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The clinical meaning of the area under a Receiver Operating Characteristic curve for the evaluation of the performance of disease markers
STEFANO PARODI, Damiano Verda, Francesca Bagnasco, Marco Muselli
Epidemiol Health. 2022;e2022088.   Published online October 17, 2022
DOI: https://doi.org/10.4178/epih.e2022088    [Accepted]
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AbstractAbstract PDF
Abstract
The area under a Receiver Operating Characteristic (ROC) curve (AUC) is a popular measure of pure diagnostic accuracy, which is independent from the proportion of diseased subjects in the analysed sample. However, its actual usefulness in clinical setting has been questioned, because it does not seem directly related to the actual performance of a diagnostic marker in identifying diseased and non-diseased subjects in real clinical settings. This study evaluates the relation between AUC and the proportion of correct classifications (global diagnostic accuracy, GDA) in relation to the shape of the corresponding ROC curves. We demonstrate that AUC represents an upward biased measure of GDA at an optimal accuracy cut-off for balanced groups. The size of bias depends on the shape of the ROC plot and on the proportion of diseased and non-diseased subjects. In proper curves the bias is independent from the diseased/non-diseased ratio and can be easily estimated and removed. Moreover, the comparison between two partial AUCs can be replaced by a more powerful test for the corresponding whole AUCs. Applications to three real data sets are provided, which include: a marker for a hormone deficit in children; two tumour markers for malignant mesothelioma; two gene expression profiles in ovarian cancer patients. AUC is a measure of accuracy with a potential clinical relevance for the evaluation of disease markers. Clinical meaning of ROC parameters should always be evaluated analysing the shape of the corresponding ROC curve.
Summary
Korean summary
Key Message
Meta-analysis of diagnostic test accuracy studies with multiple thresholds for data integration
Sung Ryul Shim
Epidemiol Health. 2022;44:e2022083.   Published online September 28, 2022
DOI: https://doi.org/10.4178/epih.e2022083
  • 1,428 View
  • 135 Download
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
OBJECTIVES
The objective of this study is to introduce methods to use all of the information without omission when individual studies provide multiple effect sizes according to multiple cut-off values (thresholds) during diagnostic test accuracy (DTA) for data integration. For diagnostic test meta-analysis, a general performance method for synthesizing data according to one cut value in one study and a performance method for synthesizing data according to two or more cut values in one study were compared and analyzed.
METHODS
As sample data for meta-analysis of DTA studies, 13 DTA studies on prostate cancer (34 effect sizes including total cut-offs) were collected. The summary statistics were calculated and the summary line was analyzed using the “meta”, “mada”, and “diagmeta” packagesof the R software.
RESULTS
The summary statistics of the random effect model univariate analysis of the “meta” package with a single cut-off corresponding to the highest Youden index in a single study and those of the bivariate analysis of the “mada” package were highly similar. However, in the bivariate analysis of the “diagmeta” package including all cut-off values, the sensitivity decreased and the specificity increased as the amount of data increased.
CONCLUSIONS
Considering the heterogeneity of the summary receiver op erating characteristic curve and the use of all given cut-offs, the use of the bivariate analysis model of the “diagmeta” package is recommended. This study focused on practical methods of DTA rather than theoretical concepts for use by researchers whose fields of study are non-statistics related. By performing this study, we hope that many researchers will use R software to determine the DTA more easily, and that there will be greater interest in related research.
Summary
Korean summary
본 연구는 진단검사 메타분석시 개별 대상연구가 다수의 기준치 (cut-off value, threshold)에 따른 여러 개의 효과크기를 제공하고 있을 때, 정보의 누락없이 이를 모두 사용하는 방법과 더불어 기존의 수행방법도 비교 분석하였기에 연구에 적합한 모델 선택에 도움이 될 것이다.
Key Message
The objective of this study is to introduce methods to use all of the information without omission when indi¬vidual studies provide multiple effect sizes according to multiple cut-off values (thresholds) during diagnostic test accuracy (DTA) for data integration.
