• Asian Pacific Journal of Cancer Prevention
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• v.16 no.11
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• pp.4603-4608
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• 2015

Background: To determine the potential value of serum tumor markers in predicting pCR (pathological complete response) during neoadjuvant chemotherapy. Materials and Methods: We retrospectively monitored the pro-, mid-, and post-neoadjuvant treatment serum tumor marker concentrations in patients with locally advanced breast cancer (stage II-III) who accepted pre-surgical chemotherapy or chemotherapy in combination with targeted therapy at Fudan University Shanghai Cancer Center between September 2011 and January 2014 and investigated the association of serum tumor marker levels with therapeutic effect. Core needle biopsy samples were assessed using immunohistochemistry (IHC) prior to neoadjuvant treatment to determine hormone receptor, human epidermal growth factor receptor 2(HER2), and proliferation index Ki67 values. In our study, therapeutic response was evaluated by pCR, defined as the disappearance of all invasive cancer cells from excised tissue (including primary lesion and axillary lymph nodes) after completion of chemotherapy. Analysis of variance of repeated measures and receiver operating characteristic (ROC) curves were employed for statistical analysis of the data. Results: A total of 348 patients were recruited in our study after excluding patients with incomplete clinical information. Of these, 106 patients were observed to have acquired pCR status after treatment completion, accounting for approximately 30.5% of study individuals. In addition, 147patients were determined to be Her-2 positive, among whom the pCR rate was 45.6% (69 patients). General linear model analysis (repeated measures analysis of variance) showed that the concentration of cancer antigen (CA) 15-3 increased after neoadjuvant chemotherapy in both pCR and non-pCR groups, and that there were significant differences between the two groups (P=0.008). The areas under the ROC curves (AUCs) of pre-, mid-, and post-treatment CA15-3 concentrations demonstrated low-level predictive value (AUC=0.594, 0.644, 0.621, respectively). No significant differences in carcinoembryonic antigen (CEA) or CA12-5 serum levels were observed between the pCR and non-pCR groups (P=0.196 and 0.693, respectively). No efficient AUC of CEA or CA12-5 concentrations were observed to predict patient response toward neoadjuvant treatment (both less than 0.7), nor were differences between the two groups observed at different time points. We then analyzed the Her-2 positive subset of our cohort. Significant differences in CEA concentrations were identified between the pCR and non-pCR groups (P=0.039), but not in CA15-3 or CA12-5 levels (p=0.092 and 0.89, respectively). None of the ROC curves showed underlying prognostic value, as the AUCs of these three markers were less than 0.7. The ROC-AUCs for the CA12-5 concentrations of inter-and post-neoadjuvant chemotherapy in the estrogen receptor negative HER2 positive subgroup were 0.735 and 0.767, respectively. However, the specificity and sensitivity values were at odds with each other which meant that improving either the sensitivity or specificity would impair the efficiency of the other. Conclusions: Serum tumor markers CA15-3, CA12-5, and CEA might have little clinical significance in predicting neoadjuvant treatment response in locally advanced breast cancer.

• Management & Information Systems Review
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• v.29 no.2
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• pp.1-25
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• 2010

This study attempted to empirically test the determinants of stock returns in Korean stock market applying multi-factor model proposed by Haugen and Baker(1996). Regression models were developed using 16 variables related to liquidity, risk, historical price, price level, and profitability as independent variables and 690 stock monthly returns as dependent variable. For the statistical analysis, the data were collected from the Kis Value database and the tests of forecasting power in this study minimized various possible bias discussed in the literature as possible. The statistical results indicated that: 1) Liquidity, one-month excess return, three-month excess return, PER, ROE, and volatility of total return affect stock returns simultaneously. 2) Liquidity, one-month excess return, three-month excess return, six-month excess return, PSR, PBR, ROE, and EPS have an antecedent influence on stock returns. Meanwhile, realized returns of decile portfolios increase in proportion to predicted returns. This results supported previous study by Haugen and Baker(1996) and indicated that firm-characteristic model can better predict stock returns than CAPM. 3) The firm-characteristic model has better predictive power than Fama-French three-factor model, which indicates that a portfolio constructed based on this model can achieve excess return. This study found that expected return factor models are accurate, which is consistent with other countries' results. There exists a surprising degree of commonality in the factors that are most important in determining the expected returns among different stocks.

