• Title/Summary/Keyword: Disease Prediction

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Association of Poor Prognosis Subtypes of Breast Cancer with Estrogen Receptor Alpha Methylation in Iranian Women

  • Izadi, Pantea;Noruzinia, Mehrdad;Fereidooni, Foruzandeh;Nateghi, Mohammad Reza
    • Asian Pacific Journal of Cancer Prevention
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    • v.13 no.8
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    • pp.4113-4117
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    • 2012
  • Breast cancer is a prevalent heterogeneous malignant disease. Gene expression profiling by DNA microarray can classify breast tumors into five different molecular subtypes: luminal A, luminal B, HER-2, basal and normal-like which have differing prognosis. Recently it has been shown that immunohistochemistry (IHC) markers including estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (Her2), can divide tumors to main subtypes: luminal A (ER+; PR+/-; HER-2-), luminal B (ER+;PR+/-; HER-2+), basal-like (ER-;PR-;HER2-) and Her2+ (ER-; PR-; HER-2+). Some subtypes such as basal-like subtype have been characterized by poor prognosis and reduced overall survival. Due to the importance of the ER signaling pathway in mammary cell proliferation; it appears that epigenetic changes in the $ER{\alpha}$ gene as a central component of this pathway, may contribute to prognostic prediction. Thus this study aimed to clarify the correlation of different IHC-based subtypes of breast tumors with $ER{\alpha}$ methylation in Iranian breast cancer patients. For this purpose one hundred fresh breast tumors obtained by surgical resection underwent DNA extraction for assessment of their ER methylation status by methylation specific PCR (MSP). These tumors were classified into main subtypes according to IHC markers and data were collected on pathological features of the patients. $ER{\alpha}$ methylation was found in 25 of 28 (89.3%) basal tumors, 21 of 24 (87.5%) Her2+ tumors, 18 of 34 (52.9%) luminal A tumors and 7 of 14 (50%) luminal B tumors. A strong correlation was found between $ER{\alpha}$ methylation and poor prognosis tumor subtypes (basal and Her2+) in patients (P<0.001). Our findings show that $ER{\alpha}$ methylation is correlated with poor prognosis subtypes of breast tumors in Iranian patients and may play an important role in pathogenesis of the more aggressive breast tumors.

Prognostic Factors in First-Line Chemotherapy Treated Metastatic Gastric Cancer Patients: A Retrospective Study

  • Inal, Ali;Kaplan, M. Ali;Kucukoner, Mehmet;Urakci, Zuhat;Guven, Mehmet;Nas, Necip;Yunce, Muharrem;Isikdogan, Abdurrahman
    • Asian Pacific Journal of Cancer Prevention
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    • v.13 no.8
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    • pp.3869-3872
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    • 2012
  • Background: The majority of patients with gastric cancer in developing countries present with advanced disease. Systemic chemotherapy therefore has limited impact on overall survival. Patients eligible for chemotherapy should be selected carefully. The aim of this study was to analyze prognostic factors for survival in advanced gastric cancer patients undergoing first-line palliative chemotherapy. Methods: We retrospectively reviewed 107 locally advanced or metastatic gastric cancer patients who were treated with docetaxel and cisplatin plus fluorouracil (DCF) as first-line treatment between June 2007 and August 2011. Twenty-eight potential prognostic variables were chosen for univariate and multivariate analyses. Results: Among the 28 variables of univariate analysis, nine variables were identified to have prognostic significance: performance status, histology, location of primary tumor, lung metastasis, peritoneum metastasis, ascites, hemoglobin, albumin, weight loss and bone metastasis. Multivariate analysis by Cox proportional hazard model, including nine prognostic significance factors evident in univariate analysis, revealed weight loss, histology, peritoneum metastasis, ascites and serum hemoglobin level to be independent variables. Conclusion: Performance status, weight loss, histology, peritoneum metastasis, ascites and serum hemoglobin level were identified as important prognostic factors in advanced gastric cancer patients. These findings may facilitate pretreatment prediction of survival and can be used for selecting patients for treatment.