Development and validation of the Pediatric-Youth Hyperphagia Assessment for Prader-Willi syndrome
Sung Yoon Cho, Danbee Kang, Minji Im, Aram Yang, Min-Sun Kim, Jiyeon Kim, Eu-Seon Noh, Eun Kyung Kwon, Eujin Choi, Sunju Han, Young Ah Park, Min Jung Kwak, Youngha Kim, Juhee Cho, Dong-Kyu Jin
Epidemiol Health. 2022;44:e2022014.   Published online January 10, 2022
DOI: https://doi.org/10.4178/epih.e2022014
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AbstractAbstract AbstractSummary PDF
Abstract
OBJECTIVES
Hyperphagia is a highly stressful, life-threatening feature of Prader-Willi syndrome (PWS). It is important to assess this complex behavior accurately over time. This study aimed to develop and validate the Pediatric-Youth Hyperphagia Assessment for Prader-Willi syndrome (PYHAP) as a tool targeting children and adolescents.
METHODS
After an extensive literature review and qualitative interviews, the final version of the PYHAP with 14 questions in 3 domains (verbal [5], behavior [4], and social [5]) was developed and tested at Samsung Medical Center in Seoul, Korea from July 2018 to September 2019. Exploratory factor analysis and confirmatory factor analysis (CFA) were performed to confirm construct validity. The correlations between the PYHAP and the Korean Children’s Eating Behavior Questionnaire (K-CEBQ) were calculated to evaluate convergent and discriminant validity. Criterion validity and the validity of the response categories were also tested.
RESULTS
Cronbach’s alpha coefficient of the PYHAP was 0.91. The fit indices for CFA were good (comparative fit index, 0.87; standardized root mean squared residual, 0.08). The domains of the PYHAP were closely correlated with the relevant domains of the K-CEBQ. The accuracy of the PYHAP score for predicting uncontrolled hyperphagia was good (area under the curve, 0.75; 95% confidence interval, 0.65 to 0.85).
CONCLUSIONS
The PYHAP was confirmed to be a reliable and valid tool to evaluate hyperphagia in children and adolescents with PWS via caregivers’ assessments. It is recommended to use the PYHAP to communicate with parents or caregivers about patients’ hyperphagia or to monitor and manage extreme behaviors in children with PWS.
Summary
Korean summary
프래더 윌리 증후군에서 '조절되지 않는 식욕'은 환자의 수명과 삶의 질에 매우 중요한 문제로, 최근 식욕 억제제 개발을 위한 연구가 활발히 이뤄지고 있으나 약제의 유효성을 객관적으로 평가하는 도구는 부족한 상황입니다. 본 연구는 주부양자를 통하여 평가가 가능한 프래더윌리 증후군 소아청소년 환자들의 식욕심각도 평가도구를 개발하였고, 그것의 신뢰성과 타당성을 입증하였습니다.
Key Message
Pediatric-Youth Hyperphagia Assessment for Prader-Willi syndrome (PYHAP) is a reliable and valid tool to evaluate hyperphagia in children and adolescents with PWS via caregivers’ assessments.
Korea National Health and Nutrition Examination Survey, 20th anniversary: accomplishments and future directions
Kyungwon Oh, Yoonjung Kim, Sanghui Kweon, Soyeon Kim, Sungha Yun, Suyeon Park, Yeon-Kyeng Lee, Youngtaek Kim, Ok Park, Eun Kyeong Jeong
Epidemiol Health. 2021;43:e2021025.   Published online April 19, 2021
DOI: https://doi.org/10.4178/epih.e2021025
  • 11,362 View
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  • 23 Citations
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
The Korea National Health and Nutrition Examination Survey (KNHANES) was initiated in 1998 to provide evidence for the development and evaluation of health policies and programs. The Korea Disease Control and Prevention Agency is responsible for the KNHANES and has conducted it as a series of surveys. Over the past 20 years, efforts to produce accurate, timely, and nationwide health statistics have been refined by establishing a continuous annual survey system with full-time field staff, incrementally expanding survey components, collaborating with relevant academic societies for quality control, and revising the survey methods. Additionally, the utility of the collected data was increased by linking the KNHANES data with related data from other government agencies or institutions and making the overall data publicly available on the official website of KNHANES (https://knhanes.kdca.go.kr). Additional long-term plans are being developed, including plans to continue producing nationwide health indicators and invigorating the utilization of the KNHANES data.
