Communications for Statistical Applications and Methods
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v.18
no.1
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pp.57-69
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2011
Researchers are continuously trying to find innovative diagnostic tests and published articles are accumulating at an enormous rate in many medical fields. Meta-analysis enables previously published study results to be reviewed and summarized; therefore, an objective assessment of diagnostic tests can be done with a meta-analysis of sensitivities and specificities. Data obtained by applying two diagnostic tests to a well-defined group of diseased patients produce a pair of sensitivity and by applying the same medical tests to a group of non-diseased subjects produce a pair of specificity. The statistical tests in the meta-analysis need to consider the correlatedness of the results from two diagnostic tests applied to the same diseased and non-diseased subjects. The associations between two diagnostic test results are often found to be unequal for the diseased and non-diseased subjects. In this paper, multivariate meta-analytic methods are studied by taking into account the different associations between correlated variables. On the basis of Monte Carlo simulations, we evaluate the performance of the multivariate meta-analysis methods proposed in this paper.
Jung, Gyeong Bok;Kang, In Soon;Lee, Young Ju;Kim, Dohyun;Park, Hun-Kuk;Lee, Gi-Ja;Kim, Chaekyun
Current Optics and Photonics
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v.1
no.4
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pp.412-420
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2017
Multinucleated bone resorptive osteoclasts differentiate from bone marrow-derived monocyte/macrophage precursor cells. During osteoclast differentiation, mononuclear pre-osteoclasts change their morphology and biochemical characteristics. In this study, Raman spectroscopy with multivariate techniques such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were used to extract biochemical information related to various cellular events during osteoclastogenesis. This technique allowed for label-free and noninvasive monitoring of differentiating cells, and clearly discriminated four different time points during osteoclast differentiation. The Raman band intensity showed significant time-dependent changes that increased up to day 4. The results of Raman spectroscopy agreed with results from atomic force microscopy (AFM) and tartrate-resistant acid phosphatase (TRAP) staining, a conventional biological assay. Under AFM, normal spindle-like mononuclear pre-osteoclasts became round and smaller at day 2 after treatment with a receptor activator of nuclear $factor-{\kappa}B$ ligand and they formed multinucleated giant cells at day 4. Thus, Raman spectroscopy, in combination with PCA-LDA, may be useful for noninvasive label-free quality assessment of cell status during osteoclast differentiation, enabling more efficient optimization of the bioprocesses.
Purpose: We evaluated prognostic value of the 8th edition of the American Joint Committee on Cancer/International Union for Cancer Control (AJCC/UICC) staging system for nasopharyngeal cancer and investigated whether tumor volume/metabolic information refined prognostication of anatomy based staging system. Materials and Methods: One hundred thirty-three patients with nasopharyngeal cancer who were staged with magnetic resonance imaging (MRI) and treated with intensity-modulated radiotherapy (IMRT) between 2004 and 2013 were reviewed. Multivariate analyses were performed to evaluate prognostic value of the 8th edition of the AJCC/UICC staging system and other factors including gross tumor volume and maximum standardized uptake value of primary tumor (GTV-T and SUV-T). Results: Median follow-up period was 63 months. In multivariate analysis for overall survival (OS), stage group (stage I-II vs. III-IVA) was the only significant prognostic factor. However, 5-year OS rates were not significantly different between stage I and II (100% vs. 96.2%), and between stage III and IVA (80.1% vs. 71.7%). Although SUV-T and GTV-T were not significant prognostic factors in multivariate analysis, those improved prognostication of stage group. The 5-year OS rates were significantly different between stage I-II, III-IV (SUV-T ≤ 16), and III-IV (SUV-T > 16) (97.2% vs. 78% vs. 53.8%), and between stage I, II-IV (GTV-T ≤ 33 mL), and II-IV (GTV-T > 33 mL) (100% vs. 87.3% vs. 66.7%). Conclusion: Current anatomy based staging system has limitations on prognostication for nasopharyngeal cancer despite the most accurate assessment of tumor extent by MRI. Tumor volume/metabolic information seem to improve prognostication of current anatomy based staging system, and further studies are needed to confirm its clinical significance.