Systems-level mechanisms of action of Panax ginseng: a network pharmacological approach

  • Park, Sa-Yoon;Park, Ji-Hun;Kim, Hyo-Su;Lee, Choong-Yeol;Lee, Hae-Jeung;Kang, Ki Sung;Kim, Chang-Eop
    • Journal of Ginseng Research
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    • v.42 no.1
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    • pp.98-106
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    • 2018
  • Panax ginseng has been used since ancient times based on the traditional Asian medicine theory and clinical experiences, and currently, is one of the most popular herbs in the world. To date, most of the studies concerning P. ginseng have focused on specific mechanisms of action of individual constituents. However, in spite of many studies on the molecular mechanisms of P. ginseng, it still remains unclear how multiple active ingredients of P. ginseng interact with multiple targets simultaneously, giving the multidimensional effects on various conditions and diseases. In order to decipher the systems-level mechanism of multiple ingredients of P. ginseng, a novel approach is needed beyond conventional reductive analysis. We aim to review the systems-level mechanism of P. ginseng by adopting novel analytical framework-network pharmacology. Here, we constructed a compound-target network of P. ginseng using experimentally validated and machine learning-based prediction results. The targets of the network were analyzed in terms of related biological process, pathways, and diseases. The majority of targets were found to be related with primary metabolic process, signal transduction, nitrogen compound metabolic process, blood circulation, immune system process, cell-cell signaling, biosynthetic process, and neurological system process. In pathway enrichment analysis of targets, mainly the terms related with neural activity showed significant enrichment and formed a cluster. Finally, relative degrees analysis for the target-disease association of P. ginseng revealed several categories of related diseases, including respiratory, psychiatric, and cardiovascular diseases.

Construction of a Protein-Protein Interaction Network for Chronic Myelocytic Leukemia and Pathway Prediction of Molecular Complexes

  • Zhou, Chao;Teng, Wen-Jing;Yang, Jing;Hu, Zhen-Bo;Wang, Cong-Cong;Qin, Bao-Ning;Lv, Qing-Liang;Liu, Ze-Wang;Sun, Chang-Gang
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.13
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    • pp.5325-5330
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    • 2014
  • Background: Chronic myelocytic leukemia is a disease that threatens both adults and children. Great progress has been achieved in treatment but protein-protein interaction networks underlining chronic myelocytic leukemia are less known. Objective: To develop a protein-protein interaction network for chronic myelocytic leukemia based on gene expression and to predict biological pathways underlying molecular complexes in the network. Materials and Methods: Genes involved in chronic myelocytic leukemia were selected from OMIM database. Literature mining was performed by Agilent Literature Search plugin and a protein-protein interaction network of chronic myelocytic leukemia was established by Cytoscape. The molecular complexes in the network were detected by Clusterviz plugin and pathway enrichment of molecular complexes were performed by DAVID online. Results and Discussion: There are seventy-nine chronic myelocytic leukemia genes in the Mendelian Inheritance In Man Database. The protein-protein interaction network of chronic myelocytic leukemia contained 638 nodes, 1830 edges and perhaps 5 molecular complexes. Among them, complex 1 is involved in pathways that are related to cytokine secretion, cytokine-receptor binding, cytokine receptor signaling, while complex 3 is related to biological behavior of tumors which can provide the bioinformatic foundation for further understanding the mechanisms of chronic myelocytic leukemia.