Summary
Korean summary
국민건강영양조사는 국민건강증진법제16조에 근거하여 1998년부터 우리 국민의 건강수준, 건강행태, 식품 및 영양소 섭취 실태에 대한 국가단위 통계를 산출하는 조사사업이다. 본 연구에서는 건강지표 생산 확대, 조사 자료 활용도 향상 등 20년간의 성과를 요약하고 사회환경과 조사여건 변화를 반영한 건강통계 생산의 발전 방안을 제시하였다.
Key Message
The Korea National Health and Nutrition Examination Survey (KNHANES) is an ongoing surveillance system that was initiated in 1998 based on Ar¬ticle 16 of the National Health Promotion Act to produce nationwide statistics regarding the health status, health behaviors, and food and nutrient consumption of the Korean population. In this study, the 20-year accomplishments of the KNHANES including vigorous production of health indicators and improvement of data utilization are summarized, and future plans are presented to improve the health statistics to reflect changes in the social and survey environments.

Citations

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    Journal of Korean Medical Science.2023;[Epub]     CrossRef
  • Sex-Specific Trends in the Prevalence of Hypertension and the Number of People With Hypertension: Analysis of the Korea National Health and Nutrition Examination Survey (KNHANES) 1998–2018
    Eunsun Seo, Sunjae Jung, Hokyou Lee, Hyeon Chang Kim
    Korean Circulation Journal.2022; 52(5): 382.     CrossRef
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    Nutrients.2022; 14(4): 880.     CrossRef
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    Environmental Research.2022; 212: 113080.     CrossRef
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    Ga Bin Lee, Yoonjung Kim, Suyeon Park, Hyeon Chang Kim, Kyungwon Oh
    Epidemiology and Health.2022; 44: e2022041.     CrossRef
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    Hyunsuk Jeong, Suyeon Park, Jihee Kim, Kyungwon Oh, Hyeon Woo Yim
    Epidemiology and Health.2022; 44: e2022042.     CrossRef
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    Diabetes & Metabolism Journal.2022; 46(3): 417.     CrossRef
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    Scientific Reports.2022;[Epub]     CrossRef
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Individual-based simulation model for COVID-19 transmission in Daegu, Korea
Woo-Sik Son
Epidemiol Health. 2020;42:e2020042.   Published online June 15, 2020
DOI: https://doi.org/10.4178/epih.e2020042
  • 9,063 View
  • 267 Download
  • 5 Citations
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
OBJECTIVES
The aims of this study were to obtain insights into the current coronavirus disease 2019 (COVID-19) epidemic in the city of Daegu, which accounted for 6,482 of the 9,241 confirmed cases in Korea as of March 26, 2020, to predict the future spread, and to analyze the impact of school opening.
METHODS
Using an individual-based model, we simulated the spread of COVID-19 in Daegu. An individual can be infected through close contact with infected people in a household, at work/school, and at religious and social gatherings. We created a synthetic population from census sample data. Then, 9,000 people were randomly selected from the entire population of Daegu and set as members of the Shincheonji Church. We did not take into account population movements to and from other regions in Korea.
RESULTS
Using the individual-based model, the cumulative confirmed cases in Daegu through March 26, 2020, were reproduced, and it was confirmed that the hotspot, i.e., the Shincheonji Church had a different probability of infection than non-hotspot, i.e., the Daegu community. For 3 scenarios (I: school closing, II: school opening after April 6, III: school opening after April 6 and the mean period from symptom onset to hospitalization increasing to 4.3 days), we predicted future changes in the pattern of COVID-19 spread in Daegu.
CONCLUSIONS
Compared to scenario I, it was found that in scenario III, the cumulative number of patients would increase by 107 and the date of occurrence of the last patient would be delayed by 92 days.