• Tuberculosis and Respiratory Diseases
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• v.67 no.2
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• pp.105-112
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• 2009

Background: Solitary pulmonary nodules (SPN) are encountered incidentally in 0.2% of patients who undergo chest X-ray or chest CT. Although SPN has malignant potential, it cannot be treated surgically by biopsy in all patients. The first stage is to determine if patients with SPN require periodic observation and biopsy or resection. An important early step in the management of patients with SPN is to estimate the clinical pretest probability of a malignancy. In every patient with SPN, it is recommended that clinicians estimate the pretest probability of a malignancy either qualitatively using clinical judgment or quantitatively using a validated model. This study examined whether Bayesian analysis or multiple logistic regression analysis is more predictive of the probability of a malignancy in SPN. Methods: From January 2005 to December 2008, this study enrolled 63 participants with SPN at the Kangnam Sacred Hospital. The accuracy of Bayesian analysis and Bayesian analysis with a FDG-PET scan, and Multiple logistic regression analysis was compared retrospectively. The accurate probability of a malignancy in a patient was compared by taking the chest CT and pathology of SPN patients with <30 mm at CXR incidentally. Results: From those participated in study, 27 people (42.9%) were classified as having a malignancy, and 36 people were benign. The result of the malignant estimation by Bayesian analysis was 0.779 (95% confidence interval [CI], 0.657 to 0.874). Using Multiple logistic regression analysis, the result was 0.684 (95% CI, 0.555 to 0.796). This suggests that Bayesian analysis provides a more accurate examination than multiple logistic regression analysis. Conclusion: Bayesian analysis is better than multiple logistic regression analysis in predicting the probability of a malignancy in solitary pulmonary nodules but the difference was not statistically significant.

• Journal of Gastric Cancer
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• v.9 no.3
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• pp.96-103
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• 2009

Purpose: Lymph node metastasis is an important factor in determining prognosis and therapeutic options for early gastric cancer (EGC) patients. Vascular endothelial growth factor (VEGF)-C and D are known as lymphangiogenic factors, and cyclooxygenase (COX)-2 is thought to play a role in lymph node metastasis in gastric carcinoma. This study was designed to determine whether the expression of VEGF-C, VEGF-D, and COX-2 is associated with clinicopathologic factors, especially lymph node metastasis in EGCs invading the submucosa. Materials and Methods: Tissue samples were obtained from 85 Patients undergoing standard gastrectomy with lymph node dissection between 1991 and 2007 in the Department of Surgery of Daejeon St. Mary's Hospital in Daejeon, Korea. All patients were diagnosed with gastric cancers and submucosal invasion. We examined the expression of VEGF-C, VEGF-D, and COX-2 using immunohistochemical methods. Results: Of the 85 patients, 16 (18.8%) had lymph node metastasis. VEGF-C, VEGF-D, and COX-2 were positively expressed in 34.1% (29/85), 22.3% (19/85), and 37.6% (32/85) of the patients. VEGF-C and COX-2 expression was significantly correlated with lymph node metastasis (P<0.05). A positive correlation existed between VEGF-C and COX-2 expression (P< 0.001). Conclusion: VEGF-C and COX-2 expression is associated with lymph node metastasis in gastric cancer with submucosal invasion. VEGF-C and COX-2 may thus be predictive markers for lymph node metastasis in EGC patients with submucosal invasion.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.1-19
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• 2018