Kang, Min Woo;Ko, Seo Young;Song, Sung Wook;Kim, Woo Jeong;Kang, Young Joon;Kang, Kyeong Won;Park, Hyun Soo;Park, Chang Bae;Kang, Jeong Ho;Bu, Ji Hwan;Lee, Sung Kgun
Journal of Trauma and Injury
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v.34
no.1
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pp.3-12
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2021
Purpose: To evaluate the severity of trauma, many scoring systems and predictive models have been presented. The quick Sequential Organ Failure Assessment (qSOFA) is a simple scoring system based on vital signs, and we expect it to be easier to apply to trauma patients than other trauma assessment tools. Methods: This study was a cross-sectional study of trauma patients who visited the emergency department of Jeju National University Hospital. We excluded patients under the age of 18 years and unknown outcomes. We calculated the qSOFA, the Modified Early Warning Score (mEWS), Revised Trauma Score (RTS), and Injury Severity Score (ISS) based on patients' initial vital signs and assessments performed in the emergency department (ED). The primary outcome was mortality within 14 days of trauma. We analyzed qSOFA scores using multivariate logistic regression analysis and compared the predictive accuracy of these scoring systems using the area under the receiver operating characteristic curve (AUROC). Results: In total, 27,764 patients were analyzed. In the multivariate logistic regression analysis of the qSOFA, the adjusted odds ratios with 95% confidence interval (CI) for mortality relative to a qSOFA score of 0 were 27.82 (13.63-56.79) for a qSOFA score of 1, 373.31 (183.47-759.57) for a qSOFA score of 2, and 494.07 (143.75-1698.15) for a qSOFA score of 3. In the receiver operating characteristic (ROC) curve analysis for the qSOFA, mEWS, ISS, and RTS in predicting the outcomes, for mortality, the AUROC for the qSOFA (AUROC [95% CI]; 0.912 [0.871-0.952]) was significantly greater than those for the ISS (0.700 [0.608-0.793]) and RTS (0.160 [0.108-0.211]). Conclusions: The qSOFA was useful for predicting the prognosis of trauma patients evaluated in the ED.
Cheolho, Lee;Hwirae, Kim;Kang-Hyun, Cho;Byeongki, Choi;Bora, Lee
Ecology and Resilient Infrastructure
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v.9
no.4
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pp.269-281
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2022
The prediction of changes regarding the distribution of vegetation and plant species according to climate changes is important for ecosystem management. In this study, we attempted to develop an assessment method to evaluate the possibility of the potential distribution of warm-temperate woody plant species of East Asia in Korea. To begin with, a list of warm-temperate woody plants distributed in China and Japan, but not in Korea, was prepared, and a database consisting their global distribution and bioclimatic variables was constructed. In addition, the warm-temperate vegetation zone in Korea was delineated using the coldness index and relevant bioclimatic data were collected. After the exclusion of multicollinearity among bioclimatic variables using correlation analysis, mean temperature of the coldest quarter, mean temperature diurnal range, and annual precipitation were selected as the major variables that influence the distribution of warm-temperate plants. A multivariate environment similarity surfaces (MESS) analysis was conducted to calculate the similarity scores between the distribution of these three bioclimatic variables in the global distribution sites of the East Asian warm-temperate woody plants and the Korean warm-temperate vegetation zone. Finally, using stepwise variable-selection regression, the mean temperature of the coldest quarter and annual precipitation were selected as the main bioclimatic variables that affect the MESS similarity index. The mean temperature of the coldest quarter accounted for 88% of the total variance. For a total of 319 East Asian warm-temperate woody plant species, the possibility of their potential distribution in Korea was evaluated by applying the constructed multivariate regression model that calculates the MESS similarity index.
Dan Shao;Qiang Gao;You Cheng;Dong-Yang Du;Si-Yun Wang;Shu-Xia Wang
Korean Journal of Radiology
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v.22
no.3
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pp.425-434
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2021
Objective: To investigate the potential value of 18F-fluorodeoxyglucose (FDG) PET/CT in predicting the survival of patients with primary tracheal malignant tumors. Materials and Methods: An analysis of FDG PET/CT findings in 37 primary tracheal malignant tumor patients with a median follow-up period of 43.2 months (range, 10.8-143.2 months) was performed. Cox proportional hazards regression analyses were used to assess the associations between quantitative 18F-FDG PET/CT parameters, other clinic-pathological factors, and overall survival (OS). A risk prognosis model was established according to the independent prognostic factors identified on multivariate analysis. A survival curve determined by the Kaplan-Meier method was used to assess whether the prognosis prediction model could effectively stratify patients with different risks factors. Results: The median survival time of the 37 patients with tracheal tumors was 38.0 months, with a 95% confidence interval of 10.8 to 65.2 months. The 3-year, 5-year and 10-year survival rate were 54.1%, 43.2%, and 16.2%, respectively. The metabolic tumor volume (MTV), total lesion glycolysis (TLG), maximum standardized uptake value, age, pathological type, extension categories, and lymph node stage were included in multivariate analyses. Multivariate analysis showed MTV (p = 0.011), TLG (p = 0.020), pathological type (p = 0.037), and extension categories (p = 0.038) were independent prognostic factors for OS. Additionally, assessment of the survival curve using the Kaplan-Meier method showed that our prognosis prediction model can effectively stratify patients with different risks factors (p < 0.001). Conclusion: This study shows that 18F-FDG PET/CT can predict the survival of patients with primary tracheal malignant tumors. Patients with an MTV > 5.19, a TLG > 16.94 on PET/CT scans, squamous cell carcinoma, and non-E1 were more likely to have a reduced OS.