Summary
Korean summary
신천지 교인 집단이 hotspot이 되어 지역사회로 전파된 대구의 COVID-19 확산을 시뮬레이션하였다. Individual based model을 이용하여 신천지 교인 집단, 즉 hotspot과 non-hotspot이 서로 다른 감염 확률을 갖고 있음을 확인하였으며, 4월 6일로 예정된 개학이 대구 지역 COVID-19 확산에 어떤 영향을 미칠지 분석하였다.
Key Message

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    Yonsei Medical Journal.2023; 64(1): 1.     CrossRef
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Equivalence model: A new graphical model for causal inference
Jalal Poorolajal
Epidemiol Health. 2020;42:e2020024.   Published online April 9, 2020
DOI: https://doi.org/10.4178/epih.e2020024
  • 8,257 View
  • 176 Download
  • 4 Citations
AbstractAbstract PDF
Abstract
Although several causal models relevant to epidemiology have been proposed, a key question that has remained unanswered is why some people at high-risk for a particular disease do not develop the disease while some people at low-risk do develop it. The equivalence model, proposed herein, addresses this dilemma. The equivalence model provides a graphical description of the overall effect of risk and protective factors at the individual level. Risk factors facilitate the occurrence of the outcome (the development of disease), whereas protective factors inhibit that occurrence. The equivalence model explains how the overall effect relates to the occurrence of the outcome. When a balance exists between risk and protective factors, neither can overcome the other; therefore, the outcome will not occur. Similarly, the outcome will not occur when the units of the risk factor(s) are less than or equal to the units of the protective factor(s). In contrast, the outcome will occur when the units of the risk factor(s) are greater than the units of the protective factor(s). This model can be used to describe, in simple terms, causal inferences in complex situations with multiple known and unknown risk and protective factors. It can also justify how people with a low level of exposure to one or more risk factor(s) may be affected by a certain disease while others with a higher level of exposure to the same risk factor(s) may remain unaffected.
Summary
Korean summary
Key Message

Citations

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Network meta-analysis: application and practice using R software
Sung Ryul Shim, Seong-Jang Kim, Jonghoo Lee, Gerta Rücker
Epidemiol Health. 2019;41:e2019013.   Published online April 8, 2019
DOI: https://doi.org/10.4178/epih.e2019013
  • 23,444 View
  • 1,305 Download
  • 96 Citations
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
The objective of this study is to describe the general approaches to network meta-analysis that are available for quantitative data synthesis using R software. We conducted a network meta-analysis using two approaches: Bayesian and frequentist methods. The corresponding R packages were “gemtc” for the Bayesian approach and “netmeta” for the frequentist approach. In estimating a network meta-analysis model using a Bayesian framework, the “rjags” package is a common tool. “rjags” implements Markov chain Monte Carlo simulation with a graphical output. The estimated overall effect sizes, test for heterogeneity, moderator effects, and publication bias were reported using R software. The authors focus on two flexible models, Bayesian and frequentist, to determine overall effect sizes in network meta-analysis. This study focused on the practical methods of network meta-analysis rather than theoretical concepts, making the material easy to understand for Korean researchers who did not major in statistics. The authors hope that this study will help many Korean researchers to perform network meta-analyses and conduct related research more easily with R software.
Summary
Korean summary
통계프로그램으로서의 R이 대세인 연구환경에서 R을 활용한 체계적인 메타분석 안내서가 요구되어지며 본 연구는 이에 대한 좋은 해답이 될 것이다. 더욱이 본 연구는 네트워크 메타분석 (Network meta-analysis)의 이론과 더불어 R을 활용한 실습위주의 내용으로 구성되어져 있어 누구나 쉽게 실행할 수 있을 것이다. 본 연구를 통하여 많은 연구자들이 보다 쉽게 본인의 연구분야에 적용하여 관련 연구가 활성화되기를 바란다.