Since stock movements forecasting is an important issue both academically and practically, studies related to stock price prediction have been actively conducted. The stock price forecasting research is classified into structured data and unstructured data, and it is divided into technical analysis, fundamental analysis and media effect analysis in detail. In the big data era, research on stock price prediction combining big data is actively underway. Based on a large number of data, stock prediction research mainly focuses on machine learning techniques. Especially, research methods that combine the effects of media are attracting attention recently, among which researches that analyze online news and utilize online news to forecast stock prices are becoming main. Previous studies predicting stock prices through online news are mostly sentiment analysis of news, making different corpus for each company, and making a dictionary that predicts stock prices by recording responses according to the past stock price. Therefore, existing studies have examined the impact of online news on individual companies. For example, stock movements of Samsung Electronics are predicted with only online news of Samsung Electronics. In addition, a method of considering influences among highly relevant companies has also been studied recently. For example, stock movements of Samsung Electronics are predicted with news of Samsung Electronics and a highly related company like LG Electronics.These previous studies examine the effects of news of industrial sector with homogeneity on the individual company. In the previous studies, homogeneous industries are classified according to the Global Industrial Classification Standard. In other words, the existing studies were analyzed under the assumption that industries divided into Global Industrial Classification Standard have homogeneity. However, existing studies have limitations in that they do not take into account influential companies with high relevance or reflect the existence of heterogeneity within the same Global Industrial Classification Standard sectors. As a result of our examining the various sectors, it can be seen that there are sectors that show the industrial sectors are not a homogeneous group. To overcome these limitations of existing studies that do not reflect heterogeneity, our study suggests a methodology that reflects the heterogeneous effects of the industrial sector that affect the stock price by applying k-means clustering. Multiple Kernel Learning is mainly used to integrate data with various characteristics. Multiple Kernel Learning has several kernels, each of which receives and predicts different data. To incorporate effects of target firm and its relevant firms simultaneously, we used Multiple Kernel Learning. Each kernel was assigned to predict stock prices with variables of financial news of the industrial group divided by the target firm, K-means cluster analysis. In order to prove that the suggested methodology is appropriate, experiments were conducted through three years of online news and stock prices. The results of this study are as follows. (1) We confirmed that the information of the industrial sectors related to target company also contains meaningful information to predict stock movements of target company and confirmed that machine learning algorithm has better predictive power when considering the news of the relevant companies and target company's news together. (2) It is important to predict stock movements with varying number of clusters according to the level of homogeneity in the industrial sector. In other words, when stock prices are homogeneous in industrial sectors, it is important to use relational effect at the level of industry group without analyzing clusters or to use it in small number of clusters. When the stock price is heterogeneous in industry group, it is important to cluster them into groups. This study has a contribution that we testified firms classified as Global Industrial Classification Standard have heterogeneity and suggested it is necessary to define the relevance through machine learning and statistical analysis methodology rather than simply defining it in the Global Industrial Classification Standard. It has also contribution that we proved the efficiency of the prediction model reflecting heterogeneity.

• Korean Journal of Social Welfare
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• v.54
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• pp.5-33
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• 2003

This study is about the re-validation evaluation of the family Relationship Scale (FRS), developed to measure the family relationship in the social work practice. This study aims at re-validating the FRS, developed and validated in by Yang in 2001 for more general utilization. The sample was married mates and females residing in Seoul. For Face Validity, the content analysis was performed, and the FRS was re-validated in the dimensions of Love & Caring, Acceptance, and Recognition, positive affection, empathy, and autonomy and flexibility for each area. Internal reliability was .93, and internal consistency among three dimensions was 93%. For Empirical Validity, the Construct validity, the Criterion validity, and the Discriminant validity were performed. Construct Validity was validated through factor analyses. Commonalities for the factor analysis was 54%, and the factor loading for each factor was over .45. The confirmative factor analysis also confirmed the fitness of the scale. For Predictive Validity of Criterion Validity, regression analysis showed that the family stress scores became lower as the scores of the family relationship became higher; the discriminant analysis revealed that the family stress turned low ill tile group of high scores of family relationship. The Correlation analysis for Concurrent Validity was performed and the results showed the positive and significant relationship with a couple communication level (r=54) and a parent-child communication level (r=64). Life satisfaction and mental health level also revealed significantly positive correlation to prove Convergent Validity. Physical health level revealed a weak relationship with family relationship providing the evidence of Discriminant Validity. Discriminance was also proved by the analysis of variance with demographics. Thus, Cross Validation was confirmed the validation of the FRS through the various analyses with the married population. This study result improved the validity generalization of the Scale and verify the generalized usage of this sociometric scale in the field of social work practice.

• Clinical and Experimental Pediatrics
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• v.50 no.5
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• pp.443-448
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• 2007

Purpose : To evaluate the potential prognostic value of the antithrombin-III (AT-III) level in the children with acute lung injury (ALI), we analyzed several early predictive factors of death including AT-III level at the onset of ALI and compared the relative risk of them for mortality. Methods : Over a 18-month period, a total of 198 children were admitted to our pediatric intensive care unit and 21 mechanically ventilated patients met ALI criteria, as defined by American-European consensus conference, i.e., bilateral pulmonary infiltrates and $PaO_2/FiO_2$ lower than 300 without left atrial hypertension. Demographic variables, hemodynamic and respiratory parameters, underlying diseases, as well as Pediatric Risk of Mortality-III (PRISM-III) scores and Lung Injury Score (LIS) at admission were collected. AT-III levels were measured within 3 hours after admission. These variables were compared between survivors and non-survivors and entered into a multiple logistic regression analysis to evaluate their independent prognostic roles. Results : The overall mortality rate was 38.1% (8/21). Non-survivors showed lower age, lower lung compliance, higher PEEP, higher oxygenation index (OI), lower arterial pH, lower $PaO_2/FiO_2$, higher PRISM-III score and LIS, and lower AT-III level. PRISM-III score, LIS, OI and decreased AT-III level (less than 70%) were independently associated with a risk of death and the odds ratio of decreased AT-III level for mortality is 2.75 (95% confidence interval; 1.28-4.12) Conclusion : These results suggest that the decreased level of AT-III is an important prognostic factor in children with ALI and the replacement of AT-III may be considered as an early therapeutic trial.

