with advanced NSCLC influenced on the QOL and function, it is important for nurses to understand and observe their symptom clusters. In addition, there is an necessity to develop nursing interventions to effectively care patients with the symptom clusters.

• Korean Journal of Adult Nursing
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• v.23 no.5
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• pp.434-445
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• 2011

Purpose: This study was conducted to identify the impact of the symptom cluster of pain, fatigue, sleep disturbance, depression on the quality of life (QOL) among breast cancer patients receiving chemotherapy. Methods: One hundred and thirteen patients were recruited from five hospitals in Korea. The instruments used in this study were the fatigue, depression, sleep disturbance, pain and the quality of life scale for patients with breast cancer. The influence of the symptom cluster on patients' QOL was analyzed by using multiple regression. Results: Most patients reported a moderate level of pain, fatigue, sleep disturbance and depression. Eighty percent of patients reported three of the four symptoms. Among the four symptoms, there was no correlation between pain and sleep disturbance. Quality of life was negative correlated with the four symptoms in the cluster. Symptom cluster of pain, fatigue, and depression accounted for 51.2% of variance in QOL. Conclusion: The findings supported that there is a symptom cluster that negatively influences quality of life and needs to be addressed as we are caring for patients and are promoting quality of life.

• Journal of Microbiology and Biotechnology
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• v.31 no.12
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• pp.1643-1655
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• 2021

Recent studies have reported dysbiosis of the microbiome in breast tissue collected from patients with breast cancer and the association between the microbiota and disease progression. However, the role of the microbiota in breast tissue remains unclear, possibly due to the complexity of breast cancer and various factors, including racial and geographical differences, influencing microbiota in breast tissue. Here, to determine the potential role of microbiota in breast tumor tissue, we analyzed 141 tissue samples based on three different tissue types (tumor, adjacent normal, and lymph node tissues) from the same patients with breast cancer in Korea. The microbiota was not simply distinguishable based on tissue types. However, the microbiota could be divided into two cluster types, even within the same tissue type, and the clinicopathologic factors were differently correlated in the two cluster types. Risk of regional recurrence was also significantly different between the microbiota cluster types (p = 0.014). In predicted function analysis, the pentose and glucuronate interconversions were significantly different between the cluster types (q < 0.001), and Enterococcus was the main genus contributing to these differences (q < 0.01). Results showed that the microbiota of breast tissue could interact with the host and influence the risk of regional recurrence. Although further studies would be recommended to validate our results, this study could expand our understanding on the breast tissue microbiota, and the results might be applied to develop novel prediction methods and treatments for patients with breast cancer.

• Molecules and Cells
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• v.43 no.2
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• pp.198-202
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• 2020

Comprehensive inhibition of RUNX1, RUNX2, and RUNX3 led to marked cell suppression compared with inhibition of RUNX1 alone, clarifying that the RUNX family members are important for proliferation and maintenance of diverse cancers, and "cluster regulation of RUNX (CROX)" is a very effective strategy to suppress cancer cells. Recent studies reported by us and other groups suggested that wild-type RUNX1 is needed for survival and proliferation of certain types of leukemia, lung cancer, gastric cancer, etc. and for their one of metastatic target sites such as born marrow endothelial niche, suggesting that RUNX1 often functions oncogenic manners in cancer cells. In this review, we describe the significance and paradoxical requirement of RUNX1 tumor suppressor in leukemia and even solid cancers based on recent our findings such as "genetic compensation of RUNX family transcription factors (the compensation mechanism for the total level of RUNX family protein expression)", "RUNX1 inhibition-induced inhibitory effects on leukemia cells and on solid cancers through p53 activation", and "autonomous feedback loop of RUNX1-p53-CBFB in acute myeloid leukemia cells". Taken together, these findings identify a crucial role for the RUNX cluster in the maintenance and progression of cancers and suggest that modulation of the RUNX cluster using the pyrrole-imidazole polyamide gene-switch technology is a potential novel therapeutic approach to control cancers.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1193-1201
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• 2016

In epidemiology or etiology, we are often interested in identifying areas of elevated risk, so called, hot spot or cluster. Many existing clustering methods only tend to a result if there exists any clustering pattern in study area. Recently, however, lots of newly introduced clustering methods can identify the location, size, and shape of clusters and test if the clusters are statistically significant as well. In this paper, one of most commonly used clustering methods, scan statistic, and its implementation SaTScan software, which is freely available, will be introduced. To exemplify the usage of SaTScan software, we used cancer data from the SEER program of National Cancer Institute of U.S.A.We aimed to help researchers and practitioners, who are interested in spatial cluster detection, using female lung cancer mortality data of the SEER program.

• The KIPS Transactions:PartB
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• v.16B no.2
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• pp.165-172
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• 2009

According to the American Cancer Society, breast cancer is the second largest cause of cancer deaths and most frequently diagnosed cancer in women. The currently most popular method for early detection of breast cancer is the digital mammography. A mass or calcification lesion has been known as the most important clue for the diagnosis. In this paper, we propose a diagnosis approach based on fuzzy cluster knowledge base. We combine different two sources of feature data in duel OFUN-NET and produce the diagnosis result with possibility degree. We also present the experimental results on the dataset of mass and calcification lesions extracted from the public real world mammogram database DDSM. These results show higher classification accuracy than conventional methods and the feasibility as a decision supporting tool for diagnosis of digital mammogram.