Key Message

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Intervention meta-analysis: application and practice using R software
Sung Ryul Shim, Seong-Jang Kim
Epidemiol Health. 2019;41:e2019008.   Published online March 28, 2019
DOI: https://doi.org/10.4178/epih.e2019008
  • 17,011 View
  • 503 Download
  • 31 Citations
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
The objective of this study was to describe general approaches for intervention meta-analysis available for quantitative data synthesis using the R software. We conducted an intervention meta-analysis using two types of data, continuous and binary, characterized by mean difference and odds ratio, respectively. The package commands for the R software were “metacont”, “metabin”, and “metagen” for the overall effect size, “forest” for forest plot, “metareg” for meta-regression analysis, and “funnel” and “metabias” for the publication bias. The estimated overall effect sizes, test for heterogeneity and moderator effect, and the publication bias were reported using the R software. In particular, the authors indicated methods for calculating the effect sizes of the target studies in intervention meta-analysis. This study focused on the practical methods of intervention meta-analysis, rather than the theoretical concepts, for researchers with no major in statistics. Through this study, the authors hope that many researchers will use the R software to more readily perform the intervention meta-analysis and that this will in turn generate further related research.
Summary
Korean summary
통계프로그램으로서의 R이 대세인 연구환경에서 R을 활용한 체계적인 메타분석 안내서가 요구되어지며 본 연구는 이에 대한 좋은 해답이 될 것이다. 더욱이 본 연구는 메타분석 (Intervention meta-analysis)의 이론과 더불어 R을 활용한 실습위주의 내용으로 구성되어져 있어 누구나 쉽게 실행할 수 있을 것이다. 본 연구를 통하여 많은 연구자들이 보다 쉽게 본인의 연구분야에 적용하여 관련 연구가 활성화되기를 바란다.
Key Message

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Diagnostic test accuracy: application and practice using R software
Sung Ryul Shim, Seong-Jang Kim, Jonghoo Lee
Epidemiol Health. 2019;41:e2019007.   Published online March 28, 2019
DOI: https://doi.org/10.4178/epih.e2019007
  • 14,991 View
  • 538 Download
  • 32 Citations
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
The objective of this paper is to describe general approaches of diagnostic test accuracy (DTA) that are available for the quantitative synthesis of data using R software. We conduct a DTA that summarizes statistics for univariate analysis and bivariate analysis. The package commands of R software were “metaprop” and “metabin” for sensitivity, specificity, and diagnostic odds ratio; forest for forest plot; reitsma of “mada” for a summarized receiver-operating characteristic (ROC) curve; and “metareg” for meta-regression analysis. The estimated total effect sizes, test for heterogeneity and moderator effect, and a summarized ROC curve are reported using R software. In particular, we focus on how to calculate the effect sizes of target studies in DTA. This study focuses on the practical methods of DTA rather than theoretical concepts for researchers whose fields of study were non-statistics related. By performing this study, we hope that many researchers will use R software to determine the DTA more easily, and that there will be greater interest in related research.
Summary
Korean summary
통계프로그램으로서의 R이 대세인 연구환경에서 R을 활용한 체계적인 메타분석 안내서가 요구되어지며 본 연구는 이에 대한 좋은 해답이 될 것이다. 더욱이 본 연구는 진단검사 메타분석 (Diagnostic test accuracy)의 이론과 더불어 R을 활용한 실습위주의 내용으로 구성되어져 있어 누구나 쉽게 실행할 수 있을 것이다. 본 연구를 통하여 많은 연구자들이 보다 쉽게 본인의 연구분야에 적용하여 관련 연구가 활성화되기를 바란다.
Key Message

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Dose-response meta-analysis: application and practice using the R software
Sung Ryul Shim, Jonghoo Lee
Epidemiol Health. 2019;41:e2019006.   Published online March 28, 2019
DOI: https://doi.org/10.4178/epih.e2019006
  • 12,816 View
  • 448 Download
  • 15 Citations
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
The objective of this study was to describe the general approaches of dose-response meta-analysis (DRMA) available for the quantitative synthesis of data using the R software. We conducted a DRMA using two types of data, the difference of means in continuous data and the odds ratio in binary data. The package commands of the R software were “doseresmeta” for the overall effect sizes that were separated into a linear model, quadratic model, and restricted cubic split model for better understanding. The effect sizes according to the dose and a test for linearity were demonstrated and interpreted by analyzing one-stage and two-stage DRMA. The authors examined several flexible models of exposure to pool study-specific trends and made a graphical presentation of the dose-response trend. This study focused on practical methods of DRMA rather than theoretical concepts for researchers who did not major in statistics. The authors hope that this study will help many researchers use the R software to perform DRMAs more easily, and that related research will be pursued.