• Pediatric Infection and Vaccine
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• v.17 no.2
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• pp.169-176
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• 2010

Purpose : We aimed to evaluate predictive parameters for non-response to intravenous immunoglobulin (IVIG) in patients with Kawasaki disease (KD) before IVIG use using two controls. Methods : We evaluated 229 consecutive KD patients who were treated with 2 g/kg of IVIG at a single center. Those who had persistent fever >24 hours after IVIG infusion made up the 23 IVIG non-responders; the first control included a total 206 defervesced cases and the second control included 46 cases that were matched for age and pre-treatment fever duration to non-responders. Results : Demographic and clinical characteristics were similar in IVIG non-responders and responders at presentation. As for laboratory findings, the neutrophil differential, CRP, AST, ALT, and LDH were higher, and lymphocyte differential, total protein, albumin, platelet count, and total cholesterol were significantly lower in IVIG non-responders compared to responders by univariate analysis in both study designs. However in multivariate analysis, non-responders showed a significantly higher neutrophil differential (cutoff value, >77%, sensitivity 68.4% and specificity 79.5%) and lower cholesterol (<124 mg/dL, sensitivity 79% and specificity 70.5%). Whereas plasma albumin (<3.6 g/dL, sensitivity 73.7% and specificity 60%) was the sole laboratory parameter of non-responders in the second study design. Conclusion : Severity of inflammation in KD was reflected by higher or lower laboratory values at presentation. Because the multivariate analysis for these indices may be influenced by some confounding factors, including the numbers of patients of different ages and fever duration, other assessment modalities are needed for KD patients with the greatest risk of coronary artery lesions.

• Pediatric Infection and Vaccine
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• v.17 no.2
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• pp.108-113
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• 2010

Purpose : The aim of this study was to identify clinical availability of serum procalcitonin (PCT) compared with C-reactive protein (CRP) in prediction of bacterial infection in children. Methods : A retrospective study was conducted with children who had been admitted to the Department of Pediatrics with bacterial and viral infection between April 2008 and March 2009 and children who were admitted with Juvenile rheumatoid arthritis (JRA) between August 2007 and July 2009. Serum PCT levels were measured using an enzyme-linked fluorescent assay. Results : The study population included 10 patients with bacterial infection (group I), 69 with viral infection (group II), and 35 with JRA (group III). Mean PCT levels were significantly higher in group I than in group II or group III (P<0.05). Mean CRP levels were significantly higher in group I than in group II (P<0.05); however, mean CRP levels were not significantly higher in group I than in group III (P>0.05). Using a cutoff of 0.5 ng/mL for PCT and 8 mg/L for CRP, sensitivity and specificity in distinguishing between group I and the other groups were 60.0% and 92.3% for PCT and 60.0% and 40.1% for CRP, respectively. Positive and negative predictive values were 42.9% and 96.0% for PCT and 10.0% and 92.6% for CRP, respectively. Conclusion : Measurement of PCT concentrations appears to be more useful than CRP for distinguishing between bacterial infection and non-bacterial diseases in children.

• Investigative Magnetic Resonance Imaging
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• v.18 no.2
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• pp.133-143
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• 2014

Purpose : The aim of this study was to determine the magnetic resonance imaging (MRI) features associated with re-excision due to the presence of a positive margin after breast conserving therapy (BCT) in breast cancer patients. Materials and Methods: We reviewed the records of 286 consecutive breast cancer patients who received BCT between January 2006 and December 2007. Among 246 patients who had undergone BCT, 38 (15.4%) underwent immediate further surgery due to positive margin status. We analyzed the MRI findings using ${\chi}^2$ test, Fisher's exact test and t tests. Multivariate logistic regression was conducted for prediction of re-excision. Results: Tumor size (p < 0.001), lesion multiplicity (p = 0.003), and non-mass-like enhancement (NMLE) type on MRI (p < 0.001) were associated with margin involvement in BCT. On preoperative MRI, larger size (${\geq}5cm$) (odds ratio = 2.96), NMLE (odds ratio = 3.81), and multifocal lesions (odds ratio = 2.54) were positively associated with re-excision. In cases involving NMLE, segmental distribution was associated with a greater likelihood of immediate re-excision. Conclusion: Larger size, multiplicity, and NMLE on MRI are significantly associated with re-excision after BCT in breast cancer patients. For NMLE lesions, the segmental distribution pattern was predictive of re-excision.