Determination of Nursing Price using Willingness to Pay (지불용의접근법을 이용한 간호서비스의 가격결정)

  • Ko, Su-Kyoung;Park, Jeong-Young
    • Journal of Korean Academy of Nursing Administration
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    • v.7 no.2
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    • pp.205-221
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    • 2001
  • It will become more and more popular to use the long-term care facilities and home health care services with the chronic disease increasing. It depends on how much the consumers would pay and purchase the services. They might get more benefits from that kind of services than from ordinary hospitalization. So far, the study of determining the medical service price has focused most often on the efforts from the providers' view. But it must be reasonable to include the consumers' value for the service. This study was performed to assess WTP(Willingness to Pay) for home health care service in order to apply to the determination of nursing price in a reasonable manner. In this study, respondents were asked if they would pay for the service's intangible benefits under the four different types(open-ended minimum WTP, open-ended maximum WTP, bidding WTP, referendum WTP). The contingent valuation method is a potentially useful tool in understanding how people value the benefits of the service. As a result, average open-ended minimum WTP was W16,015 per day among 65 respondents. Average open-ended maximum WTP was W29,154 per day among 65 respondents. Average bidding WTP was W26,300 per day among 65 respondents. Average referendum WTP was W22,200 per day among 70 respondents. The results of regression analyses were also consistent with theoretical prediction, e.g., increasing WTP with consumers' value for the service, state of patients, and household income. This study demonstrated that it was more reasonable to consider the consumers' value in determining the services' price. In addition, a further study is needed to test the validity of this CV method and to determine a proper nursing price based on the consumers' view.

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Design and Implementation of a Prediction System for Cardiovascular Diseases using PPG (PPG를 이용한 심혈관 질환 예측 시스템의 설계 및 구현)

  • Song, Je-Min;Jin, Gye-Hwan;Seo, Sung-Bo;Park, Jeong-Seok;Lee, Sang-Bock;Ryu, Keun-Ho
    • Journal of the Korean Society of Radiology
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    • v.5 no.1
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    • pp.19-25
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    • 2011
  • Photoplethysmogram(PPG) is the method to obtain the biomedical signal using the linear relationships between the blood volume for changing the cardiac contraction and relaxation and the amount of light for absorbing the hemoglobin in the blood. In this paper, we proposed the analyzed results which show the heart rate variability and the distribution of heart rate for before and after using PPG. Moreover, this paper designed and implemented the system based on personal computer to predict cardiovascular disease in advance using the analyzed results for the autonomic balance from taking the spectral analysis of heart rate and the state of the blood vessel for analyzing APG(acceleration plethysmogram).

Prediction of Changes in Health Expenditure of Chronic Diseases between Age group of Middle and Old Aged Population by using Future Elderly Model (Future Elderly Model을 활용한 중·고령자의 연령집단별 3대 만성질환 의료비 변화 예측)

  • Baek, Mi Ra;Jung, Kee Taig
    • Health Policy and Management
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    • v.26 no.3
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    • pp.185-194
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    • 2016
  • Background: The purpose of this study is to forecast changes in the prevalence of chronic diseases and health expenditure by age group. Methods: Based on the Future Elderly Model, this study projects the size of Korean population, the prevalence of chronic diseases, and health expenditure over the 2014-2040 period using two waves (2012, 2013) of the Korea Health Panel and National Health Insurance Service database. Results: First, the prevalence of chronic diseases increases by 2040. The population with hypertension increases 2.04 times; the diabetes increases 2.43 times; and the cancer increases 3.38 times. Second, health expenditure on chronic diseases increases as well. Health expenditure on hypertension increases 4.33 times (1,098,753 million won in 2014 to 4,760,811 million won in 2040); diabetes increases 5.34 times (792,444 million won in 2014 to 4,232,714 million won in 2040); and cancer increases 6.09 times (4,396,223 million won in 2014 to 26,776,724 million won in 2040). Third, men and women who belong to the early middle-aged group (44-55 years old) as of 2014, have the highest increase rate in health spending. Conclusion: Most Korean literature on health expenditure estimation employs a macro-simulation approach and does not fully take into account personal characteristics and behaviors. Thus, this study aims to benefit medical administrators and policy makers to frame effective and targeted health policies by analyzing personal-level data with a microsimulation model and providing health expenditure projections by age group.