Summary
Korean summary
통계프로그램으로서의 R이 대세인 연구환경에서 R을 활용한 체계적인 메타분석 안내서가 요구되어지며 본 연구는 이에 대한 좋은 해답이 될 것이다. 더욱이 본 연구는 용량-반응 메타분석 (Dose-response meta-analysis)의 이론과 더불어 R을 활용한 실습위주의 내용으로 구성되어져 있어 누구나 쉽게 실행할 수 있을 것이다. 본 연구를 통하여 많은 연구자들이 보다 쉽게 본인의 연구분야에 적용하여 관련 연구가 활성화되기를 바란다.
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The unrealized potential: cohort effects and age-period-cohort analysis
Jongho Heo, Sun-Young Jeon, Chang-Mo Oh, Jongnam Hwang, Juhwan Oh, Youngtae Cho
Epidemiol Health. 2017;39:e2017056.   Published online December 5, 2017
DOI: https://doi.org/10.4178/epih.e2017056
  • 12,851 View
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  • 9 Citations
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
This study aims to provide a systematical introduction of age-period-cohort (APC) analysis to South Korean readers who are unfamiliar with this method (we provide an extended version of this study in Korean). As health data in South Korea has substantially accumulated, population-level studies that explore long-term trends of health status and health inequalities and identify macrosocial determinants of the trends are needed. Analyzing long-term trends requires to discern independent effects of age, period, and cohort using APC analysis. Most existing health and aging literature have used cross-sectional or short-term available panel data to identify age or period effects ignoring cohort effects. This under-use of APC analysis may be attributed to the identification (ID) problem caused by the perfect linear dependency across age, period, and cohort. This study explores recently developed three APC models to address the ID problem and adequately estimate the effects of A-P-C: intrinsic estimator-APC models for tabular age by period data; hierarchical cross-classified random effects models for repeated cross-sectional data; and hierarchical APC-growth curve models for accelerated longitudinal panel data. An analytic exemplar for each model was provided. APC analysis may contribute to identifying biological, historical, and socioeconomic determinants in long-term trends of health status and health inequalities as well as examining Korean’s aging trajectories and temporal trends of period and cohort effects. For designing effective health policies that improve Korean population’s health and reduce health inequalities, it is essential to understand independent effects of the three temporal factors by using the innovative APC models.
Summary
Korean summary
-건강수준 및 건강불평등의 장기적인 추이에 미치는 연령, 기간, 출생 코호트의 독립적인 영향을 분해하는 방법인 연령-기간-코호트 분석법(Age-Period-Cohort analysis)을 국내 보건의료 연구자들에게 체계적으로 소개함 -APC 분석법은 건강수준 및 건강행태, 건강불평등의 추세 분석 및 고령화, 만성질환, 생애주기 연구 등에 있어서 널리 활용될 수 있음 -APC 연구 결과를 바탕으로 향후 보건의료 정책에 있어서도 기간 또는 연령에 따른 정책뿐 아니라 코호트에 특정한 정책들도 고려되어야 할 필요가 있음
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Network meta-analysis: application and practice using Stata
Sungryul Shim, Byung-Ho Yoon, In-Soo Shin, Jong-Myon Bae
Epidemiol Health. 2017;39:e2017047.   Published online October 27, 2017
DOI: https://doi.org/10.4178/epih.e2017047
  • 26,746 View
  • 1,150 Download
  • 189 Citations
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
This review aimed to arrange the concepts of a network meta-analysis (NMA) and to demonstrate the analytical process of NMA using Stata software under frequentist framework. The NMA tries to synthesize evidences for a decision making by evaluating the comparative effectiveness of more than two alternative interventions for the same condition. Before conducting a NMA, 3 major assumptions—similarity, transitivity, and consistency—should be checked. The statistical analysis consists of 5 steps. The first step is to draw a network geometry to provide an overview of the network relationship. The second step checks the assumption of consistency. The third step is to make the network forest plot or interval plot in order to illustrate the summary size of comparative effectiveness among various interventions. The fourth step calculates cumulative rankings for identifying superiority among interventions. The last step evaluates publication bias or effect modifiers for a valid inference from results. The synthesized evidences through five steps would be very useful to evidence-based decision-making in healthcare. Thus, NMA should be activated in order to guarantee the quality of healthcare system.