The purpose of this study was to suggest methods to apply generalizability theory to mathematics teacher evaluation using classroom observations in Korea by analysing mathematics teachers in the U.S. using the instructional quality of assessment instrument as an illustrative example. The subjects were 96 teachers participating in Year 3 and Year 4 from the Middle-school Mathematics and the Institutional Setting of Teaching (MIST) project funded by the National Science Foundation since 2007. The MIST project investigates the following question: What does it takes to support mathematics teachers' development of ambitious and equitable instructional practices on a large scale (MIST, 2007). This study examined data based on both the univariate generalizability analysis using GENOVA program and the multivariate generalizability analysis using mGENOVA program. Specifically, this study determined the relative effects of each error source and investigated optimal measuring conditions to obtain the suitable generalizability coefficients. The methodology applied in this study can be utilized to find effective optimal measurement conditions for the mathematics teacher evaluation for professional development in Korea. Finally, this study discussed limitations of the results and suggested directions for future research.
Out of the total 17,000 reservoirs in Korea, 13,600 small agricultural reservoirs do not have hydrological measurement facilities, making it difficult to predict water storage volume and appropriate operation. This paper examined univariate and multivariate long short-term memory (LSTM) modeling to predict the storage rate of agricultural reservoirs using remote sensing and artificial intelligence. The univariate LSTM model used only water storage rate as an explanatory variable, and the multivariate LSTM model added n-day accumulative precipitation and date of year (DOY) as explanatory variables. They were trained using eight years data (2013 to 2020) for Idong Reservoir, and the predictions of the daily water storage in 2021 were validated for accuracy assessment. The univariate showed the root-mean square error (RMSE) of 1.04%, 2.52%, and 4.18% for the one, three, and five-day predictions. The multivariate model showed the RMSE 0.98%, 1.95%, and 2.76% for the one, three, and five-day predictions. In addition to the time-series storage rate, DOY and daily and 5-day cumulative precipitation variables were more significant than others for the daily model, which means that the temporal range of the impacts of precipitation on the everyday water storage rate was approximately five days.
Roder, David Murray;Ward, Gail Heather;Farshid, Gelareh;Gill, Peter Grantley
Asian Pacific Journal of Cancer Prevention
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v.15
no.14
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pp.5901-5908
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2014
Background: Data from BreastScreen Australia Screening and Assessment Services (SAS) for 2002-2010 were analysed to determine whether some SAS characteristics were more conducive that others to high screening performance, as indicated by high priority performance indicators and standards. Materials And Methods: Indicators investigated related to: numbers of benign open biopsies, screen-detected invasive cancers, and interval cancers, and wait times between screening and assessment. Multivariate Poisson regression was undertaken using as candidate predictors of performance, SAS size (screening volume), urban or rural location, year of screening, accreditation status, and percentages of clients from culturally and linguistically diverse backgrounds, rural and remote areas, and socio-economically disadvantaged areas. Results: Performance standards for benign biopsies and invasive cancer detection were uniformly met irrespective of SAS location and size. The interval cancer standard was also met, except in 2003 when the 95% confidence interval of the rate still incorporated the national standard. Performance indicators improved over time for: benign open biopsy for second or subsequent screening rounds; rates of invasive breast cancer detection for second or subsequent screening rounds; and rates of small cancer detection. No differences were found over time in interval cancer rates. Interval cancer rates did not differ between non-metropolitan and metropolitan SAS, although state-wide SAS had lower rates. The standard for wait time between screening and assessment (being assessed ${\leq}28$ days) was mostly unmet and this applied in particular to SAS with high percentages of culturally and linguistically diverse women in their screening populations. Conclusions: Gains in performance were observed, and all performance standards were met irrespective of SAS characteristics, except wait times to assessment. Additional descriptive data should be collected on SAS characteristics, and their associations with favourable screening performance, as these may be important when deciding on SAS design
Lee, Eun Jee;Lee, GeunWoo;Park, Juhee;Kim, Dong-Sook;Ahn, Hyeong Sik
Journal of the Korean Medical Association
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v.61
no.11
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pp.687-698
/
2018
Inappropriate antibiotic use significantly contributes to antibiotic resistance, resulting in reduced antibiotic efficacy and an increased burden of disease. The objective of this study was to investigate the characteristics of prescribers whose antibiotics use was high and to explore factors affecting the use of antibiotics by medical institutions. This study analyzed the National Health Insurance claims data from 2015. Antibiotic prescription data were analyzed in terms of the number of defined daily doses per 1,000 patients per day, according to the World Health Organization anatomical-therapeutic-chemical classification and methodologies for measuring the defined daily dose. We investigated the characteristics of prescribers and medical institutions with high antibiotic use. Multivariate regression analyses were performed on the basis of characteristics of the medical institution (number of patients, type of medical institution [hospital or clinic], age of the physician, etc.). The number of patients and number of beds were found to be significant factors affecting antibiotic use in hospitals, and the number of patients, region, and medical department were significant factors affecting antibiotic use at the level of medical institutions. These findings are expected to help policy-makers to better target future interventions to promote prudent antibiotic prescription.
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