Intentions to Care for New Influenza A(H1N1) Patients and Influencing Factors: An application of theory of planned behavior (계획된 행위이론을 적용한 간호사의 신종인플루엔자 A 환자 간호의도와 영향 요인)

  • Jeong, Sun Young;Park, Hyo Sun;Wang, Hee-Jung;Kim, Mijung
    • Journal of Home Health Care Nursing
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    • v.22 no.1
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    • pp.78-87
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    • 2015
  • Purpose: The purpose of this study was to explore the intentions and influencing factors of intentions to care for New Influenza A ($H_1N_1$) patient Methods: This study involved a descriptive design using self-administered questionnaire. Intentions to care for H1N1 patient was evaluated by prediction tool, based on the Theory of Planned Behavior (TPB). The data were analyzed by SPSS 17.0 using descriptive statistics, t-test, ANOVA with a Scheffe test, Pearson's correlation and multiple regression analysis. Results: The level of intention was high, attitude was negative, subjective norm was high, and perceived behavioral control was moderate. The general regression model with intention as a dependent variable was statistically significant (F=39.31, p<.001). 28.1% of variance in intention was explained by subjective norm (t=8.75, p<.001), and perceived behavioral control (t=4.28, p<.001). Among the predictors, subjective norm had the greatest effect on intention (${\beta}=.44$). The nurse with the higher subjective norm and more positive perceived behavioral control reported the higher intention. Conclusion: The findings of this study suggested that the various aspects of nurse's characteristics should be considered when establishing strategies to improve the nurse's intention for care of infectious disease.

The Role of MicroRNAs in Regulatory T Cells and in the Immune Response

  • Ha, Tai-You
    • IMMUNE NETWORK
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    • v.11 no.1
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    • pp.11-41
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    • 2011
  • The discovery of microRNA (miRNA) is one of the major scientific breakthroughs in recent years and has revolutionized current cell biology and medical science. miRNAs are small (19~25nt) noncoding RNA molecules that post-transcriptionally regulate gene expression by targeting the 3' untranslated region (3'UTR) of specific messenger RNAs (mRNAs) for degradation of translation repression. Genetic ablation of the miRNA machinery, as well as loss or degradation of certain individual miRNAs, severely compromises immune development and response, and can lead to immune disorders. Several sophisticated regulatory mechanisms are used to maintain immune homeostasis. Regulatory T (Treg) cells are essential for maintaining peripheral tolerance, preventing autoimmune diseases and limiting chronic inflammatory diseases. Recent publications have provided compelling evidence that miRNAs are highly expressed in Treg cells, that the expression of Foxp3 is controlled by miRNAs and that a range of miRNAs are involved in the regulation of immunity. A large number of studies have reported links between alterations of miRNA homeostasis and pathological conditions such as cancer, cardiovascular disease and diabetes, as well as psychiatric and neurological diseases. Although it is still unclear how miRNA controls Treg cell development and function, recent studies certainly indicate that this topic will be the subject of further research. The specific circulating miRNA species may also be useful for the diagnosis, classification, prognosis of diseases and prediction of the therapeutic response. An explosive literature has focussed on the role of miRNA. In this review, I briefly summarize the current studies about the role of miRNAs in Treg cells and in the regulation of the innate and adaptive immune response. I also review the explosive current studies about clinical application of miRNA.

Bayesian spatial analysis of obesity proportion data (비만율 자료에 대한 베이지안 공간 분석)

  • Choi, Jungsoon
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.5
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    • pp.1203-1214
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    • 2016
  • Obesity is a risk factor for various diseases as well as itself a disease and associated with socioeconomic factors. The obesity proportion has been increasing in Korea over about 15 years so that investigation of the socioeconomic factors related with obesity is important in terms of preventation of obesity. In particular, the association between obesity and socioeconomic status varies with gender and has spatial dependency. In the paper, we estimate the effects of socioeconomic factors on obesity proportion by gender, considering the spatial correlation. Here, a conditional autoregressive model under the Bayesian framework is used in order to take into account the spatial dependency. For the real applicaiton, we use the obestiy proportion dataset at 25 districts of Seoul in 2010. We compare the proposed spatial model with a non-spatial model in terms of the goodness-of-fit and prediction measures so the spatial model performs well.