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RISS 인기검색어
- 검색키워드
- 저자 : 전티나 ( Christina Jeon ) (검색결과 2 건)
- 무료
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지선하 ( Sun Ha Jee ),정금지 ( Keum Ji Jung ),전티나 ( Christina Jeon ),김희진 ( Hee Jin Kim ),윤영덕 ( Young Duk Yun ),김일순 ( Il Soon Kim ) 한국보건정보통계학회(구 한국보건통계학회) 2014 보건정보통계학회지 Vol.39 No.1
Objectives: The purpose of the study was to estimate relative risk and attributable risk of 35 tobacco-related diseases and to compute total medical expenses on smoking by providing a cohort study with 20 years follow-up period. Methods: Smoking-attributable medical costs were calculated by applying the percentages of population attributable risks (PARs) to the estimated medical costs by the tobacco related diseases in 2012. In this study, PARs were obtained by using relative risks from the Korean Cancer Prevention Study and the previous studies, and population smoking prevalence surveyed in 1990 conducted by Korean Institute of Tuberculosis. Results: As a result, the medical expenses from tobacco use were 1,846,562,350,000 won (about 3.86% of total medical expenses). The top 5 medical expenses on tobacco-related diseases were ischemic heart diseases, cerebrovascular diseases, lung cancer, diabetes, and chronic obstructive pulmonary disease, respectively. More than a half percent of total medical expenses (about one billion dollars) were spent from these five, tobacco-related diseases. Conclusions: While the harmful effect of smoking is expected to have a steady increase for a while, antismoking policy should be reinforced to reduce the risk of disease incidence, and the medical expenses for treating the tobacco-related diseases.
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정금지 ( Keum Ji Jung ),김소리울 ( Soriul Kim ),윤미욱 ( Miwuk Yun ),전티나 ( Christina Jeon ),지선하 ( Sun Ha Jee ) 한국보건정보통계학회(구 한국보건통계학회) 2014 보건정보통계학회지 Vol.39 No.1
Objectives: In genome-wide association studies (GWASs), single-nucleotide polymorphisms (SNPs) that have been identified as cancer-associated loci are common, but they confer only small increases in risk. The question was whether combining multiple disease-related SNPs and the modest effects within Genetic Risk Score (GRS) may be useful in identifying subgroups that are at high risk of cancer. Methods: In this paper, we first reviewed articles that examined the predictability of GRS on cancer prediction models. Our data sources included a PubMed search of the literature published until February 2014. Secondly, we have calculated the GRS using the data example data with five SNPs related colorectal cancer (CRC) obtained from the Korean cancer prevention study II. Two approaches were used to calculate the GRS: a simple risk alleles count method (counted GRS) and a weighted method based on the genotype frequencies for each SNP and the effect sizes (allelic odds ratio or beta coefficient) from our study (weighted GRS). Results: Of 31 studies initially identified, 16 (135,110 participants) met the inclusion criteria. Among 16 articles, 7 studies were related to prostate cancer, 6 studies to breast cancer, and 3 studies to colon cancer and lung cancer. Fifteen studies except for one study concluded that in general, a genetic score may be helpful or useful in identifying the high risk group and particularly to determining the high risk individual among patients within a ‘‘gray zone’’ of cancer risk. The weighted GRS with age and sex (AUC=0.9333) had higher predictability on the CRC risk than the model with GRS alone (AUC=0.816). Conclusions: Although adding GRS improves prediction model performance, the clinical utility of these genetic risk models is limited. Nonetheless, the modelling suggests public health potential since it is possible to stratify the population into cancer risk categories, thereby informing targeted prevention and management.
KCI
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