Summary
Korean summary
같은 치료 목적을 가진 여러 치료법들 간의 효과를 상호 비교한 결과들을 통합하기 위해 개발된 네트워크 메타분석 (NMA) 결과는 의사결정의 우선순위를 정하는데 있어 가장 상위의 과학적 설득력을 갖는다. STATA 통계프로그램에서 제공하는 빈도주의 틀에 기반한 NMA를 수행하는데 점검해야 할 가정들과 실제 적용 과정을 소개한다.
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Meta-analysis for genome-wide association studies using case-control design: application and practice
Sungryul Shim, Jiyoung Kim, Wonguen Jung, In-Soo Shin, Jong-Myon Bae
Epidemiol Health. 2016;38:e2016058.   Published online December 18, 2016
DOI: https://doi.org/10.4178/epih.e2016058
  • 13,669 View
  • 368 Download
  • 3 Citations
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
This review aimed to arrange the process of a systematic review of genome-wide association studies in order to practice and apply a genome-wide meta-analysis (GWMA). The process has a series of five steps: searching and selection, extraction of related information, evaluation of validity, meta-analysis by type of genetic model, and evaluation of heterogeneity. In contrast to intervention meta-analyses, GWMA has to evaluate the Hardy–Weinberg equilibrium (HWE) in the third step and conduct meta-analyses by five potential genetic models, including dominant, recessive, homozygote contrast, heterozygote contrast, and allelic contrast in the fourth step. The ‘genhwcci’ and ‘metan’ commands of STATA software evaluate the HWE and calculate a summary effect size, respectively. A meta-regression using the ‘metareg’ command of STATA should be conducted to evaluate related factors of heterogeneities.
Summary
Korean summary
오늘날 활발히 수행되고 있는 유전체역학연구는 재현성의 문제, 대상자 크기의 한계 등으로 유전체 메타분석 연구가 요구되고 있다. 유전체 메타분석의 전반적인 수행 단계는 약물, 수술 등의 중개연구의 메타분석처럼 5 단계를 밟아 수행된다. 그러나, 유전체 메타분석은 3번째 과정에서 Hardy–Weinberg equilibrium (HWE) 검정과 4번째 과정에서 5가지 가능한 유전형 모델에 따라 메타분석이 이루어진다는 점에서 중개연구의 메타분석과 차이가 있다.
Key Message

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  • Recommendations for Statistical Reporting in Cardiovascular Medicine: A Special Report From the American Heart Association
    Andrew D. Althouse, Jennifer E. Below, Brian L. Claggett, Nancy J. Cox, James A. de Lemos, Rahul C. Deo, Sue Duval, Rory Hachamovitch, Sanjay Kaul, Scott W. Keith, Eric Secemsky, Armando Teixeira-Pinto, Veronique L. Roger
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Comparison of methods of extracting information for meta-analysis of observational studies in nutritional epidemiology
Jong-Myon Bae
Epidemiol Health. 2016;38:e2016003.   Published online January 11, 2016
DOI: https://doi.org/10.4178/epih.e2016003
  • 15,710 View
  • 240 Download
  • 5 Citations
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
OBJECTIVES
A common method for conducting a quantitative systematic review (QSR) for observational studies related to nutritional epidemiology is the “highest versus lowest intake” method (HLM), in which only the information concerning the effect size (ES) of the highest category of a food item is collected on the basis of its lowest category. However, in the interval collapsing method (ICM), a method suggested to enable a maximum utilization of all available information, the ES information is collected by collapsing all categories into a single category. This study aimed to compare the ES and summary effect size (SES) between the HLM and ICM.
METHODS
A QSR for evaluating the citrus fruit intake and risk of pancreatic cancer and calculating the SES by using the HLM was selected. The ES and SES were estimated by performing a meta-analysis using the fixedeffect model. The directionality and statistical significance of the ES and SES were used as criteria for determining the concordance between the HLM and ICM outcomes.
RESULTS
No significant differences were observed in the directionality of SES extracted by using the HLM or ICM. The application of the ICM, which uses a broader information base, yielded more-consistent ES and SES, and narrower confidence intervals than the HLM.
CONCLUSIONS
The ICM is advantageous over the HLM owing to its higher statistical accuracy in extracting information for QSR on nutritional epidemiology. The application of the ICM should hence be recommended for future studies.
Summary
Korean summary
영양역학과 관련하여 관찰연구 결과를 체계적 고찰을 할 때, 통상적으로 섭취가 가장 낮은 군을 기준으로 하여 가장 높은 군의 effect size (ES) 정보를 추출하는 Highest versus Lowest Method (HLM)을 적용한다. 그러나 주어진 정보를 최대한 활용한다는 점에서 구간의 정보들을 통합한 ES 정보로 메타분석에 적용하는 Interval Collapse Method (ICM)법이 제안되었다. HLM에 비하여 더 많은 정보를 활용한 ICM 적용을 한 결과, ES 뿐만 아니라 SES에서도 일치성을 보이면서 표준오차가 작아지는 현상을 확인하였다. 영양역학의 메타분석을 위해 추출하는 방법 중 정보를 보다 더 많이 활용하는 ICM이 HLM에 비하여 통계적 정확성의 이득을 더 갖기 때문에, 향후 적극 활성화할 필요가 있다.
Key Message

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    Jong-Myon Bae
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The causality between smoking and lung cancer among groups and individuals: addressing issues in tobacco litigation in South Korea
Young-Ho Khang
Epidemiol Health. 2015;37:e2015026.   Published online May 31, 2015
DOI: https://doi.org/10.4178/epih/e2015026
  • 15,949 View
  • 150 Download
  • 2 Citations
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Abstract
This article discusses issues on the causality between smoking and lung cancer, which have been raised during the tobacco litigation in South Korea. It should be recognized that the explanatory ability of risk factor(s) for inter-individual variations in disease occurrence is different from the causal contribution of the risk factor(s) to disease occurrence. The affected subjects of the tobacco litigation in South Korea are lung cancer patients with a history of cigarette smoking. Thus, the attributable fraction of the exposed rather than the population attributable fraction should be used in the tobacco litigation regarding the causal contribution of smoking to lung cancer. Scientific evidence for the causal relationship between smoking and lung cancer is based on studies of individuals and groups, studies in animals and humans, studies that are observational or experimental, studies in laboratories and communities, and studies in both underdeveloped and developed countries. The scientific evidence collected is applicable to both groups and individuals. The probability of causation, which is calculated based on the attributable fraction for the association between smoking and lung cancer, could be utilized as evidence to prove causality in individuals.
Summary
Korean summary
이 글에서는 우리나라 담배소송 과정에서 제기된 흡연과 폐암의 인과성에 대하여 논하였다. 질병 발생의 개인 간 변이에 대한 위험 요인의 설명력과 질병발생에 미치는 위험요인의 인과적 기여도는 다르다는 점을 지적하였다. 개인에서의 흡연과 폐암의 인과성에 대한 정보로 인과확률이 활용될 수 있음을 강조하였다.
Key Message

Citations

Citations to this article as recorded by  
  • Trends in the of epidemiological perspectives on the causality of occupational diseases
    Jun-Pyo Myong, Hyeongsu Kim, Kunsei Lee, Soung Hoon Chang
    Journal of the Korean Medical Association.2018; 61(8): 466.     CrossRef
  • Tobacco and epidemiology in Korea: old tricks, new answers?
    Alex Broadbent, Seung-sik Hwang
    Journal of Epidemiology and Community Health.2016; 70(6): 527.     CrossRef

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